Physical Sciences and Mathematics Commons^™

Modeling And Visualization Of Uncertainty-Aware Geometries Using Multi-Variate Normal Distributions, Christina Gillman, Thomas Wischgoll, Bernd Hamann, James Ahrens

Computer Science and Engineering Faculty Publications

Many applications are dealing with geometric data that are affected by uncertainty. It is important to analyze, visualize, and understand the properties of uncertain geometry. We present a methodology to model uncertain geometry based on multi-variate normal distributions. In addition, we propose a visualization technique to represent a hull for uncertain geometry capturing a user-defined percentage of the underlying uncertain geometry. To show the effectiveness of our approach, we have modeled and visualized uncertain datasets from different applications.

Wright State University's Symposium Of Student Research, Scholarship & Creative Activities From Friday April 13, 2018, Wright State University

Symposium of Student Research, Scholarship, and Creative Activities Materials

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Symposium of Student Research, Scholarship & Creative Activities on April 13, 2018.

Usability Assessment For Caregiver Behavior Analysis Using Gaming Technology, Alexandrea C. Oliver, Tanvi Banerjee, Jennifer Hughes, Noah L. Schroeder

Computer Science and Engineering Faculty Publications

The proposed research focuses on developing a mobile application for Android systems that will detect changes in behavior and activity patterns of those who are primary caregivers for dementia patients. This application will be used to detect fluctuation in the behavior and the task performance of the caregivers as a measure of caregiver stress. By detecting these changes in behavior, the goal is to analyze the effects of caregiving to evaluate caregiver burnout. A usability study was conducted for this application to find the optimal design factors and features that benefit the target user: the caregiver.

The purpose of this …

An Uncertainty-Aware Workflow For Keyhole Surgery Planning Using Hierarchical Image Semantics, Christina Gillmann, Robin G.C. Maack, Tobias Post, Thomas Wischgoll, Hans Hagen

Computer Science and Engineering Faculty Publications

Keyhole surgeries become increasingly important in clinical daily routine as they help minimizing the damage of a patient's healthy tissue. The planning of keyhole surgeries is based on medical imaging and an important factor that influences the surgeries' success. Due to the image reconstruction process, medical image data contains uncertainty that exacerbates the planning of a keyhole surgery. In this paper we present a visual workfiow that helps clinicians to examine and compare different surgery paths as well as visualizing the patients' affected tissue. The analysis is based on the concept of hierarchical image semantics, that segment the underlying image …

Trust In Visualization (And What It Has To Do With Theory), Thomas Wischgoll

Computer Science and Engineering Faculty Publications

There are different issues with trust involved when working with domain experts to visualize their data. There may be limitations with the data that require special precautions, such as sensitivity or security limitations. It may have taken a lot of effort to collect or create the data so that a certain level of trust is required for the domain expert to share the data. At the same time, the domain expert needs to be able to trust in the final visualization results. This presentation discusses these issues with trust and what requirements for a theoretical foundation this results in. Furthermore, …

Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena

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Domain knowledge plays a significant role in powering a number of intelligent applications such as entity recommendation, question answering, data analytics, and knowledge discovery. Recent advances in Artificial Intelligence and Semantic Web communities have contributed to the representation and creation of this domain knowledge in a machine-readable form. This has resulted in a large collection of structured datasets on the Web which is commonly referred to as the Web of data. The Web of data continues to grow rapidly since its inception, which poses a number of challenges in developing intelligent applications that can benefit from its use. Majority of …

Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon

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Goals can be described as the user's desired state of the agent and the world and are satisfied when the agent and the world are altered in such a way that the present state matches the desired state. For physical agents, they must act in the world to alter it in a series of individual atomic actions. Traditionally, agents use planning to create a chain of actions each of which altering the current world state and yielding a new one until the final action yields the desired goal state. Once this goal state has been achieved, the goal is said …

Visual Analytics Of Cascaded Bottlenecksin Planar Flow Networks, Tobias Post, Thomas Wischgoll, Bernd Hamann, Hans Hagen

Computer Science and Engineering Faculty Publications

Finding bottlenecks and eliminating them to in-crease the overall flow of a network often appears in real world applications, such as production planning, factory layout, flowrelated physical approaches, and even cyber security. In many cases, several edges can form a bottleneck (cascaded bottlenecks). This work presents a visual analytics methodology to analyze these cascaded bottlenecks. The methodology consists of multiple steps: identification of bottlenecks, identification of potential improvements, communication of bottlenecks, interactive adaption of bottlenecks, and a feedback loop that allows users to adapt flow networks and their resulting bottlenecks until they are satisfied with the flow network configuration. To …

Comparing And Enhancing The Analytical Model For Exposure Of A Retail Facility Layout With Human Performance, Bradley R. Guthrie, Pratik Parikh, Tyler Whitlock, Madison Glines, Thomas Wischgoll, John Flach, Scott Watamaniuk

Computer Science and Engineering Faculty Publications

Recent research in retail facility layout has focused on developing analytical models to estimate visibility measures of novel rack layouts based on assumptions about a shopper’s field of view. However, because of the human element involved in the shopping experience, it is vital to compare these models relative to actual human performance. In this study, we evaluate the predictions of our previously developed analytical model (that estimates exposure of every location on a given rack layout assuming expected head movement) in a 3D Virtual Environment (VE). We conducted trials with 18 participants who were asked to find targets strategically placed …

Towards An Image-Based Indicator For Pad Classification And Localization, Christina Gillmann, Johh H. Matsuura, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Peripheral Artery Disease (PAD) is an often occurring problem caused by narrowed veins. With this type of disease, mostly the legs receive an insufficient supply of blood to sustain their functions. This can result in an amputation of extremities or strokes. In order to quantify the risks, doctors onsult a classification table which is based on the pain response of a patient. This classification is subjective and does not indicate the exact origin of the PAD symptoms. Resulting from this, complications can occur unprompted. We present the first results for an image-based indicator assisting medical doctors in estimating the stage …

An Uncertainty-Aware Visual System For Image Pre-Processing, Christina Gillmann, Pablo Arbelaez, Jose Tiberio Hernandez, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Due to image reconstruction process of all image capturing methods, image data is inherently affected by uncertainty. This is caused by the underlying image reconstruction model, that is not capable to map all physical properties in its entirety. In order to be aware of these effects, image uncertainty needs to be quantified and propagated along the entire image processing pipeline. In classical image processing methodologies, pre-processing algorithms do not consider this information. Therefore, this paper presents an uncertainty-aware image pre-processing paradigm, that is aware of the input image’s uncertainty and propagates it trough the entire pipeline. To accomplish this, we …

A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla

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In recent times, social media platforms like Twitter have become more popular and people have become more interactive and responsive than before. People often react to every news in real-time and within no-time, the information spreads rapidly. Even with viral diseases like Zika, people tend to share their opinions and concerns on social media. This can be leveraged by the health officials to track the disease in real-time thereby reducing the time lag due to traditional surveys. A faster and accurate detection of the disease can allow health officials to understand people's opinion of the disease and take necessary precautions …

Caregiver Assessment Using Smart Gaming Technology: A Preliminary Approach, Garrett Goodman, Tanvi Banerjee, William Romine, Cogan Shimizu, Jennifer Hughes

Computer Science and Engineering Faculty Publications

As pre-diagnostic technologies are becoming increasingly accessible, using them to improve the quality of care available to dementia patients and their caregivers is of increasing interest. Specifically, we aim to develop a tool for non- invasively assessing task performance in a simple gaming application. To address this, we have developed Caregiver Assessment using Smart Technology (CAST), a mobile application that personalizes a traditional word scramble game. Its core functionality uses a Fuzzy Inference System (FIS) optimized via a Genetic Algorithm (GA) to provide customized performance measures for each user of the system. With CAST, we match the relative level of …

Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios

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One of the challenges of our society is the existence of chronic-related conditions and diseases among the elderly and people at risk. Apart from the welfare of people, a significant impact of this phenomenon is the accumulation of high financial costs for both individuals and health care systems. In order to address this issue and to reduce its effects, many efforts have been made towards preventing, identifying in early stages and, generally, managing chronic-related medical conditions and diseases. As a result, there has been a keen research and market interest in health monitoring devices during the past few decades. Nevertheless, …

Implementation Of Unmanned Aerial Vehicles Reporting Plume Cloud Concentration Values In A 3d Simulation Environment, Emily Catherine Novak

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Unmanned aerial vehicles, or UAVs, have the potential to vastly improve plume cloud tracking at low cost. Plume clouds can be produced from blast mining, chemical warfare, unintended man-made disasters, and natural causes. This thesis provides implementation of the capability to simulate a 3D environment in which UAVs are individually controlled and each report a plume's concentration value at a specific location. It leverages existing industry standard technologies, including the PX4 autopilot system, the Gazebo simulation environment, the Robot Operating System (ROS), and QGroundControl. The provided system integrates the existing tools with a plume model plug-in that provides simulated plume …

A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne

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Pictographs, commonly referred to as `emoji’, have become a popular way to enhance electronic communications. They are an important component of the language used in social media. With their introduction in the late 1990’s, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. In 2015, Instagram reported that nearly half of the photo comments posted on Instagram contain emoji, and in the same year, Twitter reported that the `face with tears of joy’ emoji has been tweeted 6.6 …

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

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Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves …

Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff

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Mindfulness is the state of retaining awareness of what is happening at the current point in time. It has been used in multiple forms to reduce stress, anxiety, and even depression. Promoting Mindfulness can be done in various ways, but current research shows a trend towards preferential usage of breathing exercises over other methods to reach a mindful state. Studies have showcased that breathing can be used as a tool to promote brain control, specifically in the auditory cortex region. Research pertaining to disorders such as Tinnitus, the phantom awareness of sound, could potentially benefit from using these brain control …

Developing A Kinect Based Holoportation System, Soumya Chiday

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Holographic communication and distributed collaboration offer great potential for empathic computing to help remove the cost, distance, language and expertise barriers in many social and economic activities. Recent advances in AR-enhanced communication as evident by Microsoft Holoportation technology demonstrate the progress toward fully immersive collaborations distributed and remotely. Current holoportation system requires the use of extensive camera-arrays and powerful server system due to the computation demand and sensory needs to capture and reconstruct the subject of interests Thus, they suffer in mobility and applicability in real-world scenarios. In this thesis, we present an ultra-portable holoportation system design that requires only …

Wetting Properties Of Structured Interfaces Composed Of Surface-Attached Spherical Nanoparticles, Bishal Bhattarai

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In this thesis, the effects of the external pressure and surface energy on stability and wetting transition at nanotextured interfaces are studied using molecular dynamics and continuum simulations. The surface roughness of the composite interface is modeled via an array of spherical nanoparticles with controlled wettability. It was found that in the absence of external pressure, the liquid interface is flat and its location relative to the solid substrate is determined by the radius of the particle and the local contact angle. With increasing pressure on the liquid film, its interface becomes more curved and the three-phase contact line is …

Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson

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When presented with many search results, finding information or patterns within the data poses a challenge. This thesis presents the design, implementation and evaluation of a visualization enabling users to browse through voluminous information and comprehend the data. Implemented with the JavaScript library Data Driven Documents (D3), the visualization represents the search as clusters of similar documents grouped into bubbles with the contents depicted as word-clouds. Highly interactive features such as touch gestures and intuitive menu actions allow for expeditious exploration of the search results. Other features include drag-and-drop functionality for articles among bubbles, merging nodes, and refining the search …

Development Of A Human-Ai Teaming Based Mobile Language Learning Solution For Dual Language Learners In Early And Special Educations, Saurabh Shukla

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Learning English as a secondary language is often an overwhelming challenge for dual language learners (DLLs), whose first language (L1) is not English, especially for children in early education (PreK-3 age group). These early DLLs need to devote a considerable amount of time learning to speak and read the language, in order to gain the language proficiency to function and compete in the classroom. Fear of embarrassment when mispronouncing words in front of others may drive them to remain silent; effectively hampering their participation in the class and overall curricular growth. The process of learning a new language can benefit …

Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff

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As the Internet continues to replace the brick-and-mortar store as the main place for purchasing goods, web-based companies are looking for ways to reduce the cost of delivering those goods. The use of Unmanned Aerial Vehicles, or UAVs, is one delivery method that is increasingly being used. These UAVs can be programmed with delivery routes and destinations and can complete the job while requiring limited intervention from human controllers. Sense and Avoidance (SAA) systems have recently been incorporated into these UAVs so that they can detect objects in their flight path, reroute the UAV accordingly and operate even more autonomously. …

Multiple Drone Detection And Acoustic Scene Classification With Deep Learning, Hari Charan Vemula

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Classification of environmental scenes and detection of events in one's environment from audio signals enables one to create better-planning agents, intelligent navigation systems, pattern recognition systems, and audio surveillance systems. This thesis will explore the use of Convolutional Neural Networks(CNN'S) with spectrograms and raw audio waveforms as inputs to Deep Neural Networks with hand engineered features extracted from large-scale feature extraction schemes to identify the acoustic scenes and events. The first part focuses on building an audio pattern recognition system capable of detecting the if there are zero, one, or two DJI phantoms in the scene within the range of …

Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally

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Augmented Reality (AR) places virtual contents along with real objects to enhance user perception in the physical environment. It is a technology that has shown great potential in many industries such as medicine, education and transportation. AR devices, such as Microsoft HoloLens, come with multi-modal interaction capabilities, such as voice, gesture and gaze, to support intuitive and reliable human-computer interactions. However, HoloLens gesture support is limited to simple gestures like tap, bloom and hold, it stops short to support meaningful interaction through full hand gesture and motion tracking, which may be critical in field operations of various industry practices in …

Using Natural Language Processing And Machine Learning For Analyzing Clinical Notes In Sickle Cell Disease Patients, Shufa Khizra

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Sickle Cell Disease (SCD) is a hereditary disorder in red blood cells that can lead to excruciating pain episodes. SCD causes the normal red blood cells to distort its shape and turn into sickle shape. The distorted shape makes the hemoglobin inflexible and stick to the walls of the vessels thereby obstructing the free flow of blood and eventually making the tissues suffer from lack of oxygen. The lack of oxygen causes serious problems including Acute Chest Syndrome (ACS), stroke, infection, organ damage, and over the lifetime an SCD can harm a persons spleen, brain, kidneys, eyes, bones. Sickling of …

Multi-Scale And Multi-Modal Streaming Data Aggregation And Processing For Decision Support During Natural Disasters, Shruti Kar

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With the surge in digital information systems, there is a data deluge from various sources that can be analyzed and integrated to produce relevant, reliable and actionable information, for better decision making. We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for an aggregate level analysis and location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood …

Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman

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Due to current market forces, leading-edge semiconductor fabrication plants have moved outside of the US. While this is not a problem at first glance, when it comes to security-sensitive applications, over-production, device cloning, or design alteration becomes a possibility. Since these vulnerabilities exist during the fabrication phase, a Reverse Engineering (RE) step must be introduced to help ensure secure device operation. This thesis proposes several unique methods and a collection of tools to ensure trust assurance in integrated circuit design by detecting fabrication flaws and possible hardware Trojans using several image processing techniques; fused into a singular view of the …

Verifying Data-Oriented Gadgets In Binary Programs To Build Data-Only Exploits, Zachary David Sisco

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Data-Oriented Programming (DOP) is a data-only code-reuse exploit technique that "stitches" together sequences of instructions to alter a program's data flow to cause harm. DOP attacks are difficult to mitigate because they respect the legitimate control flow of a program and by-pass memory protection schemes such as Address Space Layout Randomization, Data Execution Prevention, and Control Flow Integrity. Techniques that describe how to build DOP payloads rely on a program's source code. This research explores the feasibility of constructing DOP exploits without source code-that is, using only binary representations of programs. The lack of semantic and type information introduces difficulties …

A Model For Seasonal Dynamic Networks, Jace D. Robinson

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Sociotechnological and geospatial processes exhibit time varying structure that make insight discovery challenging. This paper presents statistical model of systems with seasonal dynamics, modeled as a dynamic network, to address this challenge. It assumes the probability of edge formations depend on a type assigned to incident nodes and the current time. Time dependencies are modeled by unique seasonal processes. The model is studied on several synthetic and real datasets. Superior fidelity of this model on seasonal datasets compared to existing network models, while being able to remain equally accurate for networks with randomly changing structure, is shown. The model is …