Computer Sciences Commons^™

Zebra: Zero-Effort Bilateral Recurring Authentication, Shrirang Mare, Andrés Molina-Markham, Cory Cornelius, Ronald Peterson, David Kotz

Dartmouth Scholarship

Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but …

Volumetric Cloud Rendering: An Animation Of Clouds, Zhaoxin Ye

All Theses

This paper demonstrates a production workflow for a volumetric-rendering-based short animation about clouds. The animation is based on the concept of a giant fish swimming in the sky from Zhuangzi's philosophical story. The algorithm and implementation for the modeling and rendering of clouds are also presented. A renderer was developed that uses the OpenVDB library for data storage, fast retrieving and grid manipulation. A user-friendly pipeline was also developed for cloud modeling and rendering, which used Python and XML for adjusting rendering parameters. The pipeline includes Maya to build the rough cloud model and Houdini to calculate the interior light …

Meshpotato: A C++/Python Api For Production Volumetric Rendering, Kevin Coley

All Theses

MeshPotato is a production volume rendering API written in C++. Its purpose is to simplify the creation of high quality volumetric effects such as fire, smoke, clouds and explosions. MeshPotato has been designed to be extensible and flexible for quick changes. Python bindings have been implemented with this library to allow for tools that are scripted and integrated within popular 3D modeling applications such as Maya and Houdini. The design of MeshPotato is discussed along with its plugin system, volume rendering API and some results from using the tool.

White Noise And Newer Media: The Prophetic Impact Of Jack's Avatars, Caleb Milligan

All Theses

In this paper, I analyze Don DeLillo's White Noise through a contemporary techno-literate approach that utilizes Internet and game studies to better understand its protagonist, Jack Gladney, and to reevaluate the novel's critical legacy. Jack is not a modernist living in a postmodern world, as critics like Tom LeClair, John Duvall, and Leonard Wilcox have claimed for the many years since the publication of this novel. Lacking the authentic consistency for such a title, he is instead a postmodern human simulacrum sampling different character types to avoid his lack of discernable self. In each role he plays, however, he is …

An Automated Build System For Articulated Characters, James Sledge

All Theses

Rigging is the process of designing and implementing the manipulation architecture for an animated three-dimensional character. Rigs that give the animator the most control tend to be the most difficult to set up and maintain. Due to the linear nature of some elements of rigging, the more complicated a rig, the more time-intensive--and therefore more expensive--to achieve a high quality rig. A solution to complex rig iterability is to automate as much of the process as possible. The topic of this thesis is a framework for modular rigging automation, with a focus on quick and efficient rig iteration. A rigger …

The Rusterizer: An Art-Directable And Semi-Procedural Tool For Generating Rust Surfaces, Karen Stritzinger

All Theses

The Rusterizer is an art-directable tool designed to facilitate the creation of rust on the surfaces of 3d models. Cellular automata are combined with a procedural shader to create an animated growth effect. A workflow for using the tool is provided. The result is demonstrated with a time-lapse animation of a robot in an alley as it rusts. Future extensions and improvements to the tool are suggested.

Real-Time Particle Simulation And Motion Capture Interaction, Amanda Morland

All Theses

This thesis presents the design and development of a program that allows artists to explore and create visual effects from the interaction between a particle system and motion captured data. A spatial subdivision scheme was developed to ensure fast and efficient particle-mesh collisions, allowing the user to interact with the system as it runs. Motion captured data was applied to create different animation routines which include a tango electronica dance and a tribal magician choreography. The particle system was created to work in conjunction with these animations and developed to be as versatile as possible, allowing for a multitude of …

A Memento Of Complexity: The Rhetorics Of Memory, Ambience, And Emergence, Glen Southergill

All Dissertations

Drawing from complexity theory, this dissertation develops a schema of rhetorical memory that exhibits extended characteristics. Scholars traditionally conceptualize memory, the fourth canon in classical rhetoric, as place (loci) or image (phantasm). However, memory rhetoric resists the traditional loci-phantasm framework and instead emerges from enmeshments of interiority, collectivity, and technology. Emergence considers the dynamics of fundamental parts that generate complex systems and offers a methodological lens to theorizing memory. The resulting construct informs everyday life, which includes interfacing with pervasive computing or sensing familiarity. Further, congruently with a neurological turn that contradicts simplification, this dissertation resituates rhetorical memory as generative …

A Computational Model Of Memetic Evolution: Optimizing Collective Intelligence, Noah Welsh

All Dissertations

The purpose of this study was to create an adaptive agent based simulation modeling the processes of creative collaboration. This model aided in the development of a new evolutionary based framework through which education scholars, academics, and professionals in all disciplines and industries can work to optimize their collective ability to find creative solutions to complex problems. The basic premise follows that the process of idea exchange, parallels the role sexual reproduction in biological evolution and is essential to society's collective ability to solve complex problems. The study outlined a set of assumptions used to develop a new theory of …

Exploring Video Streaming In Public Settings: Shared Geocaching Over Distance Using Mobile Video Chat, Jason Procyk, Carman Neustaedter, Carolyn Pang, Anthony Tang, Tejinder K. Judge

Research Collection School Of Computing and Information Systems

Our research explores the use of mobile video chat in public spaces by people participating in parallel experiences, where both a local and remote person are doing the same activity together at the same time. We prototyped a wearable video chat experience and had pairs of friends and family members participate in 'shared geocaching' over distance. Our results show that video streaming works best for navigation tasks but is more challenging to use for fine-grained searching tasks. Video streaming also creates a very intimate experience with a remote partner, but this can lead to distraction from the 'real world' and …

An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components — users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user …

On Understanding Diffusion Dynamics Of Patrons At A Theme Park, Jiali Du, Akshat Kumar, Pradeep Reddy Varakantham

Research Collection School Of Computing and Information Systems

In this work, we focus on the novel application of learning the diffusion dynamics of visitors among attractions at a large theme park using only aggregate information about waiting times at attractions. Main contributions include formulating optimisation models to compute diffusion dynamics. We also developed algorithm capable of dealing with noise in the data to populate parameters in the optimization model. We validated our approach using cross validation on a real theme park data set. Our approach provides an accuracy of about 80$% for popular attractions, providing solid empirical support for our diffusion models.

The Quasigroup Block Cipher And Its Analysis, Matthew J. Battey

Student Work

This thesis discusses the Quasigroup Block Cipher (QGBC) and its analysis. We first present the basic form of the QGBC and then follow with improvements in memory consumption and security. As a means of analyzing the system, we utilize tools such as the NIST Statistical Test Suite, auto and crosscorrelation, then linear and algebraic cryptanalysis. Finally, as we review the results of these analyses, we propose improvements and suggest an algorithm suitable for low-cost FPGA implementation.

Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang

Research Collection School Of Computing and Information Systems

Group exercise provides motivation to follow and maintain a healthy daily exercise schedule while enjoying beneficial encouragement and social support from friends and exercise partners. However, mobility and transportation issues frequently prevent seniors from engaging in group activities. To address this problem, we investigated the exercise needs of seniors and developed a prototype remote exercise system. Our system uses haptic feedback to simulate assistive pushing and pulling of limbs when exercising with a partner. We developed three distinct vibration metaphors -- constant push/pull, corrective feedback, and notification -- to convey engagement and connection between exercise partners. We conducted a preliminary …

Creating An Information Systems Security Culture Through An Integrated Model Of Employees Compliance, Mohammad I. Merhi

Theses and Dissertations - UTB/UTPA

Employees’ non-compliance with information systems security policies has been identified as a major threat to organizational data and information systems. This dissertation investigates the process underlying information systems security compliance in organizations with the focus on employees. The process model is complex, comprising many normative, attitudinal, psychological, environmental, and organizational factors. Therefore, the study of information security compliance requires a holistic assessment of all these factors. This dissertation seeks to achieve this objective by offering a comprehensive and integrated model of employee behavior especially focused towards information security compliance. The research framework is influenced by the Reciprocal Determinism Theory which …

A Self-Adaptive Framework For Failure Avoidance In Configurable Software, Jacob Swanson

School of Computing: Dissertations, Theses, and Student Research

Many software systems today are highly-configurable, meaning the user can customize their instance of the application, adding and removing features as needed. However, this configurability makes it harder to ensure that faults will not escape testing and manifest as failures in the field. This is because many failures are configuration-dependent; they will appear under certain combinations of features configurations, but not others. Once faults are found and reported in the field, there can be a long lag time (days, weeks or even months) until patches are created and released to fix them. In the meantime, users will continue to use …

Information And Hardness Quantification Of Graphs: A Computational Study, Brent Dutson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

New techniques to measure the information contained within a network of interconnected nodes (such as links between computers in the Internet) have recently been developed. This work studies the relationship between the computer time needed to solve a common network problem and the information contained within the given network.

On The Database Lookup Problem Of Approximate Matching, Frank Breitinger, Harald Baier, Douglas White

Electrical & Computer Engineering and Computer Science Faculty Publications

Investigating seized devices within digital forensics gets more and more difficult due to the increasing amount of data. Hence, a common procedure uses automated file identification which reduces the amount of data an investigator has to look at by hand. Besides identifying exact duplicates, which is mostly solved using cryptographic hash functions, it is also helpful to detect similar data by applying approximate matching.

Let x denote the number of digests in a database, then the lookup for a single similarity digest has the complexity of O(x). In other words, the digest has to be compared against …

Improving Reuse And Maintainability Of Communication Software With Conversation-Aware Aspects, Ali Raza

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Inter-process communications (IPC) are ubiquitous in today’s software systems, yet they are rarely treated as first-class programming concepts. Implementing crosscutting concerns for message-based IPC are difficult, even using aspect-oriented programming languages (AOPL) such as AspectJ. Many of these challenges are because the context of a communication-related crosscutting concern is often a conversation consisting of message sends and receives. Hence, developers typically have to implement communication protocols manually using primitive operations, such as connect, send, receive, and close. This dissertation describes an extension to AspectJ, called CommJ, with which developers can implement communication-related concerns in cohesive and loosely coupled aspects. It …

Decision Making Using Trust And Risk In Self-Adaptive Agent Organization, Kamilia Ahmadi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Interaction between agents is one of the key factors in multi-agent societies in order to cooperatively execute complex tasks which are beyond the capability of a single agent. In the self-adaptation society, agents try to keep best neighbors around themselves. Agents use history of past iterations to evaluate their neighbors and locally modify their structural links. Main characteristics of this model are its decentralization, dynamicity and no need of external control. This research at first deals with implementing self-adaptive agent organization. Then it focuses on evaluating cooperation peers in decision making. Trust as an evaluation mechanism lies at the core …

Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao

Research Collection School Of Computing and Information Systems

No abstract provided.

Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni

Research Collection School Of Computing and Information Systems

Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …

Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu

Research Collection School Of Computing and Information Systems

Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …

Technique For Authenticating H.264/Svc And Its Performance Evaluation Over Wireless Mobile Networks, Yifan Zhao, Swee Won Lo, Robert H. Deng, Xuhua Ding

Research Collection School Of Computing and Information Systems

In this paper, a bit stream-based authentication scheme for H.264/Scalable Video Coding (SVC) is proposed. The proposed scheme seamlessly integrates cryptographic algorithms and Erasure Correction Codes (ECCs) to SVC video streams such that the authenti- cated streams are format compliant with the SVC specifications and preserve the three- dimensional scalability (i.e., spatial, quality and temporal) of the original streams. We implement our scheme on a smart phone and study its performance over a realistic bursty packet-lossy wireless mobile network. Our analysis and experimental results show that the scheme achieves very high verification rates with lower communication overhead and much smaller …

Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Researchers have introduced the Dynamic Distributed Constraint Optimization Problem (Dynamic DCOP) formulation to model dynamically changing multi-agent coordination problems, where a dynamic DCOP is a sequence of (static canonical) DCOPs, each partially different from the DCOP preceding it. Existing work typically assumes that the problem in each time step is decoupled from the problems in other time steps, which might not hold in some applications. Therefore, in this paper, we make the following contributions: (i) We introduce a new model, called Markovian Dynamic DCOPs (MD-DCOPs), where the DCOP in the next time step is a function of the value assignments …

Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

A great challenge of city planners is to provide efficient and effective connection service to travelers using public transportation system. This is commonly known as the last-mile problem and is critical in promoting the utilization of public transportation system. In this paper, we address the last-mile problem by considering a dynamic and demand-responsive mechanism for arranging ride sharing on a non-dedicated commercial fleet (such as taxis or passenger vans). Our approach has the benefits of being dynamic, flexible, and with low setup cost. A critical issue in such ride-sharing service is how riders should be grouped and serviced, and how …

Canaries In The Urban Data Mine: Analytics For Smarter City Life, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Technology-based sensors and data analytics have created unprecendented levels of informedness for consumers, corporations, the public and government agencies. The information they generated provides a basis for smarter cities and more sustainable urban living.

How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Linus’ Law reflects on a key characteristic of open source software development: developers’ tendency to closely work together in the bug resolution process. In this paper we empirically examine Linus’ Law using a data-set of 1,000+ Android bugs, owned by 70+ developers. Our results indicate that encouraging developers to work closely with one another has nuanced implications; while one form of contact may help reduce bug resolution time, another form can have quite the opposite effect. We present statistically significant evidence in support of our results and discuss their relevance at the individual and organizational levels.

Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Detecting anomaly collections is an important task with many applications, including spam and fraud detection. In an anomaly collection, entities often operate in collusion and hold different agendas to normal entities. As a result, they usually manifest collective extreme traits, i.e., members of an anomaly collection are consistently clustered toward the top or bottom ranks on certain features. We therefore propose to detect these anomaly collections by extreme feature ranks. We introduce a novel anomaly definition called Extreme Rank Anomalous Collection or ERAC. We propose a new measure of anomalousness capturing collective extreme traits based on a statistical model. As …

Towards Semantically Secure Outsourcing Of Association Rule Mining On Categorical Data, Junzuo Lai, Yingjiu Li, Robert H. Deng, Jian Weng, Chaowen Guan, Qiang Yan

Research Collection School Of Computing and Information Systems

When outsourcing association rule mining to cloud, it is critical for data owners to protect both sensitive raw data and valuable mining results from being snooped at cloud servers. Previous solutions addressing this concern add random noise to the raw data and/or encrypt the raw data with a substitution mapping. However, these solutions do not provide semantic security; partial information about raw data or mining results can be potentially discovered by an adversary at cloud servers under a reasonable assumption that the adversary knows some plaintext–ciphertext pairs. In this paper, we propose the first semantically secure solution for outsourcing association …