Computer Sciences Commons^™

Automatic Detection And Denoising Of Signals In Large Geophysical Datasets, Gabriel O. Trisca

Boise State University Theses and Dissertations

To fully understand the complex interactions of various phenomena in the natural world, scientific disciplines such as geology and seismology increasingly rely upon analyzing large amounts of observations. However, data collection is growing at a faster rate than what is currently possible to analyze through traditional approaches. These datasets, supplied by the increasing use of sensors and remote sensing, require specialized computer programs to effectively analyze complex and expansive volumes of data.

Elaborating on existing geophysical data processing approaches for infrasound data collected from an avalanche-prone area, this project proposes new techniques for processing large geophysical datasets. These improved techniques …

Compiling Collapsing Rules In Certain Constructor Systems, Sergio Antoy, Andy Jost

Computer Science Faculty Publications and Presentations

The implementation of functional logic languages by means of graph rewriting requires a special handling of collapsing rules. Recent advances about the notion of a needed step in some constructor systems offer a new approach to this problem. We present two results: a transformation of a certain class of constructor-based rewrite systems that eliminates collapsing rules, and a rewrite-like relation that takes advantage of the absence of collapsing rules. We formally state and prove the correctness of these results. When used together, these results simplify without any loss of efficiency an implementation of graph rewriting and consequently of functional logic …

Intrusion Detection System Of Industrial Control Networks Using Network Telemetry, Stanislav Ponomarev

Doctoral Dissertations

Industrial Control Systems (ICSs) are designed, implemented, and deployed in most major spheres of production, business, and entertainment. ICSs are commonly split into two subsystems - Programmable Logic Controllers (PLCs) and Supervisory Control And Data Acquisition (SCADA) systems - to achieve high safety, allow engineers to observe states of an ICS, and perform various configuration updates. Before wide adoption of the Internet, ICSs used "air-gap" security measures, where the ICS network was isolated from other networks, including the Internet, by a physical disconnect [1]. This level of security allowed ICS protocol designers to concentrate on the availability and safety of …

State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Extreme Learning Machine (ELM) has been introduced as a new algorithm for training single hidden layer feed-forward neural networks (SLFNs) instead of the classical gradient-based algorithms. Based on the consistency property of data, which enforce similar samples to share similar properties, ELM is a biologically inspired learning algorithm with SLFNs that learns much faster with good generalization and performs well in classification applications. However, the random generation of the weight matrix in current ELM based techniques leads to the possibility of unstable outputs in the learning and testing phases. Therefore, we present a novel approach for computing the weight matrix …

Object Tracking From Multiple Multi-Axis Platforms In Four Dimensions, Theodore A. Teates

Electrical & Computer Engineering Theses & Dissertations

Object handoff in free space requires a sound framework between at least two optical sensors and one object. Previous work developed an algorithm that can determine the ap­ propriate time to initiate handoff of object tracking responsibilities from one optical sensor with an object in view to another optical sensor with the same object in view. In order to maintain persistent tracking of objects in this work, gimbal movements of optical sensors are determined by calculations using the Lagrange method to determine the trackability measures between the moving object and the handoff cone for the appropriate optical sensor. The rotation …

Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

The different advantageous embodiments provide a system comprising a number of computers, a graphical user interface, first program code stored on the computer, and second program code stored on the computer. The graphical user interface is executed by a computer in the number of computers. The computer is configured to run the first program code to define a mission using a number of mission elements. The computer is configured to run the second program code to generate instructions for a number of assets to execute the mission and monitor the number of assets during execution of the mission.

Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In August 2014 a conference on “Model reduction across disciplines” was held in Leicester, UK. As a scientific field, model reduction is an important part of mathematical modelling and data analysis with very wide areas of applications. The main scientific goal of the conference was to facilitate interdisciplinary discussion of model reduction and coarse-graining methodologies in order to reveal their general mathematical nature. This time, however, the conference had an additional personal and more profound mission – it was dedicated to the 60th birthday of Professor Alexander Gorban (albeit with some delay) whose fantastic achievements in applying model reduction techniques …

Cooperative 3-D Map Generation Using Multiple Uavs, Andrew Erik Lawson

University Scholar Projects

This report aims to demonstrate the feasibility of building a global 3-D map from multiple UAV robots in a GPS-denied, indoor environment. Presented are the design of each robot and the reasoning behind choosing its hardware and software components, the process in which a single robot obtains a individual 3-D map entirely onboard, and lastly how the mapping concept is extended to multiple robotic agents to form a global 3-D map using a centralized server. In the latter section, this report focuses on two algorithms, Online Mapping and Map Fusion, developed to facilitate the cooperative approach. A limited selection …

A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames.

We anticipate that such key frame selection technique will have significant impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery. Three real-world datasets are used for evaluation and testing and the observed results are encouraging.

Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm.

Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements.

Future …

Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.

Pinpoint: Efficient And Effective Resource Isolation For Mobile Security And Privacy, Paul Ratazzi, Ashok Bommisetti, Nian Ji, Wenliang Du

Electrical Engineering and Computer Science - All Scholarship

Virtualization is frequently used to isolate untrusted processes and control their access to sensitive resources. However, isolation usually carries a price in terms of less resource sharing and reduced inter-process communication. In an open architecture such as Android, this price and its impact on performance, usability, and transparency must be carefully considered. Although previous efforts in developing general-purpose isolation solutions have shown that some of these negative sideeffects can be mitigated, doing so involves overcoming significant design challenges by incorporating numerous additional platform complexities not directly related to improved security. Thus, the general purpose solutions become inefficient and burdensome if …

College Of Engineering Senior Design Competition Spring 2015, University Of Nevada, Las Vegas

Fred and Harriet Cox Senior Design Competition Projects

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the projects on …

Design And Verification Environment For High-Performance Video-Based Embedded Systems, Michael Mefenza Nentedem

Graduate Theses and Dissertations

In this dissertation, a method and a tool to enable design and verification of computation demanding embedded vision-based systems is presented. Starting with an executable specification in OpenCV, we provide subsequent refinements and verification down to a system-on-chip prototype into an FPGA-Based smart camera. At each level of abstraction, properties of image processing applications are used along with structure composition to provide a generic architecture that can be automatically verified and mapped to the lower abstraction level. The result is a framework that encapsulates the computer vision library OpenCV at the highest level, integrates Accelera's System-C/TLM with UVM and QEMU-OS …

Enabling Runtime Self-Coordination Of Reconfigurable Embedded Smart Cameras In Distributed Networks, Franck Ulrich Yonga Yonga

Graduate Theses and Dissertations

Smart camera networks are real-time distributed embedded systems able to perform computer vision using multiple cameras. This new approach is a confluence of four major disciplines (computer vision, image sensors, embedded computing and sensor networks) and has been subject of intensive work in the past decades. The recent advances in computer vision and network communication, and the rapid growing in the field of high-performance computing, especially using reconfigurable devices, have enabled the design of more robust smart camera systems. Despite these advancements, the effectiveness of current networked vision systems (compared to their operating costs) is still disappointing; the main reason …

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 …

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 …

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 …

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 …

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 …

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 …

Video-To-Video Pose And Expression Invariant Face Recognition Using Volumetric Directional Pattern, Vijayan K. Asari, Almabrok Essa

Electrical and Computer Engineering Faculty Publications

Face recognition in video has attracted attention as a cryptic method of human identification in surveillance systems. In this paper, we propose an end-to-end video face recognition system, addressing a difficult problem of identifying human faces in video due to the presence of large variations in facial pose and expression, and poor video resolution. The proposed descriptor, named Volumetric Directional Pattern (VDP), is an oriented and multi-scale volumetric descriptor that is able to extract and fuse the information of multi frames, temporal (dynamic) information, and multiple poses and expressions of faces in input video to produce feature vectors, which are …

A Study Of Decision Process In Mcdm Problems With Large Number Of Criteria, Jian Liu, Peng Liu, Si Feng Liu, Xian Zhong Zhou, Tao Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an effective decision process method is proposed to address the challenge in a multiple criteria decision-making (MCDM) problem because of large number of criteria. This method is based on the criteria reduction, tolerance relation, and prospect theory (PT). By building a discernibility matrix for tolerance relation (DMTR) in an MCDM problem with numerical values or interval numbers, this method first allows us to recognize a set of critical criteria from a large criteria pool and ignore the other criteria. Next, it establishes the criteria weights through the DMTR as they are usually not indicated in the data. …

Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso

Electrical and Computer Engineering Faculty Research & Creative Works

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …

Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses.

The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations.

The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …

Clustering Header Categories Extracted From Web Tables, George Nagy, David W. Embley, Mukkai Krishnamoorthy, Sharad C. Seth

School of Computing: Conference and Workshop Papers

Revealing related content among heterogeneous web tables is part of our long term objective of formulating queries over multiple sources of information. Two hundred HTML tables from institutional web sites are segmented and each table cell is classified according to the fundamental indexing property of row and column headers. The categories that correspond to the multi-dimensional data cube view of a table are extracted by factoring the (often multi-row/column) headers. To reveal commonalities between tables from diverse sources, the Jaccard distances between pairs of category headers (and also table titles) are computed. We show how about one third of our …

Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

A new definition of semi-modularity to accommodate relative timing constraints in self-timed circuits is presented. While previous definitions ignore such constraints, the new definition takes them into account. The difference on a design solution for a well-known speed-independent circuit implementation of the Muller C element and a set of relative timing constraints that renders the implementation hazard free is illustrated. The old definition produces a false semi-modularity conflict that cannot exist due to the set of imposed constraints. The new definition correctly accepts the solution.

Con-Resistant Trust For Improved Reliability In A Smart Grid Special Protection System, Crystal M. Shipman, Kenneth M. Hopkinson, Juan L. Lopez Jr.

Faculty Publications

This paper applies a con-resistant trust mechanism to improve the performance of a communications-based special protection system to enhance its effectiveness and resiliency. Smart grids incorporate modern information technologies to increase reliability and efficiency through better situational awareness. However, with the benefits of this new technology come the added risks associated with threats and vulnerabilities to the technology and to the critical infrastructure it supports. The research in this paper uses con-resistant trust to quickly identify malicious or malfunctioning (untrustworthy) protection system nodes to mitigate instabilities. The con-resistant trust mechanism allows protection system nodes to make trust assessments based on …