Physical Sciences and Mathematics Commons^™

Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Adaptive Randomized Rounding In The Big Parsimony Problem, Sangho Shim, Sunil Chopra, Eunseok Kim

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective, Montana Ferita, Julie Fucarino, Alex Capaldi, Charlotte Beckford

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Period Drift In A Neutrally Stable Stochastic Oscillator, Kevin Sanft

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

An Agent-Based Model Of An Endangered Florida Tillansia Utriculata Population, Erin N. Bodine, Alexandra Campbell, Anna C. Kula

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Social Inclusion In The Digital Era: Rethinking Debates And Narratives In The World Bank Report., Calisto Kondowe, Wallace Chigona

African Conference on Information Systems and Technology

The 2019 (5th) proceedings of ACIST focuses on how African societies are leveraging and can leverage the smart capabilities in digital technologies to address organizational and societal challenges. Technology-enabled solutions offer solutions to many of these challenges. Digital technologies are increasingly becoming integral to and interdependent with the African society.

An Electronic Framework To Shepherd The Pastoral Livestock (Resolve Conflicts In Pastoral Communities), Frezewd Lemma, Anteneh Alemu, Desta Zerihun, Endale Aregu

African Conference on Information Systems and Technology

This paper proposes a tracking framework based on GPS enabled location sensors, the GSM/WCDMA wireless network, and algorithms running in an edge clouds to resolve deadly conflicts that arise in the Africans pastorals community. The paper also proposes an automatic digital identification mechanism that helps resolve conflicts during animals mixup. This algorithmic based solution would totally relief the community from using the traditional identification mechanisms such as hot branding which are known to be cruel to animals. To communicate with the pastorals, the framework takes into consideration the low level literacy of the community as well as their use of …

Factors Influencing Customers’ Attitude For Using M-Birr Adoption In Ethiopia, Gebremedhin Gebreyohans, Abdurehman Ali

African Conference on Information Systems and Technology

Diffusion of Innovations (DOI) is a theory to explain how and over time new philosophies and then technology diffuse into different contexts. This research tested the attributes of DOI and other variables empirically,usingM-Birr system as the goal of the innovation. The research was conducted among customers of M-Birr service in Addis Ababa, Ethiopia. The data collection instrument was a closed-ended questionnaire administered to 360 respondents of which 211 were returned giving 58.6% return rate. The demographic make-up of the respondents showed that most of them were between the age of 30 to 50 and degree holders. From the factor analysis …

Applying Machine Learning To Encrypted Network Traffic For Malware Detection, Derek Manning

Landmark Conference Summer Research Symposium

The landscape of network analysis is ever-evolving as the fields of technology and business progress. While the landscape of the analysis may change, at the core of network analysis is the detection of malicious activity. In real-time traffic flow, it is non-trivial to determine whether a particular flow is malicious in nature. Most malicious software (malware) analysis is done after the flow has already reached its end target, and is analyzed in the form of network traffic captures. For any network analysis system, it is important that the privacy of the data being transmitted it not compromised in the process. …

Smiler: Consistent And Usable Saliency Model Implementations, Toni Kunic, Calden Wloka, John K. Tsotsos

MODVIS Workshop

The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintaining and executing computational saliency models. This work drastically reduces the human effort required to apply saliency algorithms to new tasks and datasets, while also ensuring consistency and procedural correctness for results and conclusions produced by different parties. At its launch SMILER already includes twenty three saliency models (fourteen models based in MATLAB and nine supported through containerization), and the open design of SMILER encourages this number to grow with future contributions from the community. The project …

Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos

MODVIS Workshop

No abstract provided.

The Fluid Representations Of Networks Estimating Liquid Viscosity, Jan Jaap R. Van Assen, Shin'ya Nishida, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Forensic Analysis Of Spy Applications In Android Devices, Shinelle Hutchinson, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Smartphones with Google's Android operating system are becoming more and more popular each year, and with this increased user base, comes increased opportunities to collect more of these users' private data. There have been several instances of malware being made available via the Google Play Store, which is one of the predominant means for users to download applications. One effective way of collecting users' private data is by using Android Spyware. In this paper, we conduct a forensic analysis of a malicious Android spyware application and present our findings. We also highlight what information the application accesses and what it …

Towards Human Retinal Cones Spatial Distribution Modeling, Matteo Paolo Lanaro, Hélène Perrier, David Coeurjolly, Victor Ostromoukhov, Alessandro Rizzi

MODVIS Workshop

No abstract provided.

Recovering Depth From Stereo Without Using Any Oculomotor Information, Tadamasa Sawada

MODVIS Workshop

The human visual system uses binocular disparity to perceive depth within 3D scenes. It is commonly assumed that the visual system needs oculomotor information about the relative orientation of the two eyes to perceive depth on the basis of binocular disparity. The necessary oculomotor information can be obtained from an efference copy of the oculomotor signals, or from a 2D distribution of the vertical disparity, specifically, from the vertical component of binocular disparity. It is known that oculomotor information from the efference copy and from the vertical disparity distribution can affect the perception of depth based on binocular disparity. But, …

Smart Home Simulation In The Virtual World, Thomas Jones-Moore, David Son

Scholars Week

The goal of this project is to produce a 'smart home' by using IoT and RFID like things in the virtual world to help solve problems. Some of these problems can be CPR training, etc. Used as an evaluation platform of suggested hardware to get a desired (or best fit) set of smart objects, or combinations with computer vision. Cost model to determine best fit based on: accuracy, lowest cost, easiest deployment, etc.

Performance Annotation Framework, Quentin Jensen, Chloe Dawson

Scholars Week

Large scale applications developers have many tools at their disposal to optimize and verify their software. One of which is Caliper, an annotation-based performance measurement tool. Caliper is very powerful and versatile, however, can be cumbersome to apply to complex applications. To solve this problem, we have created a framework to automatically prepare an application for performance measurement. This framework provides a layer of abstraction between the user and the source-code annotations and library linking. As a result, the process of measuring the performance of an application can be fully automated away – a huge step towards automatic software optimization.

A Simulation Platform For Generation Of Synthetic Videos For Human Activity Recognition, Gary Plunkett

Scholars Week

The field of human activity recognition from video data has recently made great strides. However, the large amount of labelled data needed to train activity recognition models remains a common bottleneck. We introduce a simulation platform to procedurally generate synthetic videos of household activities, which randomizes portions of the virtual scene like camera position, human model, and interaction motion to introduce video variation.

A Day In The Life Of A Supercomputer, William Clem, Sean Mcculloch

Scholars Week

We are developing an interactive dashboard for visualizing the statistics of how users interact with nodes of a supercomputer. The intended purpose of the dashboard is to periodically provide with the overview of the load and bandwidth utilization of the nodes of a large supercomputer and details of each node and job as selected by the user. The dashboard will be interactive which will enable users to zoom in on interesting parts of the visualizations to investigate in details.

Development Of A Design Guideline For Pile Foundations Subjected To Liquefaction-Induced Lateral Spreading, Milad Souri, Arash Khosravifar

Student Research Symposium

Past earthquakes confirmed that seismically induced kinematic loads from soil lateral spreading and inertial loads from structure can cause severe damages to pile foundations. The research questions are:

• How to combine inertial and kinematic loads in design of pile foundations in liquefied soil?
• How the combination of inertia and kinematics changes with depth?
• How this combination is affected by long-duration earthquakes?
• How this combination affects inelastic demands in piles?

Exploring And Expanding The One-Pixel Attack, Umairullah Khan, Walt Woods, Christof Teuscher

Student Research Symposium

In machine learning research, adversarial examples are normal inputs to a classifier that have been specifically perturbed to cause the model to misclassify the input. These perturbations rarely affect the human readability of an input, even though the model’s output is drastically different. Recent work has demonstrated that image-classifying deep neural networks (DNNs) can be reliably fooled with the modification of a single pixel in the input image, without knowledge of a DNN’s internal parameters. This “one-pixel attack” utilizes an iterative evolutionary optimizer known as differential evolution (DE) to find the most effective pixel to perturb, via the evaluation of …

Yelp Improved : Aggregating Restaurant Reviews, Kunal Sonar

Creative Activity and Research Day - CARD

In the near future, online food delivery service companies would occupy a big market share in the food industry. This project aims to provide factual information from customer reviews as part of the numerous innovations in place to drive business and demands. Natural Language Processing is used to provide a comprehensive view of individual restaurants using technologies like NLTK, SpaCy, Gensim and Sklearn. Data of one million Las Vegas restaurant customer reviews is curated from the Yelp Dataset Challenge. Reviews are pre-processed, split into chunks of phrases and mapped to attributes like food, budget, service etc. These attributes are derived …

Deep Neural Network Architectures For Music Genre Classification, Kai Middlebrook, Shyam Sudhakaran, Kunal Sonar, David Guy Brizan

Creative Activity and Research Day - CARD

With the recent advancements in technology, many tasks in fields such as computer vision, natural language processing, and signal processing have been solved using deep learning architectures. In the audio domain, these architectures have been used to learn musical features of songs to predict: moods, genres, and instruments. In the case of genre classification, deep learning models were applied to popular datasets--which are explicitly chosen to represent their genres--and achieved state-of-the-art results. However, these results have not been reproduced on less refined datasets. To this end, we introduce an un-curated dataset which contains genre labels and 30-second audio previews for …

Patterns In Color Perception, Madeline Henson, Taimur Iftikhar

Student Symposium

Synesthesia is a neurological condition that forces individuals to process a lot of different senses at once. These different senses can be stimulated by anything; for example, if one hears some sounds, they might also perceive those sounds as colors and vice versa. Another form of Synesthesia, termed Grapheme-Color Synesthesia, can occur when one looks at different characters in a language and they see different colors generated in their brain. The amount of colors a person sees by looking at different characters varies. Our goal for our project was to figure out how different languages stimulate different neurological senses for …

Perception Is Reality?, Madeline Henson, Taimur Iftikhar

Student Symposium

Related presentation in Panel 1A: Brain Games

Surfaces Of Revolution In Virtual Reality, Joshua Harris

Undergraduate Research Conference

Why is this project needed?

❑ Surfaces of Revolution is many student’s first experience with three dimensional mathematical objects.

❑ The calculations required are not the inhibitor of the student’s understanding.

❑ Visualization of these solids along with the appropriate set up are the greatest hindrance to a deep under-standing of surfaces of revolution.

❑ Other tools that create computer generated visualizations of surfaces and curves in space render them as two-dimensional projections of a three dimensional object.

❑ Other tools typically do not have the capabilities of guided instruction, exploration of concepts on carefully chosen examples, and the ability …

Data Parsing For Optimized Molecular Geometry Calculations, Luke Rens

Undergraduate Research Conference

The purpose of this project is to optimize and streamline to process of using ADF and ReaxFF. There is no efficient way to effectively add constraints to a compound and run it through ADF, take the ADF output and create a file that can be run through Reaxff, then take that Reaxff output and come to conclusions on it. To streamline this process, scripts were developed using Python to parse information out of data generated by ADF.

Safety And Security With Aadl: Using Lattices To Model Data Flow, Erick Martinez

Kansas State University Undergraduate Research Conference

Architecture and Design Language is a model based engineering language that is used to create safety-critical systems. The issue with the creation of these systems is the lack of importance in security when these systems are created. To improve and promote the increase if importance and reliability for the creation of these systems we are looking into creating a method in which we can create lattice formations to identify and restrict certain information to its own category/classification. Lattices form sets of nodes that can be restricted so that certain information can only be distributed between two nodes that have the …

Wearing The Inside Out: Using Long Short-Term Memory Networks And Wearable Data To Identify Human Emotions, Carlos Aguirre, Maria Fernanda De La Torre

Kansas State University Undergraduate Research Conference

Studying emotions may sound unusual in computer science, a field based on quantifiable data and rationality. Contrary to belief, studies have shown any decision is highly dependent on emotional input. To improve human-computer interaction, it is crucial to improve our understanding of human emotions and teach machines to identify them. With large amounts of information streaming available from our environment, identifying our current emotional state becomes challenging, even at the individual self-level. This project aims to identify indicative emotional temporal data from wearable devices. Using brain activity data from an EEG and smart watches that record data, such as heart-beat, …

How Middle School Boys From Underrepresented Communities Perceive Computer Science And Computer Science Careers, Cristal Kelly

Undergraduate Research at FIU (URFIU) Conference

Computer science (CS) as a field is characterized by significant disparities in the representation of people groups from minority populations. In this phenomenological study we sought to understand how middle school boys from minority groups perceive CS and related careers with the goal of identifying the factors that contribute to their career intentions. Specifically we sought to answer the following questions: How are salient factors reported by middle school boys related to CS career aspirations associated with their cultural values? How do perceived barriers shape their career intentions? And how do high CS interest and negative perceptions interact to affect …