Graphics and Human Computer Interfaces Commons^™

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

A Reliable And Efficient Wireless Sensor Network System For Water Quality Monitoring, Dung Nguyen, Phu Huu Phung

Computer Science Faculty Publications

Wireless sensor networks (WSNs) are strongly useful to monitor physical and environmental conditions to provide realtime information for improving environment quality. However, deploying a WSN in a physical environment faces several critical challenges such as high energy consumption, and data loss.In this work, we have proposed a reliable and efficient environmental monitoring system in ponds using wireless sensor network and cellular communication technologies. We have designed a hardware and software ecosystem that can limit the data loss yet save the energy consumption of nodes. A lightweight protocol acknowledges data transmission among the nodes. Data are transmitted to the cloud using …

Procedurally Generating Genetic Keys, Adam A. Levasseur

Computer Engineering

This project presents a method for creating multi-part models based on input keys to generate new, variant models via genetic algorithms. By utilizing 3D models as modular parts, this method allows for the generation of a unique, compound model based on one or multiple input keys. This paper explains the process of creating and testing such generation styles using simple geometry to create more complex, compound models.

P4sinc – An Execution Policy Framework For Iot Services In The Edge, Phu Huu Phung, Hong-Linh Truong, Divya Teja Yasoju

Computer Science Faculty Publications

Internet of Things (IoT) services are increasingly deployed at the edge to access and control Things. The execution of such services needs to be monitored to provide information for security, service contract, and system operation management. Although different techniques have been proposed for deploying and executing IoT services in IoT gateways and edge servers, there is a lack of generic policy frameworks for instrumentation and assurance of various types of execution policies for IoT services. In this paper, we present P4SINC as an execution policy framework that covers various functionalities for IoT services deployed in software-defined machines in IoT infrastructures. …

Investigating Trust And Trust Recovery In Human-Robot Interactions, Abigail L. Thomson

Celebration of Learning

As artificial intelligence and robotics continue to advance and be used in increasingly different functions and situations, it is important to look at how these new technologies will be used. An important factor in how a new resource will be used is how much it is trusted. This experiment was conducted to examine people’s trust in a robotic assistant when completing a task, how mistakes affect this trust, and if the levels of trust exhibited with a robot assistant were significantly different than if the assistant were human. The task was to watch a computer simulation of the three-cup monte …

Simulating Foodborne Pathogens In Poultry Production And Processing To Defend Against Intentional Contamination, Silas B. Lankford

Computer Science and Computer Engineering Undergraduate Honors Theses

There is a lack of data in recent history of food terrorism attacks, and as such, it is difficult to predict its impact. The food supply industry is one of the most vulnerable industries for terrorist threats while the poultry industry is one of the largest food industries in the United States. A small food terrorism attack against just a single poultry processing center has the potential to affect a much larger population than its immediate consumers. In this work, the spread of foodborne pathogens is simulated in a poultry production and processing system to defend against intentional contamination. An …

Hybridguard: A Principal-Based Permission And Fine-Grained Policy Enforcement Framework For Web-Based Mobile Applications, Phu Huu Phung, Abhinav Mohanty, Rahul Rachapalli, Meera Sridhar

Computer Science Faculty Publications

Web-based or hybrid mobile applications (apps) are widely used and supported by various modern hybrid app development frameworks. In this architecture, any JavaScript code, local or remote, can access available APIs, including JavaScript bridges provided by the hybrid framework, to access device resources. This JavaScript inclusion capability is dangerous, since there is no mechanism to determine the origin of the code to control access, and any JavaScript code running in the mobile app can access the device resources through the exposed APIs. Previous solutions are either limited to a particular platform (e.g., Android) or a specific hybrid framework (e.g., Cordova) …

Toward An Iot-Based Expert System For Heart Disease Diagnosis, Do Thanh Thai, Quang Tran Minh, Phu Huu Phung

Computer Science Faculty Publications

IoT technology has been recently adopted in the healthcare system to collect Electrocardiogram (ECG) signals for heart disease diagnosis and prediction. However, noises in collected ECG signals make the diagnosis and prediction system unreliable and imprecise. In this work, we have proposed a new lightweight approach to removing noises in collected ECG signals to perform precise diagnosis and prediction. First, we have used a revised Sequential Recursive (SR) algorithm to transform the signals into digital format. Then, the digital data is proceeded using a revised Discrete Wavelet Transform (DWT) algorithm to detect peaks in the data to remove noises. Finally, …

Static Human Detection And Scenario Recognition Via Wearable Thermal Sensing System, Qingquan Sun, Ju Shen, Haiyan Qiao, Xinlin Huang, Chen Chen, Fei Hu

Computer Science Faculty Publications

Conventional wearable sensors are mainly used to detect the physiological and activity information of individuals who wear them, but fail to perceive the information of the surrounding environment. This paper presents a wearable thermal sensing system to detect and perceive the information of surrounding human subjects. The proposed system is developed based on a pyroelectric infrared sensor. Such a sensor system aims to provide surrounding information to blind people and people with weak visual capability to help them adapt to the environment and avoid collision. In order to achieve this goal, a low-cost, low-data-throughput binary sampling and analyzing scheme is …

Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy

Honors Theses

Localization of phones is a ubiquitous part of the modern mobile electronics landscape. However, there are many situations where the current method of networked localization fails. A Pedestrian Dead Reckoning System where the location of the user is calculated by counting the steps and direction of the user was implemented as an iOS app with python for data analysis. A novel algorithm for wireless sensor localization using Ad-Hoc Bluetooth networks was proposed. A small experiment was performed proving that the system is nearly equal to state of the art algorithms.

Cse: U: Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam Nguyen

Computer Science Faculty Publications

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. The use of natural language with the resulting dialogs makes the flexibility in communicating user utterances commensurate with that in dialog completion paths—an aspect …

Building A Foundation For Digital Animation, Paulynne Castillo

Angelo King Institute for Economic and Business Studies (AKI)

An analysis of the Philippine digital animation sub-sector reveals that the key areas on which resources should be focused to move up the industry’s value chain are: 1) recruiting, developing, and retaining talent; 2) financing the cultivation of original content; and 3) expanding and improving the country’s information communication technology (ICT) infrastructure.

Big Data Visualization Platform For Mixed Reality, Aliakbar Panahi

Theses and Dissertations

The visualization of data helps to provide faster and deeper insight into the data. In this work, a system for visualizing and analyzing big data in an interactive mixed reality environment is proposed. Such a system can be used for representing different types of data such as temporal, geospatial, network graph, and high dimensional. Also, an implementation of this system for four different data types are created. The data types include network data, volumetric data, high dimensional, and spectral data for different mixed reality devices such as Microsoft HoloLens, Oculus Rift, Samsung Gear VR, and Android ARCore were created. It …

Musical Exercise For People With Visual Impairments, Ridwan Ahmed Khan

Dissertations, Master's Theses and Master's Reports

However, it is hard specifically for people with visual impairments to do exercise without proper guidance. They have accessibility issues and thus, without others ’ help, they cannot be sure if they are doing exercise in a consistent form. To address this problem, I have developed a Musical Exercise platform for people with visual impairments . With the help of audio feedback of Musical Exercise, people with visual impairments can perform exercises in a good form consistently. To assess usability of the system and compare different audio profiles of the system, I designed six different con ditions, including blindfolded or …

Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda

Computer Science Faculty Publications

In this work, we present a practical system which uses mobile devices for interactive manuals. In particular, there are two modes provided in the system, namely, expert/trainer and trainee modes. Given the expert/trainer editor, experts design the step-by-step interactive manuals. For each step, the experts capture the images by using phones/tablets and provide visual instructions such as interest regions, text, and action animations. In the trainee mode, the system utilizes the existing object detection and tracking algorithms to identify the step scene and retrieve the respective instruction to be displayed on the mobile device. The trainee then follows the displayed …

Leveraging Static Analysis Tools For Improving Usability Of Memory Error Sanitization Compilers, Rigel Gjomemo, Phu Huu Phung, Edmund Ballou, Kedar S. Namjoshi, V. N. Venkatakrishnan, Lenore Zuck

Computer Science Faculty Publications

Memory errors such as buffer overruns are notorious security vulnerabilities. There has been considerable interest in having a compiler to ensure the safety of compiled code either through static verification or through instrumented runtime checks. While certifying compilation has shown much promise, it has not been practical, leaving code instrumentation as the next best strategy for compilation. We term such compilers Memory Error Sanitization Compilers (MESCs). MESCs are available as part of GCC, LLVM and MSVC suites. Due to practical limitations, MESCs typically apply instrumentation indiscriminately to every memory access, and are consequently prohibitively expensive and practical to only small …

Real-Time, Non-Contact Heart Rate Monitor, Daniel Blike

Computer Engineering

No abstract provided.

Visual Code: Breaking The Binary, Jacob Johannesen, Andrew Adriance

Liberal Arts and Engineering Studies

This project seeks to create an accessible programming language that is more visually based. Although some solutions exist, namely MIT’s Scratch, nothing has caught up to the mobile age. This proj- ect aims to reframe creating a game or app into the context of tell- ing a story, putting character creation first. By researching sto- ry-telling and how people learn, and by applying technical and user interface design knowledge, this project intends to deliver a soft- ware solution that opens introductory coding education to more people.

A Language-Based Model For Specifying And Staging Mixed-Initiative Dialogs, Saverio Perugini, Joshua W. Buck

Computer Science Faculty Publications

Specifying and implementing flexible human-computer dialogs, such as those used in kiosks, is complex because of the numerous and varied directions in which each user might steer a dialog. The objective of this research is to improve dialog specification and implementation. To do so we developed a model for specifying and staging mixed-initiative dialogs. The model involves a dialog authoring notation, based on concepts from programming languages, for specifying a variety of unsolicited reporting, mixed-initiative dialogs in a concise representation that serves as a design for dialog implementation. Guided by this foundation, we built a dialog staging engine which operationalizes …

Improving Electroencephalography-Based Imagined Speech Recognition With A Simultaneous Video Data Stream, Sarah J. Stolze

Computer Science and Computer Engineering Undergraduate Honors Theses

Electroencephalography (EEG) devices offer a non-invasive mechanism for implementing imagined speech recognition, the process of estimating words or commands that a person expresses only in thought. However, existing methods can only achieve limited predictive accuracy with very small vocabularies; and therefore are not yet sufficient to enable fluid communication between humans and machines. This project proposes a new method for improving the ability of a classifying algorithm to recognize imagined speech recognition, by collecting and analyzing a large dataset of simultaneous EEG and video data streams. The results from this project suggest confirmation that complementing high-dimensional EEG data with similarly …

Gecka3d: A 3d Game Engine For Commonsense Knowledge Acquisition, Erik Cambria, Tam Nguyen, Brian Cheng, Kenneth Kwok, Jose Sepulveda

Computer Science Faculty Publications

Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. GECKA3D integrates the potential of serious games and games with a purpose. This provides a platform for the acquisition of reusable and multi-purpose knowledge and also enables the development of games that can provide entertainment value and …

A Study Of Android Malware Detection Techniques And Machine Learning, Balaji Baskaran, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Android OS is one of the widely used mobile Operating Systems. The number of malicious applications and adwares are increasing constantly on par with the number of mobile devices. A great number of commercial signature based tools are available on the market which prevent to an extent the penetration and distribution of malicious applications. Numerous researches have been conducted which claims that traditional signature based detection system work well up to certain level and malware authors use numerous techniques to evade these tools. So given this state of affairs, there is an increasing need for an alternative, really tough malware …

Extended Pixel Representation For Image Segmentation, Deeptha Girish, Vineeta Singh, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We explore the use of extended pixel representation for color based image segmentation using the K-means clustering algorithm. Various extended pixel representations have been implemented in this paper and their results have been compared. By extending the representation of pixels an image is mapped to a higher dimensional space. Unlike other approaches, where data is mapped into an implicit features space of higher dimension (kernel methods), in the approach considered here, the higher dimensions are defined explicitly. Preliminary experimental results which illustrate the proposed approach are promising.

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 …