Computer Sciences Commons^™

On Efficiency Of Distributed Password Recovery, Radek Hranický, Martin Holkovič, Petr Matoušek

Journal of Digital Forensics, Security and Law

One of the major challenges in digital forensics today is data encryption. Due to the leaked information about unlawful sniffing, many users decided to protect their data by encryption. In case of criminal activities, forensic experts are challenged how to decipher suspect's data that are subject to investigation. A common method how to overcome password-based protection is a brute force password recovery using GPU-accelerated hardware. This approach seems to be expensive. This paper presents an alternative approach using task distribution based on BOINC platform. The cost, time and energy efficiency of this approach is discussed and compared to the GPU-based …

Towards Syntactic Approximate Matching - A Pre-Processing Experiment, Doowon Jeong, Frank Breitinger, Hari Kang, Sangjin Lee

Journal of Digital Forensics, Security and Law

Over the past few years the popularity of approximate matching algorithms (a.k.a. fuzzy hashing) has increased. Especially within the area of bytewise approximate matching, several algorithms were published, tested and improved. It has been shown that these algorithms are powerful, however they are sometimes too precise for real world investigations. That is, even very small commonalities (e.g., in the header of a le) can cause a match. While this is a desired property, it may also lead to unwanted results. In this paper we show that by using simple pre-processing, we signicantly can in uence the outcome. Although our test …

An Improved Smote Algorithm Based On Genetic Algorithm For Imbalanced Data Collection, Qiong Gu, Xian-Ming Wang, Zhao Wu, Bing Ning, Chun-Sheng Xin

Electrical & Computer Engineering Faculty Publications

Classification of imbalanced data has been recognized as a crucial problem in machine learning and data mining. In an imbalanced dataset, minority class instances are likely to be misclassified. When the synthetic minority over-sampling technique (SMOTE) is applied in imbalanced dataset classification, the same sampling rate is set for all samples of the minority class in the process of synthesizing new samples, this scenario involves blindness. To overcome this problem, an improved SMOTE algorithm based on genetic algorithm (GA), namely, GASMOTE was proposed. First, GASMOTE set different sampling rates for different minority class samples. A combination of the sampling rates …

An Efficient Method For Optimizing Segmentation Parameters, Jacob D' Avy, Wei-Wen Hsu, Chung-Hao Chen, Andreas F. Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Segmenting an image into meaningful regions is an important step in many computer vision applications such as facial recognition, target tracking and medical image analysis. Because image segmentation is an ill-posed problem, parameters are needed to constrain the solution to one that is suitable for a given application. For a user, setting parameter values is often unintuitive. We present a method for automating segmentation parameter selection using an efficient search method to optimize a segmentation objective function. Efficiency is improved by utilizing prior knowledge about the relationship between a segmentation parameter and the objective function terms. An adaptive sampling of …

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, …

Learning Human Poses From Monocular Images, Xiaochuan Fan

Theses and Dissertations

In this research, we mainly focus on the problem of estimating the 2D human pose from a monocular image and reconstructing the 3D human pose based on the 2D human pose. Here a 3D pose is the locations of the human joints in the 3D space and a 2D pose is the projection of a 3D pose on an image. Unlike many previous works that explicitly use hand-crafted physiological models, both our 2D pose estimation and 3D pose reconstruction approaches implicitly learn the structure of human body from human pose data.

This 3D pose reconstruction is an ill-posed problem without …

Implementation Of An Air Supply Unit Control Scheme For The Uc2av (Unmanned Circulation Control Aerial Vehicle), Cameron Rosen

Electronic Theses and Dissertations

The expanded prevalence of Unmanned Aerial Vehicles (UAVs) in recent years has created many opportunities to research novel applications for their use, enabled by the reduced cost, mission flexibility, and reduced risk that small-scale unmanned platforms provide in comparison to larger aircraft. Despite the versatility of unmanned aviation, limitations on payload size and weight, fuel and power capacity, and takeoff and landing infrastructure can restrict UAV applications, and have created a need for lift augmenting technologies that can reduce the impact of these limitations. Circulation Control (CC) is an active flow technique that has been proven as a method for …

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 …

A Flexible Pet-Based Wearable Sensor For Arterial Pulse Waveform Measurement, Dan Wang, Dean Krusienski, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

In light of the need of health monitoring, the paper presents a flexible polyethylene terephthalate (PET)-based wearable sensor for arterial pulse waveform measurement. The sensor encompasses a polydimethylsiloxane (PDMS) microstructure embedded with an electrolyte-enabled 5×1 transducer array, which spans 6mm and has a spatial resolution of 1.5mm. A pulse signal exerts a deflection on the microstructure and is recorded as a resistance change by a transducer at the site of the pulse. An untrained individual can easily align the sensor on a targeted artery with a negligible margin and then acquire the arterial pulse waveform continuously and non-invasively. This sensor …

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 …

Geometric Deformations Of Sodalite Frameworks, Ciprian Borcea, Ileana Streinu

Computer Science: Faculty Publications

In mathematical crystallography and computational materials science, it is important to infer flexibility properties of framework materials from their geometric representation. We study combinatorial, geometric and kinematic properties for frameworks modeled on sodalite.

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 …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2016, Buenaventura "Ven" Basco

Libraries' Newsletters

No abstract provided.

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 …

The Reconfigurable Machinery Efficient Workspace Analysis Based On The Twist Angles, Ana M. Djuric, Vukica Jovanovic, Mirjana Filipovic, Ljubinko Kevac

Engineering Technology Faculty Publications

A novel methodology for the calculation, visualisation and analysis of the Reconfigurable Machinery Efficient Workspace (RMEW), based on the twist angles, is presented in this paper. The machinery's kinematic parameters are used for calculating the workspace, while the efficient workspace is associated with the machinery's path and includes the end-effector position and orientation. To analyse and visualise many different machinery efficient workspaces at the same time, the calculation is based on the previously developed and validated complex reconfigurable machinery's kinematic structure named n-DOF Global Kinematic Model (n-GKM). An industrial robot is used as an example to demonstrate …

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 …

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

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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 …