Computer Engineering Commons^™

Revealing Malicious Contents Hidden In The Internet, Muhammad Nazmus Sakib

Theses and Dissertations

In this age of ubiquitous communication in which we can stay constantly connected with the rest of the world, for most of the part, we have to be grateful for one particular invention - the Internet. But as the popularity of Internet connectivity grows, it has become a very dangerous place where objects of malicious content and intent can be hidden in plain sight. In this dissertation, we investigate different ways to detect and capture these malicious contents hidden in the Internet. First, we propose an automated system that mimics high-risk browsing activities such as clicking on suspicious online ads, …

Optical Fiber Sensors In Physical Intrusion Detection Systems: A Review, Gary Andrew Allwood, Graham Wild, Steven Hinkley

Research outputs 2014 to 2021

Fiber optic sensors have become a mainstream sensing technology within a large array of applications due to their inherent benefits. They are now used significantly in structural health monitoring, and are an essential solution for monitoring harsh environments. Since their first development over 30 years ago, they have also found promise in security applications. This paper reviews all of the optical fiber-based techniques used in physical intrusion detection systems. It details the different approaches used for sensing, interrogation, and networking, by research groups, attempting to secure both commercial and residential premises from physical security breaches. The advantages and the disadvantages …

Interfacing Of Neuromorphic Vision, Auditory And Olfactory Sensors With Digital Neuromorphic Circuits, Anup Vanarse

Theses: Doctorates and Masters

The conventional Von Neumann architecture imposes strict constraints on the development of intelligent adaptive systems. The requirements of substantial computing power to process and analyse complex data make such an approach impractical to be used in implementing smart systems.

Neuromorphic engineering has produced promising results in applications such as electronic sensing, networking architectures and complex data processing. This interdisciplinary field takes inspiration from neurobiological architecture and emulates these characteristics using analogue Very Large Scale Integration (VLSI). The unconventional approach of exploiting the non-linear current characteristics of transistors has aided in the development of low-power adaptive systems that can be implemented …

An Investigation Into Off-Link Ipv6 Host Enumeration Search Methods, Clinton Carpene

Theses: Doctorates and Masters

This research investigated search methods for enumerating networked devices on off-link 64 bit Internet Protocol version 6 (IPv6) subnetworks. IPv6 host enumeration is an emerging research area involving strategies to enable detection of networked devices on IPv6 networks. Host enumeration is an integral component in vulnerability assessments (VAs), and can be used to strengthen the security profile of a system. Recently, host enumeration has been applied to Internet-wide VAs in an effort to detect devices that are vulnerable to specific threats. These host enumeration exercises rely on the fact that the existing Internet Protocol version 4 (IPv4) can be exhaustively …

An Evaluation Of Robotics In Nursing Homes To Reduce Adverse Drug Events, Ozell Ueal Jr.

Walden Dissertations and Doctoral Studies

Adverse drug events (ADE) cause many deaths annually in addition to affecting the quality of life of many others. The descriptive mixed methods approach, specifically exploratory case study and experimental design that guided this research utilized the survey and focus group methods to evaluate perceptions about robotic technology (RT) to reduce the rate of ADEs in U.S. nursing homes (NH). There is a lack of scholarly research into whether a conceptual approach rooted in RT can be implemented to assist with drug administrations in NHs. The purpose of this study was twofold. The first purpose was to evaluate the causes …

Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus

Dissertations, Master's Theses and Master's Reports

The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …

De-Anonymization Attack Anatomy And Analysis Of Ohio Nursing Workforce Data Anonymization, Jacob M. Miracle

Browse all Theses and Dissertations

Data generalization (anonymization) is a widely misunderstood technique for preserving individual privacy in non-interactive data publishing. Easily avoidable anonymization failures are still occurring 14 years after the discovery of basic techniques to protect against them. Identities of individuals in anonymized datasets are at risk of being disclosed by cyber attackers who exploit these failures. To demonstrate the importance of proper data anonymization we present three perspectives on data anonymization. First, we examine several de-anonymization attacks to formalize the anatomy used to conduct attacks on anonymous data. Second, we examine the vulnerabilities of an anonymous nursing workforce survey to convey how …

Identifying Offensive Videos On Youtube, Rajeshwari Kandakatla

Browse all Theses and Dissertations

Harassment on social media has become a critical problem and social media content depicting harassment is becoming common place. Video-sharing websites such as YouTube contain content that may be offensive to certain community, insulting to certain religion, race etc., or make fun of disabilities. These videos can also provoke and promote altercations leading to online harassment of individuals and groups. In this thesis, we present a system that identifies offensive videos on YouTube. Our goal is to determine features that can be used to detect offensive videos efficiently and reliably. We conducted experiments using content and metadata available for each …

Computer Graphics And Visualization Based Analysis And Record System For Hand Surgery And Therapy Practice, Venkatamanikanta Subrahmanyakartheek Gokavarapu

Browse all Theses and Dissertations

In this thesis, we have designed and developed a computer graphics and visualization based analysis and record system for hand surgery and therapy practice. In particular, we have designed and developed three novel technologies: (i) model-based data compression for hand motion records (ii) model-based surface area estimation of a human hand and (iii) an emulated study of hand wound area estimation. First, we have presented a new data compression technique to better address the needs of electronic health record systems, such as file storage and privacy. In our proposed approach, we will extract the patient's hand motion information and store …

A Stochastic Petri Net Based Nlu Scheme For Technical Documents Understanding, Adamantia Psarologou

Browse all Theses and Dissertations

Natural Language Understanding (NLU) is a very old research field, which deals with machine reading comprehension. Despite the many years of work and the numerous accomplishments by several researchers in the field, there is still place for significant improvements. Here, our goal is to develop a novel NLU methodology for detecting and extracting event/action associations in technical documents. In order to achieve this goal we present a synergy of methods (Kernel extraction, Formal Language Modeling, Stochastic Petri-nets (SPN) mapping and Event Representation via SPN graph synthesis). In particular, the basic meaning of a natural language sentence is given by its …

Mining And Analyzing Subjective Experiences In User Generated Content, Lu Chen

Browse all Theses and Dissertations

Web 2.0 and social media enable people to create, share and discover information instantly anywhere, anytime. A great amount of this information is subjective information -- the information about people's subjective experiences, ranging from feelings of what is happening in our daily lives to opinions on a wide variety of topics. Subjective information is useful to individuals, businesses, and government agencies to support decision making in areas such as product purchase, marketing strategy, and policy making. However, much useful subjective information is buried in ever-growing user generated data on social media platforms, it is still difficult to extract high quality …

An Analysis Of The Technological, Organizational, And Environmental Factors Influencing Cloud Adoption, Joe Malak

Walden Dissertations and Doctoral Studies

Cloud computing provides an answer to the increasing costs of managing information technology (IT), and has become a model that aligns IT services with an organization's business strategies. However, concerns and uncertainties associated with cloud computing are deterring IT decision makers from making sound decisions regarding the adoption of the technology. The purpose of this online survey study was to examine the relationship between relative advantage, compatibility, organizational size, top management support, organizational readiness, mimetic pressure, normative pressures, coercive pressure, and the IT decision makers' intent to adopt cloud computing. The theoretical framework incorporated the diffusion of innovations theory, a …

Measures Of User Interactions, Conversations, And Attacks In A Crowdsourced Platform Offering Emotional Support., Samir Yelne

Browse all Theses and Dissertations

Online social systems have emerged as a popular medium for people in society to communicate with each other. Among the most important reasons why people communicate is to share emotional problems, but most online social systems are uncomfortable or unsafe spaces for this purpose. This has led to the rise of online emotional support systems, where users needing to speak to someone can anonymously connect to a crowd of trained listeners for a one-on-one conversation. To better understand who, how and when users utilize these systems, and to evaluate their safety, this thesis offers a comprehensive examination of the characteristics …

Software Defined Secure Ad Hoc Wireless Networks, Maha Alqallaf

Browse all Theses and Dissertations

Software defined networking (SDN), a new networking paradigm that separates the network data plane from the control plane, has been considered as a flexible, layered, modular, and efficient approach to managing and controlling networks ranging from wired, infrastructure-based wireless (e.g., cellular wireless networks, WiFi, wireless mesh net- works), to infrastructure-less wireless networks (e.g. mobile ad-hoc networks, vehicular ad-hoc networks) as well as to offering new types of services and to evolving the Internet architecture. Most work has focused on the SDN application in traditional and wired and/or infrastructure based networks. Wireless networks have become increasingly more heterogeneous. Secure and collab- …

Knowledge-Empowered Probabilistic Graphical Models For Physical-Cyber-Social Systems, Pramod Anantharam

Browse all Theses and Dissertations

There is a rapid intertwining of sensors and mobile devices into the fabric of our lives. This has resulted in unprecedented growth in the number of observations from the physical and social worlds reported in the cyber world. Sensing and computational components embedded in the physical world constitute a Cyber-Physical System (CPS). Current science of CPS is yet to effectively integrate citizen observations in CPS analysis. We demonstrate the role of citizen observations in CPS and propose a novel approach to perform a holistic analysis of machine and citizen sensor observations. Specifically, we demonstrate the complementary, corroborative, and timely aspects …

Knowledge-Driven Implicit Information Extraction, Pathirage Dinindu Perera

Browse all Theses and Dissertations

Natural language is a powerful tool developed by humans over hundreds of thousands of years. The extensive usage, flexibility of the language, creativity of the human beings, and social, cultural, and economic changes that have taken place in daily life have added new constructs, styles, and features to the language. One such feature of the language is its ability to express ideas, opinions, and facts in an implicit manner. This is a feature that is used extensively in day to day communications in situations such as: 1) expressing sarcasm, 2) when trying to recall forgotten things, 3) when required to …

A Hierarchical Framework For Phylogenetic And Ancestral Genome Reconstruction On Whole Genome Data, Lingxi Zhou

Theses and Dissertations

Gene order gets evolved under events such as rearrangements, duplications, and losses, which can change both the order and content along the genome, through the long history of genome evolution. Recently, the accumulation of genomic sequences provides researchers with the chance to handle long-standing problems about the phylogenies, or evolutionary histories, of sets of species, and ancestral genomic content and orders. Over the past few years, such problems have been proven so interesting that a large number of algorithms have been proposed in the attempt to resolve them, following different standards. The work presented in this dissertation focuses on algorithms …

Learning Hierarchically Decomposable Concepts With Active Over-Labeling, Yuji Mo, Stephen Scott, Doug Downey

School of Computing: Conference and Workshop Papers

Many classification tasks target high-level concepts that can be decomposed into a hierarchy of finer-grained subconcepts. For example, some string entities that are Locations are also Attractions, some Attractions are Museums, etc. Such hierarchies are common in named entity recognition (NER), document classification, and biological sequence analysis. We present a new approach for learning hierarchically decomposable concepts. The approach learns a high-level classifier (e.g., location vs. non-location) by seperately learning multiple finer-grained classifiers (e.g., museum vs. non-museum), and then combining the results. Soliciting labels at a finer level of granularity than that of the target concept is a new approach …

Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan

Research Collection School Of Computing and Information Systems

We espouse a vision of small data-based immersive retail analytics, where a combination of sensor data, from personal wearable-devices and store-deployed sensors & IoT devices, is used to create real-time, individualized services for in-store shoppers. Key challenges include (a) appropriate joint mining of sensor & wearable data to capture a shopper’s product level interactions, and (b) judicious triggering of power-hungry wearable sensors (e.g., camera) to capture only relevant portions of a shopper’s in-store activities. To explore the feasibility of our vision, we conducted experiments with 5 smartwatch-wearing users who interacted with objects placed on cupboard racks in our lab (to …

Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding

Research Collection School Of Computing and Information Systems

Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point (STIP) based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words (BoVW) model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, …

We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

Recent literature advances Wi-Fi signals to “see” people’s motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people’s talks leveraging MIMO technology. We …

Challenging The Efficient Market Hypothesis With Dynamically Trained Artificial Neural Networks, Kevin M. Harper

UNF Graduate Theses and Dissertations

A review of the literature applying Multilayer Perceptron (MLP) based Artificial Neural Networks (ANNs) to market forecasting leads to three observations: 1) It is clear that simple ANNs, like other nonlinear machine learning techniques, are capable of approximating general market trends 2) It is not clear to what extent such forecasted trends are reliably exploitable in terms of profits obtained via trading activity 3) Most research with ANNs reporting profitable trading activity relies on ANN models trained over one fixed interval which is then tested on a separate out-of-sample fixed interval, and it is not clear to what extent these …

Distributed Rule-Based Ontology Reasoning, Raghava Mutharaju

Browse all Theses and Dissertations

The vision of the Semantic Web is to provide structure and meaning to the data on the Web. Knowledge representation and reasoning play a crucial role in accomplishing this vision. OWL (Web Ontology Language), a W3C standard, is used for representing knowledge. Reasoning over the ontologies is used to derive logical consequences. A fixed set of rules are run on an ontology iteratively until no new logical consequences can be derived. All existing reasoners run on a single machine, possibly using multiple cores. Ontologies (sometimes loosely referred to as knowledge bases) that are automatically constructed can be very large. Single …

Customizable 3-D Virtual Gi Tract Systems For Locating, Mapping, And Navigation Inside Human Gastrointestinal Tract, Megha Dattatrey Dalvi

Browse all Theses and Dissertations

One of the critical challenges of wireless capsule endoscopy examination is to find the exact position of the capsule in the Gastrointestinal Tract (GI) tract so as to correctly and accurately spot the position of the intestinal diseases. Creating a 3D virtual GI tract system could significantly improve the capsule endoscopy operations. The virtual human model, such as the BioDigital Human, has been credited as Google Earth for the human body, which provides us medically accurate virtual body and organ structures. However, it only assembles a “Standard” human body. The problem is: there is only one earth, but billions of …

Augment Hololens’ Body Recognition And Tracking Capabilities Using Kinect, Krishna Chaithanya Mathi

Browse all Theses and Dissertations

In this thesis, we are primarily interested in exploring the HoloLens technologies for medical practices. Particularly, we will address the limitation of HoloLens’ capability in human body sensing, recognition and tracking. We will then introduce and demonstrate the use of Kinect to augment HoloLens’ sensory and processing capabilities in order to produce time and space-synchronized immersive environment with both virtual body and real body of the same patient for supporting distributed medical collaborations. Specifically, we are looking at a distributed solution in which we are collecting the patient body data from Kinect, followed by body recognition and position/motion tracking processing …

Novel Cost And Space Efficient Range Of Motion And Gait Analysis Systems, Rutvik Bharatkumar Patel

Browse all Theses and Dissertations

In this thesis, we have explored the use of the latest motion tracking technologies, as evident by Microsoft Xbox Kinect’s motion tracking capabilities, in combination with 3D digital human modeling and animation, multi-modality image capturing and processing, and fusion, to design a new generation of low-cost range of motion and gait analysis solutions that overcome the limitation of existing tools. The proposed solutions and our prototype systems have demonstrated accurate measurements and reliable analysis outcome compared to current clinic practices, with significantly reduced complexity and cost. Furthermore, it eliminates the need for expensive effort for pre- and post- processing of …

Removal Of Impulse Noise In Digital Images With Na\"Ive Bayes Classifier Method, Cafer Budak, Mustafa Türk, Abdullah Toprak

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Application Of A Time Delay Neural Network For Predicting Positive And Negative Links In Social Networks, Saghar Babakhanbak, Kaveh Kavousi, Fardad Farokhi

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Brain Tumor Detection Using Monomodal Intensity Based Medical Image Registration And Matlab, Emrah Irmak, Ergun Erçelebi̇, Ahmet Hani̇fi̇ Ertaş

Turkish Journal of Electrical Engineering and Computer Sciences

digital image processing. Using suitable computer programming techniques and transformation between two images, a new much more informative image can be found. In this paper, three important and basic medical image registration (MIR) methods, namely MIR by maximization of mutual information, MIR using cross correlation (Fourier transform approach), and MIR by minimization of similarity metric, were proposed and accordingly two comprehensive applications were performed using MIR by minimization of the similarity metric, which uses the sum of the squared differences metric as a metric and the regular step gradient descent optimizer as an optimizer. What is more, MR images of …

Fuzzy Logic Based Voltage Control Scheme For Improvement In Dynamic Response Of The Class D Inverter Based High Frequency Induction Heating System, Booma Nagarajan, Rama Reddy Sathi, Pradeep Vishnuram

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.