Matching Items (42)

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Input-Elicitation Methods for Crowdsourced Human Computation

Description

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task is created that aims
to determine ground-truth by collecting information in
two different ways: rankings and numerical estimates.
Results indicate that accurate collective decisions can
be achieved with less people when ordinal and cardinal
information is collected and aggregated together
using consensus-based, multimodal models. We also
show that presenting users with larger problems produces
more valuable ordinal information, and is a more
efficient way to collect an aggregate ranking. As a result,
we suggest input-elicitation to be more widely considered
for future work in crowdsourcing and incorporated
into future platforms to improve accuracy and efficiency.

Contributors

Agent

Created

Date Created
2020-05

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Supplemental Tool For Hebrew Courses

Description

This project serves as an extra learning tool for students enrolled in HEB 101 (Hebrew) at Arizona State University. This tool was developed using Axure Prototyping Software and can be used by anyone. The tool follows the HEB 101 course

This project serves as an extra learning tool for students enrolled in HEB 101 (Hebrew) at Arizona State University. This tool was developed using Axure Prototyping Software and can be used by anyone. The tool follows the HEB 101 course curriculum which also works alongside the textbook for the class (Hebrew From Scratch part 1). The tool fully covers the seven units that students learn in HEB 101. Each unit follows a standard structure. There is a unit title page which lays out the major concepts covered in the unit (i.e. personal pronouns, question words, prepositions, etc.) and links to different pages within the unit. Each unit has seven to ten lesson pages which introduce Hebrew concepts and provide exercises and examples to help the students practice the material they learned both in class and in the tool. Each unit also has links to Quizlet pages that have the units' vocab set up in a flashcard format so that they can study for upcoming quizzes and exams in the class. The Quizlet page for each unit also provides a randomly generated vocab quiz for the students. There is also a unit quiz for every unit which tests the students on the major concepts of the unit. There are also unit vocab pages that provide all the vocab covered in the unit. This tool provides students with numerous ways of practicing and mastering the material covered in the lectures. The main benefit of this tool for students is that it provides audio files for each vocabulary word learned in HEB 101 which will allow them to have quick access to the pronunciation of the words they are learning. This tool will be used in future HEB 101 classes.

Contributors

Agent

Created

Date Created
2018-05

Behavior Trees + Finite State Machines: A Hybrid Game AI Framework

Description

One of the core components of many video games is their artificial intelligence. Through AI, a game can tell stories, generate challenges, and create encounters for the player to overcome. Even though AI has continued to advance through the implementation

One of the core components of many video games is their artificial intelligence. Through AI, a game can tell stories, generate challenges, and create encounters for the player to overcome. Even though AI has continued to advance through the implementation of neural networks and machine learning, game AI tends to implement a series of states or decisions instead to give the illusion of intelligence. Despite this limitation, games can still generate a wide range of experiences for the player. The Hybrid Game AI Framework is an AI system that combines the benefits of two commonly used approaches to developing game AI: Behavior Trees and Finite State Machines. Developed in the Unity Game Engine and the C# programming language, this AI Framework represents the research that went into studying modern approaches to game AI and my own attempt at implementing the techniques learned. Object-oriented programming concepts such as inheritance, abstraction, and low coupling are utilized with the intent to create game AI that's easy to implement and expand upon. The final goal was to create a flexible yet structured AI data structure while also minimizing drawbacks by combining Behavior Trees and Finite State Machines.

Contributors

Created

Date Created
2018-05

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Procedural Scene Generation from Natural Language

Description

While there are many existing systems which take natural language descriptions and use them to generate images or text, few systems exist to generate 3d renderings or environments based on natural language. Most of those systems are very limited in

While there are many existing systems which take natural language descriptions and use them to generate images or text, few systems exist to generate 3d renderings or environments based on natural language. Most of those systems are very limited in scope and require precise, predefined language to work, or large well tagged datasets for their models. In this project I attempt to apply concepts in NLP and procedural generation to a system which can generate a rough scene estimation of a natural language description in a 3d environment from a free use database of models. The primary objective of this system, rather than a completely accurate representation, is to generate a useful or interesting result. The use of such a system comes in assisting designers who utilize 3d scenes or environments for their work.

Contributors

Created

Date Created
2019-05

LeapMax: Gestural Interaction System

Description

The LeapMax Gestural Interaction System is a project which utilizes the Leap Motion controller and visual programming language Max to extract complex and accurate skeletal hand tracking data from a performer in a global 3-D context. The goal of this

The LeapMax Gestural Interaction System is a project which utilizes the Leap Motion controller and visual programming language Max to extract complex and accurate skeletal hand tracking data from a performer in a global 3-D context. The goal of this project was to develop a simple and efficient architecture for designing dynamic and compelling digital gestural interfaces. At the core of this work is a Max external object which uses a custom API to extract data from the Leap Motion service and retrieve it in Max. From this data, a library of Max objects for determining more complex gesture and posture information was generated and refined. These objects can be are highly flexible and modular and can be used to create complex control schemes for a variety of systems. To demonstrate the use of this system in a performance context, an experimental musical instrument was designed in which the Leap is combined with an absolute orientation sensor and mounted on the head of a performer. This setup leverages the head mounted Leap Motion paradigm used in VR systems to construct an interactive sonic environment within the context of the user's environment. The user's gestures are mapped to the controls of a synthesis engine which utilizes several forms of synthesis including granular synthesis, frequency modulation, and delay modulation.

Contributors

Agent

Created

Date Created
2018-12

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Instructional Design with Natural Language Processing in a Virtual Reality Environment

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

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.

Contributors

Agent

Created

Date Created
2018-05

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Understanding Informal to Formal Comparisons and Proof Comprehension: a Replication Study

Description

This study sought to replicate previous work in student conceptions of formal proofs based on informal arguments, originally explored by Zazkis et al. (2016). Additional tasks were added to the experiment to produce new data that could further verify the

This study sought to replicate previous work in student conceptions of formal proofs based on informal arguments, originally explored by Zazkis et al. (2016). Additional tasks were added to the experiment to produce new data that could further verify the analysis of Zazkis et al. (2016) as well as provide more insight into how students comprehend proofs, what types of mistakes occur, and why. Results from one-on-one interviews confirmed that some students were not able to make accurate informal to formal comparisons because they were not considering multiple facets of the problem. Additionally, patterns in the students’ analysis introduced more questions concerning the motivations behind what students choose to think about when they read and dissect proofs.

Contributors

Agent

Created

Date Created
2020-05

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Speech Events in Online Fanfiction

Description

This study observes two fanfiction speech communities, Danny Phantom and Detective Conan. The members of these communities write stories based upon the canon within these two animated cartoons and interact with one another through reviews, author's notes, and story summaries.

This study observes two fanfiction speech communities, Danny Phantom and Detective Conan. The members of these communities write stories based upon the canon within these two animated cartoons and interact with one another through reviews, author's notes, and story summaries. Using the speech community model, this community's unique practices and communicative repertoire will be identified and analyzed. Both of these fandoms show similarities with the overarching general fanfiction speech community, but they also possess key differences that define them as their own separate community. Fan jargon is used frequently in author's notes, reviews, and summaries to indicate fan expertise and membership within the fandom as well as exclude newcomers from understanding the information. This jargon remains largely the same across languages, and using it properly is important to being considered a true fan. Furthermore, many stories share similar elements that are not present within the source material, indicating that the fandoms possess a shared communicative repertoire. Review practices also show strong cultural norms that demand that reviewers offer praise and encouragement to the writers. Most criticism is phrased extremely kindly to avoid breaking cultural norms. Those who do not follow these cultural norms are shunned by the community, and required to apologize to maintain proper fan membership. Fan hierarchy is also examined, including the ways that big name fans and reviewers exert centripetal and centrifugal forces upon the language, simultaneously pushing it towards standardization and variation. Authors also use many face saving techniques to demonstrate their own lack of knowledge within the community, especially if they are new or inexperienced. The members of these communities share a deep cultural connection that is strengthened by their practices and repertoires.

Contributors

Agent

Created

Date Created
2017-05

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Improving the Valley Fever Gene Annotation Through Proteogenomic Analysis

Description

Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation

Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation efforts are also hampered by incomplete genome sequencing. We intend to use proteogenomic analysis to reannotate the Coccidioides posadasii str. Silveira genome from protein-level data. Protein samples extracted from both phases of Silveira were fragmented into peptides, sequenced, and compared against databases of known and predicted proteins sequences, as well as a de novo six-frame translation of the genome. 288 unique peptides were located that did not match a known Silveira annotation, and of those 169 were associated with another Coccidioides strain. Additionally, 17 peptides were found at the boundary of, or outside of, the current gene annotation comprising four distinct clusters. For one of these clusters, we were able to calculate a lower bound and an estimate for the size of the gap between two Silveira contigs using the Coccidioides immitis RS transcript associated with that cluster's peptides \u2014 these predictions were consistent with the current annotation's scaffold structure. Three peptides were associated with an actively translated transposon, and a putative active site was located within an intact LTR retrotransposon. We note that gene annotation is necessarily hindered by the quality and level of detail in prior genome sequencing efforts, and recommend that future studies involving reannotation include additional sequencing as well as gene annotation via proteogenomics or other methods.

Contributors

Agent

Created

Date Created
2016-12

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Development of an Educational Video Game

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

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.

Contributors

Created

Date Created
2017-05