Computer Sciences Commons^™

A Cyber Forensics Needs Analysis Survey: Revisiting The Domain's Needs A Decade Later, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili, Andrew Marrington

Electrical & Computer Engineering and Computer Science Faculty Publications

The number of successful cyber attacks continues to increase, threatening financial and personal security worldwide. Cyber/digital forensics is undergoing a paradigm shift in which evidence is frequently massive in size, demands live acquisition, and may be insufficient to convict a criminal residing in another legal jurisdiction. This paper presents the findings of the first broad needs analysis survey in cyber forensics in nearly a decade, aimed at obtaining an updated consensus of professional attitudes in order to optimize resource allocation and to prioritize problems and possible solutions more efficiently. Results from the 99 respondents gave compelling testimony that the following …

Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang

Research Collection School Of Computing and Information Systems

The fault detection of electrical or mechanical anomalies in induction motors has been a challenging problem for researchers over decades to ensure the safety and economic operations of industrial processes. To address this issue, this paper studies the stator current data obtained from inverter-fed laboratory induction motors and investigates the unique signatures of the healthy and faulty motors with the aim of developing knowledge based fault detection method for performing online detection of motor fault problems, such as broken-rotor-bar and bearing faults. Stator current data collected from induction motors were analyzed by leveraging fast Fourier transform (FFT), and the FFT …

Requirements Quick Notes, William L. Honig, Shingo Takada

Computer Science: Faculty Publications and Other Works

A short introduction to requirements and their role in system development. Includes industry definition of requirements, overview of basic requirements process including numbering of requirements, ties to testing, and traceability. An introduction to requirements quality attributes (correct, unambiguous, etc.) Includes references to requirements process, numbering, and quality papers.

Requirements Metrics - Definitions Of A Working List Of Possible Metrics For Requirements Quality, William L. Honig

Computer Science: Faculty Publications and Other Works

A work in progress to define a metrics set for requirements. Metrics are defined that apply to either the entire requirements set (requirements document as a whole) or individual atomic (or singular, individual) requirements statements. Requirements are identified with standard names and a identification scheme and include both subjective and objective measures.

An example metric for the full set of requirements: Rd2 - Requirements Consistency, Is the set of atomic requirements internally consistent, with no contradictions, no duplication between individual requirements? An example of a metric for a single requirement: Ra4 - Requirement Verifiability, How adequately can this requirement be …

A Method And A Case Study For The Selection Of The Best Available Tool For Mobile Device Forensics Using Decision Analysis, Shahzad Saleem, Oliver Popov, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The omnipresence of mobile devices (or small scale digital devices - SSDD) and more importantly the utility of their associated applications for our daily activities, which range from financial transactions to learning, and from entertainment to distributed social presence, create an abundance of digital evidence for each individual. Some of the evidence may be a result of illegal activities that need to be identified, understood and eventually prevented in the future. There are numerous tools for acquiring and analyzing digital evidence extracted from mobile devices. The diversity of SSDDs, types of evidence generated and the number of tools used to …

Harmonic Analysis In Integrated Energy System Based On Compressed Sensing, Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In …

Interactive Teachable Cognitive Agents: Smart Building Blocks For Multiagent Systems, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Developing a complex intelligent system by abstracting their behaviors, functionalities, and reasoning mechanisms can be tedious and time consuming. In this paper, we present a framework for developing an application or software system based on smart autonomous components that collaborate with the developer or user to realize the entire system. Inspired by teachable approaches and programming-by-demonstration methods in robotics and end-user development, we treat intelligent agents as teachable components that make up the system to be built. Each agent serves different functionalities and may have prebuilt operations to accomplish its own design objectives. However, each agent may also be equipped …

Improving The Sensitivity Of Unobtrusive Inactivity Detection In Sensor-Enabled Homes For The Elderly, Alvin C. Valera, Hwee-Pink Tan, Liming Bai

Research Collection School Of Computing and Information Systems

Unobtrusive in-home monitoring systems are gaining acceptability and are being deployed to enable relatives and caregivers to remotely monitor and provide timely care to their elderly loved ones or senior clients, respectively, who are living independently. Such systems can provide information about nonmovement or inactivity of the elderly resident. As prolonged inactivity could mean potential danger, several algorithms have been proposed to automatically detect unusually long durations of inactivity. Such schemes, however, suffer from low sensitivity due to their high detection latency. In this paper, we propose Dwell Time-enhanced Dynamic Threshold (DTDT), a scheme for computing adaptive alert thresholds that …

Graphene Valley, Daniel Applebaum

Missouri S&T’s Peer to Peer

Silicon Valley in northern California is the proverbial hub of technological innovation and industry. Its namesake derives from the fact that silicon acts as the main component in modern electronics; however, a new material called graphene is challenging its role. In its early years of research, it was evident that the qualities of graphene far exceeded expectations. Industries are going mad trying to come up with applications and consumer products. While headway has been made, it is hard to say how long it will take to see products advertising their new graphene capabilities. Before touch screens or graphene-based microprocessors can …

Human Activity Prediction By Mapping Grouplets To Recurrent Self-Organizing Map, Qianru Sun, Hong Liu, Mengyuan Liu, Tianwei Zhang

Research Collection School Of Computing and Information Systems

Human activity prediction is defined as inferring the high-level activity category with the observation of only a few action units. It is very meaningful for time-critical applications such as emergency surveillance. For efficient prediction, we represent the ongoing human activity by using body part movements and taking full advantage of inherent sequentiality, then find the best matching activity template by a proper aligning measurement.In streaming videos, dense spatio-temporal interest points (STIPs) are first extracted as low-level descriptors for their high detection efficiency. Then, sparse grouplets, i.e., clustered point groups, are located to represent body part movements, for which we propose …

Direct Band Gap Gallium Antimony Phosphide (GasbXP1-X) Alloys, H. B. Russell, A. N. Andriotis, Madhu Menon, J. B. Jasinski, A. Martinez-Garcia, M. K. Sunkara

Center for Computational Sciences Faculty Publications

Here, we report direct band gap transition for Gallium Phosphide (GaP) when alloyed with just 1–2 at% antimony (Sb) utilizing both density functional theory based computations and experiments. First principles density functional theory calculations of GaSb_xP_1−x alloys in a 216 atom supercell configuration indicate that an indirect to direct band gap transition occurs at x = 0.0092 or higher Sb incorporation into GaSb_xP_1−x. Furthermore, these calculations indicate band edge straddling of the hydrogen evolution and oxygen evolution reactions for compositions ranging from x = 0.0092 Sb up to at least x = 0.065 …

Design And Analysis Of A Single-Camera Omnistereo Sensor For Quadrotor Micro Aerial Vehicles (Mavs), Carlos Jaramillo, Roberto G. Valenti, Ling Guo, Jizhong Xiao

Publications and Research

We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo sensor employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (a vertically-folded catadioptric configuration). We show that this arrangement provides a compact solution for omnidirectional 3D perception while mounted on top of propeller-based MAVs (not capable of large payloads). The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor’s projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous …

Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung

Computer Science Faculty Publications and Presentations

Medical image segmentation is typically performed manually by a physician to delineate gross tumor volumes for treatment planning and diagnosis. Manual segmentation is performed by medical experts using prior knowledge of organ shapes and locations but is prone to reader subjectivity and inconsistency. Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images. This paper presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative position of objects into a single framework to perform automated three-dimensional segmentation. The algorithm has been tested for prostate segmentation …

Histogram Of Oriented Phase And Gradient (Hopg) Descriptor For Improved Pedestrian Detection, Hussin Ragb, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

This paper presents a new pedestrian detection descriptor named Histogram of Oriented Phase and Gradient (HOPG) based on a combination of the Histogram of Oriented Phase (HOP) features and the Histogram of Oriented Gradient features (HOG).

The proposed descriptor extracts the image information using both the gradient and phase congruency concepts. Although the HOG based method has been widely used in the human detection systems, it lacks to deal effectively with the images impacted by the illumination variations and cluttered background. By fusing HOP and HOG features, more structural information can be identified and localized in order to obtain more …

Ambient And Smartphone Sensor Assisted Adl Recognition In Multi-Inhabitant Smart Environments, Nirmalya Roy, Archan Misra, Diane Cook

Research Collection School Of Computing and Information Systems

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users’ spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user …

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Computing and Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …

Girl’S Cybersecurity Camp, Sarah Cunha, Dale Rowe

Journal of Undergraduate Research

In 2015, the BYU Cybersecurity Research Lab (CSRL) held its first annual summer camp for Girls aged 14-18. A total of 38 girls attended the week’s activities and workshops. While over 75% of girls indicated they had taken a computing-related class, only 40% reported any significant interest in cybersecurity prior to the summercamp with 10% believing they had some experience in the field. At the conclusion of the camp, 80% of attendees reported a significant interest in the field with 100% of attendees interested in attending a similar event again.

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Publications

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n�1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.

Anchored Discussion: Development Of A Tool For Creativity In Online Collaboration, Georg J.P. Link, Dominik Siemon, Gert-Jan De Vreede, Susanne Robra-Bissantz

Information Systems and Quantitative Analysis Faculty Publications

Open innovation and crowdsourcing rely on online collaboration tools to enable dispersed people to collaborate on creative ideas. Research shows that creativity in online groups is significantly influenced by the interaction between group members. In this paper, we demonstrate how theory can be effectively used to design and evaluate a tool for creative online collaboration. Specifically, we use the body of knowledge on creativity support systems to inform the development of a tool to support anchored discussions. Anchored discussions represent a new mode for creative interaction. In anchored discussion every comment is tied to some aspect of an idea. We …

Grafalgo - A Library Of Graph Algorithms And Supporting Data Structures (Revised), Jonathan Turner

All Computer Science and Engineering Research

This report provides an (updated) overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/~jst/doc/grafalgo.

General Solution Of The Wind Triangle Problem And The Critical Tailwind Angle, Nihad E. Daidzic

Aviation Department Publications

A general analytical solution of the navigational wind-triangle problem and the calculation of the critical tailwind angle are presented in this study among other findings. Any crosswind component will effectively create a headwind component on fixed course tracks. The meaning of a route track is lost with excessive crosswinds representing the bifurcation point between the possible and the impossible navigational solutions. Any wind of constant direction and speed will effectively reduce groundspeed and increase time-of-flight on closed-loop multi-segment flights. Effective wind track component consists, in general, of true and induced components. The average groundspeed of multiple-leg flights is a harmonic …

Educational Methods For Inverted-Lecture Computer Science And Engineering Classrooms To Overcome Common Barriers To Stem Student Success, Kathleen Timmerman

Browse all Theses and Dissertations

New educational pedagogies are emerging in an effort to increase the number of new engineers available to enter the workforce in the coming years. One of the re-occurring themes in these pedagogies is variations of the flipped classroom. Often the additional classroom time gained from flipping is used to reinforce learning objectives. It is hypothesized that it might be more beneficial to students if a portion of that time is used to address common non-cognitive barriers that prevent students from succeeding in the major. In a freshman Introductory Computer Science course, three different pedagogies are compared: a hybrid lecture-active learning …

A Hybrid Approach To Aerial Video Image Registration, Karol T. Salva

Browse all Theses and Dissertations

Many video processing applications, such as motion detection and tracking, rely on accurate and robust alignment between consecutive video frames. Traditional approaches to video image registration, such as pyramidal Kanade-Lucas-Tomasi (KLT) feature detection and tracking are fast and subpixel accurate, but are not robust to large inter-frame displacements due to rotation, scale, or translation. This thesis presents an alternative hybrid approach using normalized gradient correlation (NGC) in the frequency domain and normalized cross-correlation (NCC) in the spatial domain that is fast, accurate, and robust to large displacements. A scale space search is incorporated into NGC to enable more consistent recovery …

Predicting Intake Of Applications For First Registration In The Property Registration Authority, Orlaith Mernagh

Dissertations

The motivation for this dissertation is rooted in a real business need. The Property Registration Authority is the state organisation tasked with maintaining a register of land ownership on the island of Ireland. The PRA currently faces a series of challenges; a high level of staff retiring and the inherent loss of knowledge associated with this trend, a lack of recruitment in recent years and a large increase in lodgement of applications for first registration as a result of legislation. The organisation therefore requires a reliable system for predicting future intake. Prior to this project, there has also been a …

Development Of Cloud-Based Uav Monitoring And Management System, Mason Itkin, Mihui Kim, Younghee Park

Faculty Publications

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, …

Super-Resolution Reconstruction Of Mri, Sara Gharabaghi, Thomas Wischgoll, Nasser H. Kashou

Computer Science and Engineering Faculty Publications

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI.

In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans.

The resolution of this …

Uncertainty-Awareness In Open Source Visualization Solutions, Christina Gillmann, Thomas Wischgoll, Hans Hagen

Computer Science and Engineering Faculty Publications

The popularity of open source tools is constantly increasing, as they offer the possibility to quickly create and use visualizations of arbitrary data sources. As the positive effects of uncertainty communication to all kinds of visualizations were discussed over the past years in the academic world, this work examines the uncertaintyawareness of open source solutions. Through a categorization and classification of available tools, this paper identifies the problems in uncertainty-awareness of available open source solutions. To solve this problem, a new paradigm of data handling that extends raw datasets by its uncertainty is suggested

Knowledge Driven Search Intent Mining, Ashutosh Jadhav

Browse all Theses and Dissertations

Understanding users' latent intents behind search queries is essential for satisfying a user's search needs. Search intent mining can help search engines to enhance its ranking of search results, enabling new search features like instant answers, personalization, search result diversification, and the recommendation of more relevant ads. Hence, there has been increasing attention on studying how to effectively mine search intents by analyzing search engine query logs. While state-of-the-art techniques can identify the domain of the queries (e.g. sports, movies, health), identifying domain-specific intent is still an open problem. Among all the topics available on the Internet, health is one …

Force Field Development With Gomc A Fast New Monte Carlo Molecular Simulation Code, Jason Richard Mick

Wayne State University Dissertations

In this work GOMC (GPU Optimized Monte Carlo) a new fast, flexible, and free molecular Monte Carlo code for the simulation atomistic chemical systems is presented. The results of a large Lennard-Jonesium simulation in the Gibbs ensemble is presented. Force fields developed using the code are also presented. To fit the models a quantitative fitting process is outlined using a scoring function and heat maps. The presented n-6 force fields include force fields for noble gases and branched alkanes. These force fields are shown to be the most accurate LJ or n-6 force fields to date for these compounds, capable …

Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model, Lindawati, Aldy Gunawan

Research Collection Lee Kong Chian School Of Business

Although Performance Based Contracting (PBC) concept is not totally new, the PBC adaptation in Industrial Machinery and Components (IMC) manufacturing, which produces high-value and long life machineries, is rather slow and it is done with extra caution. Three main concerns for manufacturers to implement PBC are the investment cost, the maintenance cost and possible revenue loss. To handle these concerns and accelerate the PBC implementation, we propose an integrated platform that consists of three components: dynamic pricing, sensor data feeding and machinery monitoring. We model the dynamic pricing as an optimization problem and propose Genetic Algorithm to solve the problem. …