Computer Sciences Commons^™

Gesture Based Non-Obstacle Interaction On Mobile Computing Devices For Dirty Working Environment, William B. Huynh

Open Access Theses

The dominant way of interacting with tablets, smartphones, or wearable devices are through touchscreen or touchpad, which requires the user to physically touch the device’s screen. However, in certain situation, for example, a dirty working environment, touching is not ideal or feasible. This study examined a new method that allows for a non-touch interaction by using the devices’ back camera along with simple gesture to simulate mouse clicking. Cameras are used to capture motion-based gestures coupled with object detection, achieving a non-touch interaction. With human subject evaluation, the researcher found that using the back camera on mobile devices for gesture …

A Study Of How Chinese Ink Painting Features Can Be Applied To 3d Scenes And Models In Real-Time Rendering, Muning Cao

Open Access Theses

Past research findings addressed mature techniques for non-photorealistic rendering. However, research findings indicate that there is little information dealing with efficient methods to simulate Chinese ink painting features in rendering 3D scenes. Considering that Chinese ink painting has achieved many worldwide awards, the potential to effectively and automatically develop 3D animations and games in this style indicates a need for the development of appropriate technology for the future market.

The goal of this research is about rendering 3D meshes in a Chinese ink painting style which is both appealing and realistic. Specifically, how can the output image appear similar to …

Hardware Accelerated Redundancy Elimination In Network System, Kelu Diao

Open Access Theses

With the tremendous growth in the amount of information stored on remote locations and cloud systems, many service providers are seeking ways to reduce the amount of redundant information sent across networks by using data de-duplication techniques. Data de-duplication can reduce network traffic without the loss of information, and consequently increase available network bandwidth by reducing redundant traffic. However, due to the heavy computation required for detecting and reducing redundant data transmission, de-duplication itself can become a bottleneck in high capacity links. We completed two parts of work in this research study, Hardware Accelerated Redundancy Elimination in Network Systems (HARENS) …

Social Customer Relationship Management In Higher Education, Victorian A. Farnsworth

Open Access Theses

Customer Relationship Management is a concept that has become a requirement for any successful entity to attract and retain desired constituents. It is a set of processes and tools that help track, analyze, and act upon customer related data. Over the last decade, the toolsets have evolved to include social media as another source of information and connection. Nowhere is this information and connection more important than in higher education where globalization and tighter budgets have created a competitive market. This research evaluated the use of this most recent social toolset and its effectiveness in a higher education institution, all …

User-Centric Workload Analytics: Towards Better Cluster Management, Suhas Raveesh Javagal

Open Access Theses

Effective management of computing clusters and providing a high quality customer support is not a trivial task. Due to rise of community clusters there is an increase in the diversity of workloads and the user demographic. Owing to this and privacy concerns of the user, it is difficult to identify performance issues, reduce resource wastage and understand implicit user demands. In this thesis, we perform in-depth analysis of user behavior, performance issues, resource usage patterns and failures in the workloads collected from a university-wide community cluster and two clusters maintained by a government lab. We also introduce a set of …

Bridging Statistical Learning And Formal Reasoning For Cyber Attack Detection, Kexin Pei

Open Access Theses

Current cyber-infrastructures are facing increasingly stealthy attacks that implant malicious payloads under the cover of benign programs. Current attack detection approaches based on statistical learning methods may generate misleading decision boundaries when processing noisy data with such a mixture of benign and malicious behaviors. On the other hand, attack detection based on formal program analysis may lack completeness or adaptivity when modeling attack behaviors. In light of these limitations, we have developed LEAPS, an attack detection system based on supervised statistical learning to classify benign and malicious system events. Furthermore, we leverage control flow graphs inferred from the system event …

A Faster Version Of Louvain Method For Community Detection For Efficient Modeling And Analytics Of Cyber Systems, Sunanda Vivek Shanbhaq

Open Access Theses

Cyber networks are complex networks with various hosts forming the entities of the network and the communication between them forming the edges of the network. Most cyber networks exhibit a community structure. A community is a group of nodes that are densely connected with each other as compared to other nodes in the network. Representing an IP network in the form of communities helps in viewing the network from different levels of granularity and makes the visualization of the network cleaner and more pleasing to the eye. This will help significantly in cyber attack detection in large scale cyber networks. …

Unsupervised Learning Framework For Large-Scale Flight Data Analysis Of Cockpit Human Machine Interaction Issues, Abhishek B. Vaidya

Open Access Theses

As the level of automation within an aircraft increases, the interactions between the pilot and autopilot play a crucial role in its proper operation. Issues with human machine interactions (HMI) have been cited as one of the main causes behind many aviation accidents. Due to the complexity of such interactions, it is challenging to identify all possible situations and develop the necessary contingencies. In this thesis, we propose a data-driven analysis tool to identify potential HMI issues in large-scale Flight Operational Quality Assurance (FOQA) dataset. The proposed tool is developed using a multi-level clustering framework, where a set of basic …

Enhancing The Campus Experience: Helping International Students To Adapt To North American Campus Life, Qiaoying Wang

Open Access Theses

This thesis investigates how culture adaption topic can be applied to a design solution by enhancing international students experience on North American campus. Each year more than half a million international students enroll in American colleges and universities. Many will spend several years on a campus working toward their degree. Most of them arrive with clear academic goals, but they may have no clue what their social lives will be like. In that case, a common phenomenon that most of the international students need to get along with is called “Culture Shock”, which involves culture and academic adapting difficulties, limited …

End-To-End Security In Service-Oriented Architecture, Mehdi Azarmi

Open Access Dissertations

A service-oriented architecture (SOA)-based application is composed of a number of distributed and loosely-coupled web services, which are orchestrated to accomplish a more complex functionality. Any of these web services is able to invoke other web services to offload part of its functionality. The main security challenge in SOA is that we cannot trust the participating web services in a service composition to behave as expected all the time. In addition, the chain of services involved in an end-to-end service invocation may not be visible to the clients. As a result, any violation of client’s policies could remain undetected. To …

On The 3d Point Cloud For Human-Pose Estimation, Kai-Chi Chan

Open Access Dissertations

This thesis aims at investigating methodologies for estimating a human pose from a 3D point cloud that is captured by a static depth sensor. Human-pose estimation (HPE) is important for a range of applications, such as human-robot interaction, healthcare, surveillance, and so forth. Yet, HPE is challenging because of the uncertainty in sensor measurements and the complexity of human poses. In this research, we focus on addressing challenges related to two crucial components in the estimation process, namely, human-pose feature extraction and human-pose modeling.

In feature extraction, the main challenge involves reducing feature ambiguity. We propose a 3D-point-cloud feature called …

Optimal Monitoring And Mitigation Of Systemic Risk In Lending Networks, Zhang Li

Open Access Dissertations

This thesis proposes optimal policies to manage systemic risk in financial networks. Given a one-period borrower-lender network in which all debts are due at the same time and have the same seniority, we address the problem of allocating a fixed amount of cash among the nodes to minimize the weighted sum of unpaid liabilities. Assuming all the loan amounts and cash flows are fixed and that there are no bankruptcy costs, we show that this problem is equivalent to a linear program. We develop a duality-based distributed algorithm to solve it which is useful for applications where it is desirable …

Energy Efficiency In Data Collection Wireless Sensor Networks, Miquel Andres Navarro Patino

Open Access Dissertations

This dissertation studies the problem of energy efficiency in resource constrained and heterogeneous wireless sensor networks (WSNs) for data collection applications in real-world scenarios. The problem is addressed from three different perspectives: network routing, node energy profiles, and network management. First, the energy efficiency in a WSN is formulated as a load balancing problem, where the routing layer can diagnose and exploit the WSN topology redundancy to reduce the data traffic processed in critical nodes, independent of their hardware platform, improving their energy consumption and extending the network lifetime. We propose a new routing strategy that extends traditional cost-based routing …

Developing Probability Maps For Locating And Scouting Unprotected Areas Of Gravel Hill Prairies On Rodman Soils Along The Wabash River Valley Near Lafayette, Indiana, Ryan W.R. Schroeder

Engagement & Service-Learning Summit

No abstract provided.

Sequential Pattern Mining With Uncertain Data, Jiaqi Ge

Open Access Dissertations

In recent years, a number of emerging applications, such as sensor monitoring systems, RFID networks and location based services, have led to the proliferation of uncertain data. However, traditional data mining algorithms are usually inapplicable in uncertain data because of its probabilistic nature. Uncertainty has to be carefully handled; otherwise, it might significantly downgrade the quality of underlying data mining applications.

Therefore, we extend traditional data mining algorithms into their uncertain versions so that they still can produce accurate results. In particular, we use a motivating example of sequential pattern mining to illustrate how to incorporate uncertain information in the …

Missing Gene Identification Using Functional Coherence Scores, Meghana Chitale, Ishita K. Khan, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Reconstructing metabolic and signaling pathways is an effective way of interpreting a genome sequence. A challenge in a pathway reconstruction is that often genes in a pathway cannot be easily found, reflecting current imperfect information of the target organism. In this work, we developed a new method for finding missing genes, which integrates multiple features, including gene expression, phylogenetic profile, and function association scores. Particularly, for considering function association between candidate genes and neighboring proteins to the target missing gene in the network, we used Co-occurrence Association Score (CAS) and PubMed Association Score (PAS), which are designed for capturing functional …

Web Based Cyber Forensics Training For Law Enforcement, Nick Sturgeon

Purdue Polytechnic Masters Theses

Training and education are two of the most important aspects within cyber forensics. These topics have been of concern since the inception of the field. Training law enforcement is particularly important to ensure proper execution of the digital forensics process. It is also important because the proliferation of technology in to society continues to grow at an exponential rate. Just as technology is used for good there are those that will choose to use it for criminal gains. It is critical that Law Enforcement have the tools and training in cyber forensics. This research looked to determine if web based …

Generalized Techniques For Using System Execution Traces To Support Software Performance Analysis, Thelge Manjula Peiris

Open Access Dissertations

This dissertation proposes generalized techniques to support software performance analysis using system execution traces in the absence of software development artifacts such as source code. The proposed techniques do not require modifications to the source code, or to the software binaries, for the purpose of software analysis (non-intrusive). The proposed techniques are also not tightly coupled to the architecture specific details of the system being analyzed. This dissertation extends the current techniques of using system execution traces to evaluate software performance properties, such as response times, service times. The dissertation also proposes a novel technique to auto-construct a dataflow model …

Gpu/Cpu Performance Of Image Processing Tasks For Use In The Cam 2 System, Jonathan Cottom, Yung-Hsiang Lu, Young-Sol Koh

The Summer Undergraduate Research Fellowship (SURF) Symposium

Over the past several years, graphics processing units (GPU) have increasingly been viewed as the future of image processing engines. Currently, the Continuous Analysis of Many CAMeras (CAM²) project performs its processing on CPUs, which will potentially be more costly as the system scales to service more users. This study seeks to analyze the performance gains of GPU processing and evaluate the advantage of supporting GPU-accelerated analysis for CAM² users. The platform for comparing the CPU and GPU performance has been the NVIDIA Jetson TK1. The target hardware implementation is an Amazon cloud instance, where final cost …

Web-Based Fragment Library, Junjie Wang, Lyudmila Slipchenko

The Summer Undergraduate Research Fellowship (SURF) Symposium

A new polarized force field BioEFP for modeling process in biology is far superior in accuracy to the common classical force fields. One of the main shortcomings of BioEFP is that the parameters are not readily available, thus it will take a lot of time to be calculated.

Developing an online repository of pre-computed fragment parameters and a similarity algorithm will allow ascribing each fragment of a biological macromolecule to a pre-defined fragment.

This study incorporates three parts to create the online repository. First, the visual design for the website using the Hypertext Markup Language and the Cascading Style Sheets …

Implementation Of A Speech Recognition Algorithm To Facilitate Verbal Commands For Visual Analytics Law Enforcement Toolkit, Shubham S. Rastogi, David L. Wiszowaty, Hanye Xu, Abish Malik, David S. Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

The VALET (Visual Analytics Law Enforcement Toolkit) system allows the user to visualize and predict crime hotspots and analyze crime data. Police officers have difficulty in using VALET in a mobile situation, since the system allows only conventional input interfaces (keyboard and mouse). This research focuses on introducing a new input interface to VALET in the form of speech recognition, which allows the user to interact with the software without losing functionality. First an Application Program Interface (API) that was compatible with the VALET system was found and initial code scripts to test its functionality were written. Next, the code …

Classification And Visualization Of Crime-Related Tweets, Ransen Niu, Jiawei Zhang, David S. Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

Millions of Twitter posts per day can provide an insight to law enforcement officials for improved situational awareness. In this paper, we propose a natural-language-processing (NLP) pipeline towards classification and visualization of crime-related tweets. The work is divided into two parts. First, we collect crime-related tweets by classification. Unlike written text, social media like Twitter includes substantial non-standard tokens or semantics. So we focus on exploring the underlying semantic features of crime-related tweets, including parts-of-speech properties and intention verbs. Then we use these features to train a classification model via Support Vector Machine. The second part is to utilize visual …

Project Barriers To Green Belts Through Critical Success Factors, Chad Laux, Mary E. Johnson, Paul Cada

Faculty Publications

Purpose The purpose of this paper is to utilize critical success factors (CSF) and identify items Green Belt (GB) practitioners note as barriers to completion of Six Sigma (SS) projects in a major manufacturer setting.

Design/methodology/approach The design of this paper is a descriptive study of a single location of a global manufacturer’s internal data and survey of accredited GBs who have completed an SS project for company accreditation utilizing company focus on CSFs.

Findings The results demonstrate the GB practitioners have competing priorities, have time constraints and lack project management skills that reduce timely completion of SS projects. Top …

Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su

MODVIS Workshop

We propose a combinatorial approach built on Grenander’s pattern theory to generate semantic interpretations of video events of human activities. The basic units of representations, termed generators, are linked with each other using pairwise connections, termed bonds, that satisfy predefined relations. Different generators are specified for different levels, from (image) features at the bottom level to (human) actions at the highest, providing a rich representation of items in a scene. The resulting configurations of connected generators provide scene interpretations; the inference goal is to parse given video data and generate high-probability configurations. The probabilistic structures are imposed using energies that …

Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo

MODVIS Workshop

Computer vision research rarely makes use of symmetry in stereo reconstruction despite its established importance in perceptual psychology. Such stereo reconstructions produce visually satisfying figures with precisely located points and lines, even when input images have low or moderate resolution. However, because few invariants exist, there are no known general approaches to solving symmetry correspondence on real images. The problem is significantly easier when combined with the binocular correspondence problem, because each correspondence problem provides strong non-overlapping constraints on the solution space. We demonstrate a system that leverages these constraints to produce accurate stereo models from pairs of binocular images …

Formal Aspects Of Non-Rigid-Shape-From-Motion Perception, Vicky Froyen, Qasim Zaidi

MODVIS Workshop

Our world is full of objects that deform over time, for example animals, trees and clouds. Yet, the human visual system seems to readily disentangle object motions from non-rigid deformations, in order to categorize objects, recognize the nature of actions such as running or jumping, and even to infer intentions. A large body of experimental work has been devoted to extracting rigid structure from motion, but there is little experimental work on the perception of non-rigid 3-D shapes from motion (e.g. Jain, 2011). Similarly, until recently, almost all formal work had concentrated on the rigid case. In the last fifteen …

Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker

MODVIS Workshop

Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.

To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …

Modeling Visual Features To Recognize Biological Motion: A Developmental Approach, Giulio Sandini, Nicoletta Noceti, Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Alessandro Verri, Francesca Odone

MODVIS Workshop

In this work we deal with the problem of designing and developing computational vision models – comparable to the early stages of the human development – using coarse low-level information.

More specifically, we consider a binary classification setting to characterize biological movements with respect to non-biological dynamic events. To this purpose, our model builds on top of the optical flow estimation, and abstract the representation to simulate the limited amount of visual information available at birth. We take inspiration from known biological motion regularities explained by the Two-Thirds Power Law, and design a motion representation that includes different low-level features, …

Optimal "Big Data" Aggregation Systems - From Theory To Practical Application, William J. Culhane Iv

Open Access Dissertations

The integration of computers into many facets of our lives has made the collection and storage of staggering amounts of data feasible. However, the data on its own is not so useful to us as the analysis and manipulation which allows manageable descriptive information to be extracted. New tools to extract this information from ever growing repositories of data are required.

Some of these analyses can take the form of a two phase problem which is easily distributed to take advantage of available computing power. The first phase involves computing some descriptive partial result from some subset of the original …

Privacy-Preserving Social Network Analysis, Christine Marie Task

Open Access Dissertations

Data privacy in social networks is a growing concern that threatens to limit access to important information contained in these data structures. Analysis of the graph structure of social networks can provide valuable information for revenue generation and social science research, but unfortunately, ensuring this analysis does not violate individual privacy is difficult. Simply removing obvious identifiers from graphs or even releasing only aggregate results of analysis may not provide sufficient protection. Differential privacy is an alternative privacy model, popular in data-mining over tabular data, that uses noise to obscure individuals' contributions to aggregate results and offers a strong mathematical …