Engineering Commons^™

Micro-Policies: Formally Verified, Tag-Based Security Monitors, Arthur Azevedo De Amorim, Maxime Denes, Nick Giannarakis, Cătălin Hriţcu, Benjamin C. Pierce, Antal Spector-Zabusky, Andrew Tolmach

Computer Science Faculty Publications and Presentations

Recent advances in hardware design have demonstrated mechanisms allowing a wide range of low-level security policies (or micro-policies) to be expressed using rules on metadata tags. We propose a methodology for defining and reasoning about such tag-based reference monitors in terms of a high-level “symbolic machine,” and we use this methodology to define and formally verify micro-policies for dynamic sealing, compartmentalization, control-flow integrity, and memory safety; in addition, we show how to use the tagging mechanism to protect its own integrity. For each micro-policy, we prove by refinement that the symbolic machine instantiated with the policy’s rules embodies a high-level …

Robust And Real-Time Stereo Matching On Parallel Graphics Hardware Using Gradient-Based Disparity Refinement, Jedrzej Kowalczuk

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Computer vision attempts to provide camera-equipped machines with visual perception, i.e., the capability to comprehend their surroundings through the analysis and understanding of images. The ability to perceive depth is a vital component of visual perception that enables machines to interpret the three-dimensional structure of their surroundings and allows them to navigate through the environment. In computer vision, depth perception is achieved via stereo matching, a process that identifies correspondences between pixels in images acquired using a pair of horizontally offset cameras. It is possible to calculate depths from correspondences or, more specifically, the positional offsets (disparities) between pixels in …

Simple Secrecy: Analog Stream Cipher For Secure Voice Communication, John M. Campbell

Senior Honors Theses

Voice signals are inherently analog, and some voice communication systems still utilize analog signals. Existing analog cryptographic methods do not satisfactorily provide cryptosecurity for communication systems due to several limitations. This paper proposes a novel means of provided cryptosecurity for analog signals without digitization; thereby avoiding the latency which results from ADC/DAC conversions. This method utilizes the principles of the digital stream cipher, generating instead a continuous pseudorandom analog key stream signal which is transformed with the original analog signal to create an encrypted ciphertext signal which is statistically independent of the original signal and the key stream signal. The …

Teaching Cybersecurity Using The Cloud, Khaled Salah, Mohammad Hammoud, Sherali Zeadally

Information Science Faculty Publications

Cloud computing platforms can be highly attractive to conduct course assignments and empower students with valuable and indispensable hands-on experience. In particular, the cloud can offer teaching staff and students (whether local or remote) on-demand, elastic, dedicated, isolated, (virtually) unlimited, and easily configurable virtual machines. As such, employing cloud-based laboratories can have clear advantages over using classical ones, which impose major hindrances against fulfilling pedagogical objectives and do not scale well when the number of students and distant university campuses grows up. We show how the cloud paradigm can be leveraged to teach a cybersecurity course. Specifically, we share our …

How The University Of California Runs One Repository For Ten Campuses, Katie Fortney

Inaugural CSU IR Conference, 2015

Katie Fortney, JD, MLIS, Copyright Policy & Education Officer, Office of Scholarly Communication, University of California http://osc.universityofcalifornia.edu/

Implementing Metaarchive And Lockss At Digital Commons @Cal Poly, Michele Wyngard

Inaugural CSU IR Conference, 2015

Michele Wyngard, Digital Repository Coordinator, CSU Cal Poly

Using Google Tag Manager And Google Analytics, (Code{4}Lib Journal), Suzanna Conrad

Inaugural CSU IR Conference, 2015

Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona

What’S New Since The April 2013 Stim Ir Subcommittee Report To Cold: Hydra, Islandora And Dspace, Aaron Collier, Suzanna Conrad, Carmen Mitchell, Joan Parker, Andrew Weiss, Jeremy C. Shellhase

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office
Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona
Carmen Mitchell, Institutional Repository Librarian, CSU San Marcos
Joan Parker, Librarian, Moss Landing Marine Laboratories
Andrew Weiss, Digital Services Librarian, CSU Northridge

Jeremy Shellhase, Head of Information Services & Systems Department, Humboldt State University

The State Of Scholarworks, Aaron Collier

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office

Where Do We Develop? Discovering Regions For Urban Investment In Senegal, Derek Doran, Andrew Fox, Veena Mendiratta

Computer Science and Engineering Faculty Publications

The rate of urbanization in developing countries, defined as the speed with which a population shifts from rural to urban areas, is among the highest in the world. The disproportionate number of citizens that live in a small numbers of cities places incredible pressure on the largest cities in these countries, which may already be faced with limited resources, weak industrialization, and underdeveloped infrastructures. Urban planning researchers as well as policy makers have suggested that governments in developing countries make capital investments within and surrounding smaller cities to attract citizens away from large urban centers, thereby lowering the pressure placed …

Gaussian Weighted Neighborhood Connectivity Of Nonlinear Line Attractor For Learning Complex Manifolds, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Electrical and Computer Engineering Faculty Publications

The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA …

Symbolic Aggregate Approximation (Sax) Under Interval Uncertainty, Chrysostomos D. Stylios, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we monitor a system by continuously measuring the corresponding quantities, to make sure that an abnormal deviation is detected as early as possible. Often, we do not have ready algorithms to detect abnormality, so we need to use machine learning techniques. For these techniques to be efficient, we first need to compress the data. One of the most successful methods of data compression is the technique of Symbolic Aggregate approXimation (SAX). While this technique is motivated by measurement uncertainty, it does not explicitly take this uncertainty into account. In this paper, we show that we can …

Architectural Techniques To Extend Multi-Core Performance Scaling, Hamza Bin Sohail

Open Access Dissertations

Multi-cores have successfully delivered performance improvements over the past decade; however, they now face problems on two fronts: power and off-chip memory bandwidth. Dennard's scaling is effectively coming to an end which has lead to a gradual increase in chip power dissipation. In addition, sustaining off-chip memory bandwidth has become harder due to the limited space for pins on the die and greater current needed to drive the increasing load . My thesis focuses on techniques to address the power and off-chip memory bandwidth challenges in order to avoid the premature end of the multi-core era. ^ In the first …

An Extensible Technology Framework For Cyber Security Education, Frank Jordan Sheen

Theses and Dissertations

Cyber security education has evolved over the last decade to include new methods of teaching and technology to prepare students. Instructors in this field of study often deal with a subject matter that has rigid principles, but changing ways of applying those principles. This makes maintaining courses difficult. This case study explored the kind of teaching methods, technology, and means used to explain these concepts. This study shows that generally, cyber security courses require more time to keep up to date. It also evaluates one effort, the NxSecLab, on how it attempted to relieve the administrative issues in teaching these …

Intensity And Resolution Enhancement Of Local Regions For Object Detection And Tracking In Wide Area Surveillance, Evan Krieger, Vijayan K. Asari, Saibabu Arigela, Theus H. Aspiras

Electrical and Computer Engineering Faculty Publications

Object tracking in wide area motion imagery is a complex problem that consists of object detection and target tracking over time. This challenge can be solved by human analysts who naturally have the ability to keep track of an object in a scene. A computer vision solution for object tracking has the potential to be a much faster and efficient solution. However, a computer vision solution faces certain challenges that do not affect a human analyst. To overcome these challenges, a tracking process is proposed that is inspired by the known advantages of a human analyst.

First, the focus of …

Visual Analytics For Large Communication Trace Data, Jieting Wu

School of Computing: Dissertations, Theses, and Student Research

Executions of modern parallel programs often yield complex communications among compute nodes of large-scale clusters of workstations or supercomputers. Analyzing communication patterns is becoming increasingly critical to performance optimiza- tion. As the scale and complexity of parallel applications drastically increases, visu- alization has become a feasible means to conduct analysis of massive communication patterns. However, most visualization tools fall short in showing comprehensive dy- namic communication graph and addressing the scalability issue. Our solution for analyzing dynamic communication patterns is based on an analytics framework cou- pled with a new visualization technique, named CommGram [29], that provides a flexible solution …

Trajectory Generation For Lane-Change Maneuver Of Autonomous Vehicles, Ashesh Goswami

Open Access Theses

Lane-change maneuver is one of the most thoroughly investigated automatic driving operations that can be used by an autonomous self-driving vehicle as a primitive for performing more complex operations like merging, entering/exiting highways or overtaking another vehicle. This thesis focuses on two coherent problems that are associated with the trajectory generation for lane-change maneuvers of autonomous vehicles in a highway scenario: (i) an effective velocity estimation of neighboring vehicles under different road scenarios involving linear and curvilinear motion of the vehicles, and (ii) trajectory generation based on the estimated velocities of neighboring vehicles for safe operation of self-driving cars during …

Improving Product Design Phase For Engineer To Order (Eto) Product With Knowledge Base Engineering (Kbe), Hanhdung Thi Dinh

Open Access Theses

In industry currently Computer Aided Design (CAD) is an important tool for the modification, analysis, or optimization of the 3D virtual environment that replicates the physical product. CAD software is an efficient and reliable tool. However, as globalization increases customer demands, this process needs to be faster and more efficient to accommodate changing product design situations, especially for Engineer-to- Order (ETO) products. ^ The traditional method of product design process is to operate CAD software without argumentation. Design engineers create CAD prototypes and drawings based on available knowledge and information which comes from engineering experts, company standards, industrial practices as …

Recursive Tree Traversal Dependence Analysis, Yusheng Weijiang

Open Access Theses

While there has been much work done on analyzing and transforming regular programs that operate over linear arrays and dense matrices, comparatively little has been done to try to carry these optimizations over to programs that operate over heap-based data structures using pointers. Previous work has shown that point blocking, a technique similar to loop tiling in regular programs, can help increase the temporal locality of repeated tree traversals. Point blocking, however, has only been shown to work on tree traversals where each traversal is fully independent and would allow parallelization, greatly limiting the types of applications that this transformation …

Improving Capacity-Performance Tradeoffs In The Storage Tier, Eric P. Villasenor

Open Access Dissertations

Data-set sizes are growing. New techniques are emerging to organize and analyze these data-sets. There is a key access pattern emerging with these new techniques, large sequential file accesses. The trend toward bigger files exists to help amortize the cost of data accesses from the storage layer, as many workloads are recognized to be I/O bound. The storage layer is widely recognized as the slowest layer in the system. This work focuses on the tradeoff one can make with that storage capacity to improve system performance. ^ Capacity can be leveraged for improved availability or improved performance. This tradeoff is …

Assessment Of High-Fidelity Collision Models In The Direct Simulation Monte Carlo Method, Andrew Brian Weaver

Open Access Dissertations

Advances in computer technology over the decades has allowed for more complex physics to be modeled in the DSMC method. Beginning with the first paper on DSMC in 1963, 30,000 collision events per hour were simulated using a simple hard sphere model. Today, more than 10 billion collision events can be simulated per hour for the same problem. Many new and more physically realistic collision models such as the Lennard-Jones potential and the forced harmonic oscillator model have been introduced into DSMC. However, the fact that computer resources are more readily available and higher-fidelity models have been developed does not …

Developing A Fuzzy Expert System To Examine Hazard Analysis In The United States Army, Charles J. Karels

Theses and Dissertations

The research conducted in this thesis is an attempt to determine if there are any biographical similarities between second lieutenants in the US Army who view risk in a similar manner and if so, which are the most significant. A study was conducted using in-group surveys of 72 second lieutenants receiving training in Infantry Basic Officer Leader Course (IBOLC). The participants were provided with two written surveys each presenting a scenario based on military activities. They were asked to evaluate the scenarios and fill out Risk Management (RM) worksheets based on the US Army's doctrinal process for conducing RM. The …

Efficient Thermal Image Segmentation Through Integration Of Nonlinear Enhancement With Unsupervised Active Contour Model, Fatema Albalooshi, Evan Krieger, Paheding Sidike, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Thermal images are exploited in many areas of pattern recognition applications. Infrared thermal image segmentation can be used for object detection by extracting regions of abnormal temperatures. However, the lack of texture and color information, low signal-to-noise ratio, and blurring effect of thermal images make segmenting infrared heat patterns a challenging task. Furthermore, many segmentation methods that are used in visible imagery may not be suitable for segmenting thermal imagery mainly due to their dissimilar intensity distributions.

Thus, a new method is proposed to improve the performance of image segmentation in thermal imagery. The proposed scheme efficiently utilizes nonlinear intensity …

Toward A Theory Of Multi-Method Modeling And Simulation Approach, Mariusz A. Balaban

Computational Modeling & Simulation Engineering Theses & Dissertations

The representation via simulation models can easily lead to simulation models too simple for their intended purpose, or with too much detail, making them hard to understand. This problem is related to limitations of the modeling and simulation methods. A multi-method Modeling and Simulation (M&S) approach has the potential for improved representation by taking advantage of methods' strengths and mitigating their weaknesses. Despite a high appeal for using multiple M&S methods, several related problems should be addressed first. The current level of theoretical, methodological, and pragmatic knowledge related to a multi-method M&S approach is limited. It is problematic that there …

Proclivity Or Popularity? Exploring Agent Heterogeneity In Network Formation, Xiaotian Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

The Barabasi-Albert model (BA model) is the standard algorithm used to describe the emergent mechanism of a scale-free network. This dissertation argues that the BA model, and its variants, rarely take agent heterogeneity into account in the analysis of network formation. In social networks, however, people's decisions to connect are strongly affected by the extent of similarity. In this dissertation, the author applies an agent-based modeling (ABM) approach to reassess the Barabasi-Albert model. This study proposes that, in forming social networks, agents are constantly balancing between instrumental and intrinsic preferences. After systematic simulation and subsequent analysis, this study finds that …

Java Animated Software For Teaching The Frank-Wolfe Algorithm For Static Traffic Network Equilibrium, Zhi Li

Computational Modeling & Simulation Engineering Theses & Dissertations

The popular Frank-Wolfe (FW) algorithm for solving the network equilibrium problems plays an important role in transportation simulation. Not only has the basic Frank Wolfe algorithm been studied, but also other variations of the FW algorithm (such as Conjugate Frank Wolfe and Bi-Conjugate Frank Wolfe algorithms) have been extensively studied by the research communities.

In this work, the basic Frank Wolfe algorithm is re-visited for the purpose of developing a useful, user-friendly, and appealing Java computer animation for enhancing the teaching effectiveness of this fundamental transportation static network equilibrium algorithm. Since the shortest path (SP) algorithms (such as the well-known …

Distributed Augmented Reality Communications And Interactions, Mitchell Mason

Honors Capstones

No abstract provided.

An Mas Based Energy Management System For A Stand-Alone Microgrid At High Altitude, Junhui Zhao, Bo Zhao, Meidong Xue, Xuesong Zhang, Caisheng Wang

Electrical & Computer Engineering and Computer Science Faculty Publications

A multi-agent system based energy management system (EMS) is proposed in this paper for implementing a PV-small hydro hybrid microgrid (MG) at high altitude. Based on local information, the distributed generation (DG) sources in the MG are controlled via the EMS to achieve efficient and stable system operation. Virtual bidding is used to quickly establish the scheduling of system operation and capacity reserve. In addition, real-time power dispatches are carried out through model predictive control to balance load demand and power generation in the MG. The dynamic model and the energy management strategy of the MG have been simulated on …

Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth

Research Collection School Of Computing and Information Systems

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results …

Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …