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Description
This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can

This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can be used to understand the image better through recognizing different features present within the image. Deep CNNs, however, require training sets that can be larger than a million pictures in order to fine tune their feature detectors. For the case of facial expression datasets, none of these large datasets are available. Due to this limited availability of data required to train a new CNN, the idea of using naïve domain adaptation is explored. Instead of creating and using a new CNN trained specifically to extract features related to FER, a previously trained CNN originally trained for another computer vision task is used. Work for this research involved creating a system that can run a CNN, can extract feature vectors from the CNN, and can classify these extracted features. Once this system was built, different aspects of the system were tested and tuned. These aspects include the pre-trained CNN that was used, the layer from which features were extracted, normalization used on input images, and training data for the classifier. Once properly tuned, the created system returned results more accurate than previous attempts on facial expression recognition. Based on these positive results, naïve domain adaptation is shown to successfully leverage advantages of deep CNNs for facial expression recognition.
ContributorsEusebio, Jose Miguel Ang (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
This paper details the process for designing both a simulation of the board game Jaipur, and an artificial intelligence (AI) agent that can play the game against a human player. When designing an AI for a card game, there are two major problems that can arise. The first is the

This paper details the process for designing both a simulation of the board game Jaipur, and an artificial intelligence (AI) agent that can play the game against a human player. When designing an AI for a card game, there are two major problems that can arise. The first is the difficulty of using a search space to analyze every possible set of future moves. Due to the randomized nature of the deck of cards, the search space rapidly leads to an exponentially growing set of potential game states to analyze when one tries to look more than one turn ahead. The second aspect that poses difficulty is the element of uncertainty that exists from opponent feedback. Certain moves are weak to specific opponent reactions, and these are difficult to predict due to hidden information. To circumvent these problems, the AI uses a greedy approach to decision making, attempting to maximize the value of its plays immediately, and not play for future turns. The agent utilizes conditional statements to evaluate the game state and choose a game action that it deems optimal, a heuristic to place an expected value (EV) of the goods it can choose from, and selects the best one based on this evaluation. Initial implementation of the simulation was done using C++ through a terminal application, and then was translated to a graphical interface using Unity and C#.
ContributorsOrr, James Christopher (Author) / Kobayashi, Yoshihiro (Thesis director) / Selgrad, Justin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
The objective of this creative project was to gain experience in digital modeling, animation, coding, shader development and implementation, model integration techniques, and application of gaming principles and design through developing a professional educational game. The team collaborated with Glendale Community College (GCC) to produce an interactive product intended to

The objective of this creative project was to gain experience in digital modeling, animation, coding, shader development and implementation, model integration techniques, and application of gaming principles and design through developing a professional educational game. The team collaborated with Glendale Community College (GCC) to produce an interactive product intended to supplement educational instructions regarding nutrition. The educational game developed, "Nutribots" features the player acting as a nutrition based nanobot sent to the small intestine to help the body. Throughout the game the player will be asked nutrition based questions to test their knowledge of proteins, carbohydrates, and lipids. If the player is unable to answer the question, they must use game mechanics to progress and receive the information as a reward. The level is completed as soon as the question is answered correctly. If the player answers the questions incorrectly twenty times within the entirety of the game, the team loses faith in the player, and the player must reset from title screen. This is to limit guessing and to make sure the player retains the information through repetition once it is demonstrated that they do not know the answers. The team was split into two different groups for the development of this game. The first part of the team developed models, animations, and textures using Autodesk Maya 2016 and Marvelous Designer. The second part of the team developed code and shaders, and implemented products from the first team using Unity and Visual Studio. Once a prototype of the game was developed, it was show-cased amongst peers to gain feedback. Upon receiving feedback, the team implemented the desired changes accordingly. Development for this project began on November 2015 and ended on April 2017. Special thanks to Laura Avila Department Chair and Jennifer Nolz from Glendale Community College Technology and Consumer Sciences, Food and Nutrition Department.
ContributorsNolz, Daisy (Co-author) / Martin, Austin (Co-author) / Quinio, Santiago (Co-author) / Armstrong, Jessica (Co-author) / Kobayashi, Yoshihiro (Thesis director) / Valderrama, Jamie (Committee member) / School of Arts, Media and Engineering (Contributor) / School of Film, Dance and Theatre (Contributor) / Department of English (Contributor) / Computer Science and Engineering Program (Contributor) / Computing and Informatics Program (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description
Virtual reality gives users the opportunity to immerse themselves in an accurately
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of

Virtual reality gives users the opportunity to immerse themselves in an accurately
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of interactable virtual worlds (Wikipedia, “Virtual reality”). The many worlds of virtual reality are often expansive, colorful, and detailed. However, there is one great flaw among them- an emotion evoked in many users through the exploration of such worlds-loneliness.
The content in these worlds is impressive, immersive, and entertaining. Without other people to share in these experiences, however, one can find themselves lonely. Users discover a feeling that no matter how many objects and colors surround them in countless virtual worlds, every world feels empty. As humans are social beings by nature, they feel lost without a sense of human connection and human interaction. Multiplayer experiences offer this missing element into the immersion of virtual reality worlds. Multiplayer offers users the opportunity to interact with other live people in a virtual simulation, which creates lasting memories and deeper, more meaningful immersion.
ContributorsJorgensen, Caitlin Nicole (Co-author) / Jorgensen, Nicholas (Co-author) / Ehgner, Arnaud (Thesis director) / Selgrad, Justin (Committee member) / Graphic Information Technology (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Virtual reality gives users the opportunity to immerse themselves in an accurately
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of

Virtual reality gives users the opportunity to immerse themselves in an accurately
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of interactable virtual worlds (Wikipedia, “Virtual reality”). The many worlds of virtual reality are often expansive, colorful, and detailed. However, there is one great flaw among them- an emotion evoked in many users through the exploration of such worlds-loneliness.
The content in these worlds is impressive, immersive, and entertaining. Without other people to share in these experiences, however, one can find themselves lonely. Users discover a feeling that no matter how many objects and colors surround them in countless virtual worlds, every world feels empty. As humans are social beings by nature, they feel lost without a sense of human connection and human interaction. Multiplayer experiences offer this missing element into the immersion of virtual reality worlds. Multiplayer offers users the opportunity to interact with other live people in a virtual simulation, which creates lasting memories and deeper, more meaningful immersion.
ContributorsJorgensen, Nicholas Keith (Co-author) / Jorgensen, Caitlin Nicole (Co-author) / Selgrad, Justin (Thesis director) / Ehgner, Arnaud (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that,

Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
ContributorsNakhleh, Julia Blair (Author) / Srivastava, Siddharth (Thesis director) / Fainekos, Georgios (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Medical records are increasingly being recorded in the form of electronic health records (EHRs), with a significant amount of patient data recorded as unstructured natural language text. Consequently, being able to extract and utilize clinical data present within these records is an important step in furthering clinical care. One important

Medical records are increasingly being recorded in the form of electronic health records (EHRs), with a significant amount of patient data recorded as unstructured natural language text. Consequently, being able to extract and utilize clinical data present within these records is an important step in furthering clinical care. One important aspect within these records is the presence of prescription information. Existing techniques for extracting prescription information — which includes medication names, dosages, frequencies, reasons for taking, and mode of administration — from unstructured text have focused on the application of rule- and classifier-based methods. While state-of-the-art systems can be effective in extracting many types of information, they require significant effort to develop hand-crafted rules and conduct effective feature engineering. This paper presents the use of a bidirectional LSTM with CRF tagging model initialized with precomputed word embeddings for extracting prescription information from sentences without requiring significant feature engineering. The experimental results, run on the i2b2 2009 dataset, achieve an F1 macro measure of 0.8562, and scores above 0.9449 on four of the six categories, indicating significant potential for this model.
ContributorsRawal, Samarth Chetan (Author) / Baral, Chitta (Thesis director) / Anwar, Saadat (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Natural Language Processing and Virtual Reality are hot topics in the present. How can we synthesize these together in order to make a cohesive experience? The game focuses on users using vocal commands, building structures, and memorizing spatial objects. In order to get proper vocal commands, the IBM Watson API

Natural Language Processing and Virtual Reality are hot topics in the present. How can we synthesize these together in order to make a cohesive experience? The game focuses on users using vocal commands, building structures, and memorizing spatial objects. In order to get proper vocal commands, the IBM Watson API for Natural Language Processing was incorporated into our game system. User experience elements like gestures, UI color change, and images were used to help guide users in memorizing and building structures. The process to create these elements were streamlined through the VRTK library in Unity. The game has two segments. The first segment is a tutorial level where the user learns to perform motions and in-game actions. The second segment is a game where the user must correctly create a structure by utilizing vocal commands and spatial recognition. A standardized usability test, System Usability Scale, was used to evaluate the effectiveness of the game. A survey was also created in order to evaluate a more descriptive user opinion. Overall, users gave a positive score on the System Usability Scale and slightly positive reviews in the custom survey.
ContributorsOrtega, Excel (Co-author) / Ryan, Alexander (Co-author) / Kobayashi, Yoshihiro (Thesis director) / Nelson, Brian (Committee member) / Computing and Informatics Program (Contributor) / School of Art (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Last Hymn was created by the team of Tyler Pinho, Jefferson Le, and Curtis Spence with the desire to create an eccentric Role Playing Game focused on the exploration of a strange, dying world. Battles in the game are based off of rhythm games like Dance Dance Revolution using a

Last Hymn was created by the team of Tyler Pinho, Jefferson Le, and Curtis Spence with the desire to create an eccentric Role Playing Game focused on the exploration of a strange, dying world. Battles in the game are based off of rhythm games like Dance Dance Revolution using a procedural generation algorithm that makes every encounter unique. This is then complemented with the path system where each enemy has unique rhythm patterns to give them different types of combat opportunities. In Last Hymn, the player arrives on a train at the World's End Train Station where they are greeted by a mysterious figure and guided to the Forest where they witness the end of the world and find themselves back at the train station before they left for the Forest. With only a limited amount of time per cycle of the world, the player must constantly weigh the opportunity cost of each decision, and only with careful thought, conviction, and tenacity will the player find a conclusion from the never ending cycle of rebirth. Blending both Shinto architecture and modern elements, Last Hymn used a "fantasy-chic" aesthetic in order to provide memorable locations and dissonant imagery. As the player explores they will struggle against puzzles and dynamic, rhythm based combat while trying to unravel the mystery of the world's looping time. Last Hymn was designed to develop innovative and dynamic new solutions for combat, exploration, and mapping. From this project all three team members were able to grow their software development and game design skills, achieving goals like improved level design, improved asset pipelines while simultaneously aiming to craft an experience that will be unforgettable for players everywhere.
ContributorsPinho, Tyler (Co-author) / Le, Jefferson (Co-author) / Spence, Curtis (Co-author) / Nelson, Brian (Thesis director) / Walker, Erin (Committee member) / Kobayashi, Yoshihiro (Committee member) / Computer Science and Engineering Program (Contributor) / Computing and Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
Due to its difficult nature, organic chemistry is receiving much research attention across the nation to develop more efficient and effective means to teach it. As part of that, Dr. Ian Gould at ASU is developing an online organic chemistry educational website that provides help to students, adapts to their

Due to its difficult nature, organic chemistry is receiving much research attention across the nation to develop more efficient and effective means to teach it. As part of that, Dr. Ian Gould at ASU is developing an online organic chemistry educational website that provides help to students, adapts to their responses, and collects data about their performance. This thesis creative project addresses the design and implementation of an input parser for organic chemistry reagent questions, to appear on his website. After students used the form to submit questions throughout the Spring 2013 semester in Dr. Gould's organic chemistry class, the data gathered from their usage was analyzed, and feedback was collected. The feedback obtained from students was positive, and suggested that the input parser accomplished the educational goals that it sought to meet.
ContributorsBeerman, Eric Christopher (Author) / Gould, Ian (Thesis director) / Wilkerson, Kelly (Committee member) / Mosca, Vince (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05