Computer Sciences Commons^™

An Autonomic Computing System Based On A Rule-Based Policy Engine And Artificial Immune Systems, Rahmira Rufus, William Nick, Joseph Shelton, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Autonomic computing systems arose from the notion that complex computing systems should have properties like those of the autonomic nervous system, which coordinates bodily functions and allows attention to be directed to more pressing needs. An autonomic system allows the system administrator to specify high-level policies, which the system maintains without administrator assistance. Policy enforcement can be done with a rule based system such as Jess (a java expert system shell). An autonomic system must be able to monitor itself, and this is often a limiting factor. We are developing an automatic system that has a policy engine and uses …

Towards The Development Of A Cyber Analysis & Advisement Tool (Caat) For Mitigating De-Anonymization Attacks, Siobahn Day, Henry Williams, Joseph Shelton, Gerry Dozier

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We are seeing a rise in the number of Anonymous Social Networks (ASN) that claim to provide a sense of user anonymity. However, what many users of ASNs do not know that a person can be identified by their writing style.

In this paper, we provide an overview of a number of author concealment techniques, their impact on the semantic meaning of an author's original text, and introduce AuthorCAAT, an application for mitigating de-anonymization attacks. Our results show that iterative paraphrasing performs the best in terms of author concealment and performs well with respect to Latent Semantic Analysis.

Situations And Evidence For Identity Using Dempster-Shafer Theory, William Nick, Yenny Dominguez, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We present a computational framework for identity based on Barwise and Devlin’s situation theory. We present an example with constellations of situations identifying an individual to create what we call id-situations, where id-actions are performed, along with supporting situations. We use Semantic Web standards to represent and reason about the situations in our example. We show how to represent the strength of the evidence, within the situations, as a measure of the support for judgments reached in the id-situation. To measure evidence of an identity from the supporting situations, we use the Dempster-Shafer theory of evidence. We enhance Dempster- Shafer …

Student Understanding And Engagement In A Class Employing Comps Computer Mediated Problem Solving: A First Look, Jung Hee Kim, Michael Glass, Taehee Kim, Kelvin Bryant, Angelica Willis, Ebonie Mcneil, Zachery Thomas

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

COMPS computer-mediated group discussion exercises are being added to a second-semester computer programming class. The class is a gateway for computer science and computer engineering students, where many students have difficulty succeeding well enough to proceed in their major. This paper reports on first results of surveys on student experience with the exercises. It also reports on the affective states observed in the discussions that are candidates for analysis of group functioning. As a step toward computer monitoring of the discussions, an experiment in using dialogue features to identify the gender of the participants is described.

A Tool For Staging Mixed-Initiative Dialogs, Joshua W. Buck, Saverio Perugini

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We discuss and demonstrate a tool for prototyping dialog-based systems that, given a high-level specification of a human-computer dialog, stages the dialog for interactive use. The tool enables a dialog designer to evaluate a variety of dialogs without having to program each individual dialog, and serves as a proof-of-concept for our approach to mixed-initiative dialog modeling and implementation from a programming language-based perspective.

Keynote Talk 2: Social And Perceptual Fidelity Of Avatars And Autonomous Agents In Virtual Reality, Benjamin Kunz

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Advances in display, computing and sensor technologies have led to a revival of interest and excitement surrounding immersive virtual reality. Here, on the cusp of the arrival of practical and affordable virtual reality technology, are open questions regarding the factors that contribute to compelling and immersive virtual worlds.

In order for virtual reality to be useful as a tool for use in training, education, communication, research, content-creation and entertainment, we must understand the degree to which the perception of the virtual environment and virtual characters resembles perception of the real world.

Relatedly, virtual reality's utility in these contexts demands evidence …

Exploring Web-Based Visual Interfaces For Searching Research Articles On Digital Library Systems, Maxwell Fowler, Chris Bellis, Chris Perry, Beomjin Kim

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Previous studies that present information archived in digital libraries have used either document meta-data or document content. The current search mechanisms commonly return text-based results that were compiled from the meta-data without reflecting the underlying content. Visual analytics is a possible solution for improving searches by presenting a large amount of information, including document content alongside meta-data, in a limited screen space. This paper introduces a multi-tiered visual interface for searching research articles stored in Digital Library systems. The goals of this system are to allow users to find research papers about their interests in a large work space, to …

Fuzzy Algorithms: Applying Fuzzy Logic To The Golden Ratio Search To Find Solutions Faster, Stephany Coffman-Wolph

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Applying the concept of fuzzy logic (an abstract version of Boolean logic) to well-known algorithms generates an abstract version (i.e., fuzzy algorithm) that often results in computational improvements. Precision may be reduced but counteracted by gaining computational efficiency. The trade-offs (e.g., small increase in space, loss of precision) for a variety of applications are deemed acceptable. The fuzzification of an algorithm can be accomplished using a simple three-step framework. Creating a new fuzzy algorithm goes beyond simply converting the data from raw data into fuzzy data by additionally converting the operators and concepts into their abstract equivalents. This paper demonstrates: …

The Webid Protocol Enhanced With Group Access, Biometrics, And Access Policies, Cory Sabol, William Nick, Maya Earl, Joseph Shelton, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

The WebID protocol solves the challenge of remembering usernames and passwords. We enhance this protocol in three ways. First, we give it the ability to manage groups of agents and control their access to resources on the Web. Second, we add support for biometric access control to enhance security. Finally, we add support for OWL-based policies that may be federated and result in flexible access control.

Real-Time Unsupervised Clustering, Gabriel Ferrer

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

In our research program, we are developing machine learning algorithms to enable a mobile robot to build a compact representation of its environment. This requires the processing of each new input to terminate in constant time. Existing machine learning algorithms are either incapable of meeting this constraint or deliver problematic results. In this paper, we describe a new algorithm for real-time unsupervised clustering, Bounded Self-Organizing Clustering. It executes in constant time for each input, and it produces clusterings that are significantly better than those created by the Self-Organizing Map, its closest competitor, on sensor data acquired from a physically embodied …

Dueling-Hmm Analysis On Masquerade Detection, Peter Chou

Master's Projects

Masquerade detection is the ability to detect attackers known as masqueraders that intrude on another user’s system and pose as legitimate users. Once a masquerader obtains access to a user’s system, the masquerader has free reign over whatever data is on that system. In this research, we focus on masquerade detection and user classi cation using the following two di erent approaches: the heavy hitter approach and 2 di erent approaches based on hidden Markov models (HMMs), the dueling-HMM and threshold-HMM strategies.

The heavy hitter approach computes the frequent elements seen in the training data sequence and test data sequence …

Audio Software (Vst Plugin) Development With Practical Application, Zachary Hummel

Honors Theses

Audio engineers around the world routinely utilize small pieces of software, known as “plugins,” to help shape the sound of the media they are working with. These plugins are inserted into a digital audio workstation (DAW) and contain digital signal processing (DSP) algorithms that can affect audio in a number of ways limited only by the creativity of the software developer. Common implementations of plugins include equalizers, compressors and limiters, gain, phase rotation or polarity inversion algorithms, reverb and delay, and emulation of the non-linearities of analog audio equipment. The intent of this thesis project is to design and produce …

A Roadmap To Safe And Reliable Engineered Biological Nano-Communication Networks, Justin W. Firestone

School of Computing: Dissertations, Theses, and Student Research

Synthetic biology has the potential to benefit society with novel applications that can improve soil quality, produce biofuels, grow customized biological tissue, and perform intelligent drug delivery, among many other possibilities. Engineers are creating techniques to program living cells, inserting new logic, and leveraging cell-to-cell communication, which result in changes to a cell's core functionality. Using these techniques, we can now create synthetic biological organisms (SBOs) with entirely new (potentially unseen) behaviors, which, similar to silicon devices, can sense, actuate, perform computation, and interconnect with other networks at the nanoscale level. SBOs are programmable evolving entities, and can be likened …

Identifying Terrorist Affiliations Through Social Network Analysis Using Data Mining Techniques, Govand A. Ali

Information Technology Master Theses

In a technologically enabled world, local ideologically inspired warfare becomes global all too quickly, specifically terrorist groups like Al Quaeda and ISIS (Daesh) have successfully used modern computing technology and social networking environments to broadcast their message, recruit new members, and plot attacks. This is especially true for such platforms as Twitter and encrypted mobile apps like Telegram or the clandestine Alrawi. As early detection of such activity is crucial to attack prevention data mining techniques have become increasingly important in the fight against the spread of global terrorist activity. This study employs data mining tools to mine Twitter for …

Pooling Strength Amongst Limited Datasets Using Hierarchical Bayesian Analysis, With Application To Pyroclastic Density Current Mobility Metrics, Sarah E. Ogburn, James Berger, Eliza S. Calder, Danilo Lopes, Abani K. Patra, E. Bruce Pitman, Regis Rutarindwa, Elaine Spiller, Robert L. Wolpert

Mathematics, Statistics and Computer Science Faculty Research and Publications

In volcanology, the sparsity of datasets for individual volcanoes is an important problem, which, in many cases, compromises our ability to make robust judgments about future volcanic hazards. In this contribution we develop a method for using hierarchical Bayesian analysis of global datasets to combine information across different volcanoes and to thereby improve our knowledge at individual volcanoes. The method is applied to the assessment of mobility metrics for pyroclastic density currents in order to better constrain input parameters and their related uncertainties for forward modeling. Mitigation of risk associated with such flows depends upon accurate forecasting of possible inundation …

The User Attribution Problem And The Challenge Of Persistent Surveillance Of User Activity In Complex Networks, Claudio Taglienti, James D. Cannady Jr.

CCE Faculty Articles

In telecommunication networks, the user attribution problem refers to the challenge faced in recognizing communication traffic as belonging to a given user when information needed to identify the user is missing. This problem becomes more difficult to tackle as users move across many mobile networks (complex networks) owned and operated by different providers. The traditional approach of using the source IP address as a tracking identifier does not work when used to identify mobile users. Recent efforts to address this problem by exclusively relying on web browsing behavior to identify users, brought to light the challenges of solutions which try …

Method For Determining Time-Resolved Heat Transfer Coefficient And Adiabatic Effectiveness Waveforms With Unsteady Film Cooling, James L. Rutledge, Jonathan F. Mccall

AFIT Patents

A new method for determining heat transfer coefficient (h) and adiabatic effectiveness (η) waveforms h(t) and η(t) from a single test uses a novel inverse heat transfer methodology to use surface temperature histories obtained using prior art approaches to approximate the h(t) and η(t) waveforms. The method best curve fits the data to a pair of truncated Fourier series.

Software Improvements To Parint, A Parallel Integration Software Package, Lawrence Cuneaz

Honors Theses

The best software is easy to configure and compile, is expandable and is well tested. Development of the ParInt software package for parallel integration stopped a number of years ago. When handed the software, parts of the package no longer configured or compiled consistently. Furthermore it relied on one random number generator and had no functional testing. The team tuned the auto configuration so that the program would configure and build on current systems, created expandable functionality to add new random number generators and created two functional test packs. Now ParInt can be developed with confidence knowing that it compiles …

Parallel Infeasibility Analysis, Wenting Zhao, Mark Liffiton, Faculty Advisor

John Wesley Powell Student Research Conference

Oral presentation abstract.

A Unifying Framework In Vector-Valued Reproducing Kernel Hilbert Spaces For Manifold Regularization And Co-Regularized Multi-View Learning, Hà Quang Minh, Loris Bazzani, Vittorio Murino

Dartmouth Scholarship

This paper presents a general vector-valued reproducing kernel Hilbert spaces (RKHS) framework for the problem of learning an unknown functional dependency between a struc- tured input space and a structured output space. Our formulation encompasses both Vector-valued Manifold Regularization and Co-regularized Multi-view Learning, providing in particular a unifying framework linking these two important learning approaches. In the case of the least square loss function, we provide a closed form solution, which is obtained by solving a system of linear equations. In the case of Support Vector Machine (SVM) classification, our formulation generalizes in particular both the binary Laplacian SVM to …

Chipathlon: A Competitive Assessment For Gene Regulation Tools, Avi Knecht, Adam Caprez, Istvan Ladunga

UCARE: Research Products

When gene regulation of the cell cycle malfunctions, it frequently causes cancer.

Adult, differentiated cells can be reprogrammed to induced pluripotent stem cell; which can then be reprogrammed to heart muscle, skin, etc, to repair damaged tissue (to limited extent in clinical practice).

ChIPathlon: Evaluate the performance of all transcription factor mapping (peak calling) methods. To this end, we will develop a scalable and easy to use super computing pipeline to stage data, compare many different peak calling and differential binding site tools, and store all results into a single database.

Equality And Hierarchy In Human-Robot Interaction, Kathryn E. Golden Miss, Kimberly Stowers

Human Factors and Applied Psychology Student Conference

No abstract provided.

High Performance Bayesian Applications In Medical, Economics And Climate Sciences, Ahmed Almulihi

Research and Creative Activities Poster Day

We apply high performance numerical integration to problems in Bayesian statistics. These are applied to data arising in the analysis of problems in such areas as medical statistics (birth weight data, heart transplant data, photocarcinogen data, radio therapy data), climate (global weather, tornado data), and general statistics applications (multivariate logistic distribution, multivariate normal, nonlinear regression). We compute Bayesian moment integrals using the ParInt integration software that runs efficiently on computer clusters. We compare our results to those in the literature and show excellent performance with respect to accuracy and execution time.

Work Protecting Sensitive Data In Vanets Using Active Data Bundles, Abduljaleel M. Al Hasnawi

Research and Creative Activities Poster Day

Conclusions

• Integrating ADB with VANETs inaneffective and efficient way shouldsolvemost of the privacyissuesin VANETs
• ADB is extensible -allows adding more security and privacy protection mechanisms
• According to the sensitivity of the carried data

Future Work

• Evaluateusing ADB in VANETs via simulation
• Propose ADB routingprotocolfor VANETs
• Apply the proposed solution to diverseVANETapplications

Towards A Self Adaptive System For Social Wellness, Asad Masood Khattak, Wajahat Ali Khan, Zeeshan Pervez, Farkhund Iqbal, Sungyoung Lee

All Works

© 2016 by the authors; licensee MDPI, Basel, Switzerland. Advancements in science and technology have highlighted the importance of robust healthcare services, lifestyle services and personalized recommendations. For this purpose patient daily life activity recognition, profile information, and patient personal experience are required. In this research work we focus on the improvement in general health and life status of the elderly through the use of an innovative services to align dietary intake with daily life and health activity information. Dynamic provisioning of personalized healthcare and life-care services are based on the patient daily life activities recognized using smart phone. To …

Proposal For A Digital Archives Program At The Dr. Joann Rayfield Archives, Eric Willey, April Karlene Anderson, Ross Griffiths, Dallas Long

Faculty and Staff Publications – Milner Library

A report submitted in April 2016 discussing the creation of an infrastructure for the collection and preservation of digital files by the archives of Illinois State University. Includes three possible strategies based on monetary cost and staff time, with hardware and software recommendations appropriate to each.

Make A Twitter Bot In Python: Iterative Code Examples, Robin Camille Davis, Mark E. Eaton

Publications and Research

A tutorial based upon the LACUNY Emerging Technologies Committee’s “Build Your Own Twitter Bot” day in December 2015, which was billed as a gentle introduction to programming in Python.

Ensemble Noise Filtering For Streaming Data Using Poisson Bootstrap Model Filtering, Ashwin Satyanarayana, Rosemary Chinchilla

Publications and Research

Ensemble filtering techniques filter noisy instances by combining the predictions of multiple base models, each of which is learned using a traditional algorithm. However, in the last decade, due to the massive increase in the amount of online streaming data, ensemble filtering methods, which largely operate in batch mode and requires multiple passes over the data, cause time and storage complexities. In this paper, we present an ensemble bootstrap model filtering technique with multiple inductive learning algorithms on several small Poisson bootstrapped samples of online data to filter noisy instances. We analyze three prior filtering techniques using Bayesian computational analysis …

Uncertainty Avoidance—A New Teaching/ Learning Method For An Introductory Programming Course, Zhen Jiang

Computer Science Faculty Publications

In this paper, we introduce a new procedure for under-represented students to quickly learn the use of the decision structure in computer programming. The challenge here is to help students, who lack sufficient background of mathematics and computer programming, to use this structure correctly without too much doubt and uncertainty. The traditional CS0 program elapses several semesters and requires many foundation courses to be taken before the students have knowledge of the program correctness. Our one-semester course CSC115 allows students to build up programming skills gradually case by case and program by program. Such a guideline is proven to be …

A Graph-Based Semantics Workbench For Concurrent Asynchronous Programs, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by Scoop—a concurrent object-oriented message-passing language—which has seen multiple semantics proposed and implemented over its evolution. We propose a “semantics workbench” with fully and semi-automatic tools for Scoop, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a …