Computer Engineering Commons^™

Uterine Cervical Cancer Histology Image Feature Extraction And Classification, Koyel Banerjee

Masters Theses

"The current study presents the investigation and development of image processing, computational intelligence, fuzzy logic, and statistical techniques for different types of data fusion for a varied range of applications. Raw data, decision level and feature level fusion techniques are explored for detection of pre Cervical cancer (CIN) grades from digital histology images of the cervical epithelium tissues.

In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis. The approach included medial axis determination, vertical segment partitioning as medial axis …

Robomirror: A Simulated Mirror Display With A Robotic Camera, Yuqi Zhang

Theses and Dissertations--Electrical and Computer Engineering

Simulated mirror displays have a promising prospect in applications, due to its capability for virtual visualization. In most existing mirror displays, cameras are placed on top of the displays and unable to capture the person in front of the display at the highest possible resolution. The lack of a direct frontal capture of the subject's face and the geometric error introduced by image warping techniques make realistic mirror image rendering a challenging problem. The objective of this thesis is to explore the use of a robotic camera in tracking the face of the subject in front of the display to …

Improving C2 Effectiveness Based On Robust Connectivity, S. Deller, A. Tolk, G. Rabadi, S. Bowling

Computational Modeling & Simulation Engineering Faculty Publications

This chapter describes an approach to develop an improved metric for network effectiveness through the use of Cares' (2005) Information Age Combat Model (IACM) as a context for combat (or competition) between networked forces. The IACM highlights the inadequacy of commonly used quantifiable metrics with regards to comparing networks that differ only by the placement of a few links. An agent-based simulation is used to investigate the potential value of the Perron-Frobenius Eigenvalue (λ_PFE) as an indicator of network effectiveness. The results validate this assumption. Another measurement is proven to be equally important, namely the robustness of a …

Synthetic Generators For Simulating Social Networks, Awrad Mohammed Ali

Electronic Theses and Dissertations

An application area of increasing importance is creating agent-based simulations to model human societies. One component of developing these simulations is the ability to generate realistic human social networks. Online social networking websites, such as Facebook, Google+, and Twitter, have increased in popularity in the last decade. Despite the increase in online social networking tools and the importance of studying human behavior in these networks, collecting data directly from these networks is not always feasible due to privacy concerns. Previous work in this area has primarily been limited to 1) network generators that aim to duplicate a small subset of …

Piper: Impact Of Power-Awareness On Social-Based Opportunistic Advertising, Soumaia Al Ayyat

Papers, Posters, and Presentations

Interest and social-awareness can be valuable determinants in decisions related to content delivery in mobile environments. Under certain conditions, we can deliver content with less cost and better delivery ratios, while only involving users that are interested in the type of content being delivered. However, the depletion of valuable power resources poses a deterrent to node participation in such interest-aware forwarding systems. No significant research contribution has been identified to collectively maximize the benefits of social, interest, and power awareness. In this work, we propose a new algorithm called PIPeR which integrates power awareness with an interest and socially aware …

Human-Robot Interaction For Multi-Robot Systems, Bennie Lewis

Electronic Theses and Dissertations

Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi-robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that the robots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator’s concentration is divided not only among multiple …

Spectrum Map And Its Application In Cognitive Radio Networks, Saptarshi Debroy

Electronic Theses and Dissertations

Recent measurements on radio spectrum usage have revealed the abundance of underutilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks that utilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. We argue that prior knowledge about occupancy of such bands and the corresponding achievable performance metrics can potentially …

Human Detection, Tracking And Segmentation In Surveillance Video, Guang Shu

Electronic Theses and Dissertations

This dissertation addresses the problem of human detection and tracking in surveillance videos. Even though this is a well-explored topic, many challenges remain when confronted with data from real world situations. These challenges include appearance variation, illumination changes, camera motion, cluttered scenes and occlusion. In this dissertation several novel methods for improving on the current state of human detection and tracking based on learning scene-specific information in video feeds are proposed. Firstly, we propose a novel method for human detection which employs unsupervised learning and superpixel segmentation. The performance of generic human detectors is usually degraded in unconstrained video environments …

Taming Wild Faces: Web-Scale, Open-Universe Face Identification In Still And Video Imagery, Enrique Ortiz

Electronic Theses and Dissertations

With the increasing pervasiveness of digital cameras, the Internet, and social networking, there is a growing need to catalog and analyze large collections of photos and videos. In this dissertation, we explore unconstrained still-image and video-based face recognition in real-world scenarios, e.g. social photo sharing and movie trailers, where people of interest are recognized and all others are ignored. In such a scenario, we must obtain high precision in recognizing the known identities, while accurately rejecting those of no interest. Recent advancements in face recognition research has seen Sparse Representation-based Classification (SRC) advance to the forefront of competing methods. However, …

Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki

Department of Electrical Engineering and Computer Science - Daytona Beach

This paper presents an approach to measuring computer security understood as a system property, in the category of similar properties, such as safety, reliability, dependability, resilience, etc. First, a historical discussion of measurements is presented, beginning with views of Hermann von Helmholtz in his 19th century work “Zählen und Messen”. Then, contemporary approaches related to the principles of measuring software properties are discussed, with emphasis on statistical, physical and software models. A distinction between metrics and measures is made to clarify the concepts. A brief overview of inadequacies of methods and techniques to evaluate computer security is presented, followed by …

Keeping The Skies Safe, Massood Towhidnejad, Andrew J. Kornecki

Department of Electrical Engineering and Computer Science - Daytona Beach

Professors Massood Towhidnejad and Andrew Kornecki shine a light on how their lab is helping government and the aviation industry to enhance the safety and security of software-intensive systems.

A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic

Computer Science Faculty Publications and Presentations

Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to traditional computation models, the reservoir is a dynamical system in which computation and memory are inseparable, and therefore hard to analyze. Here, we compare …

Toward A Framework For Levels Of Robot Autonomy In Human-Robot Interaction, Jenay Beer, A. D. Fisk, W. A. Rogers

Faculty Publications

Autonomy is a critical construct related to human-robot interaction (HRI) and varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots interact with one another. Thus, there is a need to understand HRI by identifying variables that influence—and are influenced by—robot autonomy. Our overarching goal is to develop a framework for LORA in HRI. To reach this goal, our framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed …

M-Fdbscan: A Multicore Density-Based Uncertain Data Clustering Algorithm, Atakan Erdem, Taflan İmre Gündem

Turkish Journal of Electrical Engineering and Computer Sciences

In many data mining applications, we use a clustering algorithm on a large amount of uncertain data. In this paper, we adapt an uncertain data clustering algorithm called fast density-based spatial clustering of applications with noise (FDBSCAN) to multicore systems in order to have fast processing. The new algorithm, which we call multicore FDBSCAN (M-FDBSCAN), splits the data domain into c rectangular regions, where c is the number of cores in the system. The FDBSCAN algorithm is then applied to each rectangular region simultaneously. After the clustering operation is completed, semiclusters that occur during splitting are detected and merged to …

Effects Of A Current Transformer's Magnetizing Current On The Driving Voltage In Self-Oscillating Converters, Güngör Bal, Seli̇m Öncü

Turkish Journal of Electrical Engineering and Computer Sciences

Magnetizing inductance is one of the parameters that affect the phase and amplitude error of the output current of current transformers (CTs). In this study, the linear circuit model of a CT is developed to be used for driving purposes in power electronics applications. A simulation of the CT and its linear model is achieved. In the model circuit, the effect of the magnetizing inductance on the driving voltage can be examined. The equivalent circuit simulation results and the linear model simulation results along with the calculated results show agreement with each other. These results are compared with experimental results.

Design And Implementation Of An Observer Controller For A Buck Converter, Shenbaga Lakshmi, Sree Renga Raja

Turkish Journal of Electrical Engineering and Computer Sciences

An observer controller for a buck converter is presented. A state feedback gain matrix is derived in order to achieve the stability of the converter and to ensure the robustness of the controller. A load estimator is designed to estimate the unmeasurable variables and to obtain the zero output voltage error. A pulse-width modulation scheme is adopted to obtain the output voltage regulation. In order to improve the transitory response and dynamic constancy of the converter, the controller parameters are designed based on the current mode control. The design is evaluated and verified using MATLAB/Simulink. An experimental set-up is done …

Impact Of Small-World Topology On The Performance Of A Feed-Forward Artificial Neural Network Based On 2 Different Real-Life Problems, Okan Erkaymaz, Mahmut Özer, Nejat Yumuşak

Turkish Journal of Electrical Engineering and Computer Sciences

Since feed-forward artificial neural networks (FFANNs) are the most widely used models to solve real-life problems, many studies have focused on improving their learning performances by changing the network architecture and learning algorithms. On the other hand, recently, small-world network topology has been shown to meet the characteristics of real-life problems. Therefore, in this study, instead of focusing on the performance of the conventional FFANNs, we investigated how real-life problems can be solved by a FFANN with small-world topology. Therefore, we considered 2 real-life problems: estimating the thermal performance of solar air collectors and predicting the modulus of rupture values …

A Hypernet Architecture, Shufeng Huang

Theses and Dissertations--Computer Science

Network virtualization is becoming a fundamental building block of future Internet architectures. By adding networking resources into the “cloud”, it is possible for users to rent virtual routers from the underlying network infrastructure, connect them with virtual channels to form a virtual network, and tailor the virtual network (e.g., load application-specific networking protocols, libraries and software stacks on to the virtual routers) to carry out a specific task. In addition, network virtualization technology allows such special-purpose virtual networks to co-exist on the same set of network infrastructure without interfering with each other.

Although the underlying network resources needed to support …

Finding Evidence Of Wordlists Being Deployed Against Ssh Honeypots – Implications And Impacts, Priya Rabadia, Craig Valli

Australian Digital Forensics Conference

This paper is an investigation focusing on activities detected by three SSH honeypots that utilise Kippo honeypot software. The honeypots were located on the same /24 IPv4 network and configured as identically as possible. The honeypots used the same base software and hardware configurations. The data from the honeypots were collected during the period 17th July 2012 and 26th November 2013, a total of 497 active day periods. The analysis in this paper focuses on the techniques used to attempt to gain access to these systems by attacking entities. Although all three honeypots are have the same configuration settings and …

Developing A Conceptual Framework For Modeling Deviant Cyber Flash Mob: A Socio-Computational Approach Leveraging Hypergraph Constructs, Samer Al-Khateeb, Nitin Agarwal

Journal of Digital Forensics, Security and Law

In a Flash Mob (FM) a group of people get together in the physical world perform an unpredicted act and disperse quickly. Cyber Flash Mob (CFM) is the cyber manifestation of flash mob coordinated primarily using social media. Deviant Cyber Flash Mob (or, DCFM) is a special case of CFM, which is categorized as the new face of transnational crime organizations (TCOs). The DCFM phenomenon can be considered as a form of a cyber-collective action that is defined as an action aiming to improve group’s conditions (such as, status or power). In this paper, we conduct a conceptual analysis of …