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After freelancing on my own for the past year and a half, I have realized that one of the biggest obstacles to college entrepreneurs is a fear or apprehension to sales. As a computer science major trying to sell my services, I discovered very quickly that I had not been

After freelancing on my own for the past year and a half, I have realized that one of the biggest obstacles to college entrepreneurs is a fear or apprehension to sales. As a computer science major trying to sell my services, I discovered very quickly that I had not been prepared for the difficulty of learning sales. Sales get a bad rap and very often is the last thing that young entrepreneurs want to try, but the reality is that sales is oxygen to a company and a required skill for an entrepreneur. Due to this, I compiled all of my knowledge into an e-book for young entrepreneurs starting out to learn how to open up a conversation with a prospect all the way to closing them on the phone. Instead of starting from scratch like I did, college entrepreneurs can learn the bare basics of selling their own services, even if they are terrified of sales and what it entails. In this e-book, there are tips that I have learned to deal with my anxiety about sales such as taking the pressure off of yourself and prioritizing listening more than pitching. Instead of trying to teach sales expecting people to be natural sales people, this e-book takes the approach of helping entrepreneurs that are terrified of sales and show them how they can cope with this fear and still close a client. In the future, I hope young entrepreneurs will have access to more resources that handle this fear and make it much easier for them to learn it by themselves. This e-book is the first step.
ContributorsMead, Kevin Tyler (Author) / Sebold, Brent (Thesis director) / Kruse, Gabriel (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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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
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
Description
What if unplanned free time could be spent with friends instead of trying to contact them? This app will do that by connecting you with friends who are ready to hang out. Kickback is a mobile app designed to connect individuals with their friends and businesses that offer opportunities to

What if unplanned free time could be spent with friends instead of trying to contact them? This app will do that by connecting you with friends who are ready to hang out. Kickback is a mobile app designed to connect individuals with their friends and businesses that offer opportunities to socialize in a group setting. The idea had been floating around in my head for a few years and this creative project gave me the opportunity to try my hand at making the idea into a reality. This thesis is a combination of technical efforts and business know-how that I had to learn in order to keep up along the way.
ContributorsFegard, Nathan (Author) / Sebold, Brent (Thesis director) / Trujillo, Rhett (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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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
The main objective of this thesis is to describe and analyze Clippr, an ASU startup founded by four students: Adam Lynch, Eric Gottfried, Ty Sivley, and Thomas Carpaneto. This paper will describe the formation of Clippr as a business, analyze the work and reasoning for dissolving the business, and suggest

The main objective of this thesis is to describe and analyze Clippr, an ASU startup founded by four students: Adam Lynch, Eric Gottfried, Ty Sivley, and Thomas Carpaneto. This paper will describe the formation of Clippr as a business, analyze the work and reasoning for dissolving the business, and suggest three pivots that could increase the chances of success for the future of Clippr. These three pivots are: mini salons, a concierge service, and an online resource. The idea for Clippr came from Sam, the team's friend's experience within the cosmetology industry. Sam graduated from cosmetology school in Phoenix and started his career as an assistant, which is the most common entry level position within the industry. Assistants do not get to work with clients and primarily do chores around the salon so he was not gaining any valuable experience. Eventually Sam found a position at a salon in Flagstaff. Unfortunately, he was not scheduled enough hours to pay his rent which forced him to travel back to Phoenix to cut his friend's and family's hair to make ends meet. Sam is not alone experiencing these issues within the industry, they are a common trend throughout the cosmetology field. It was found that there is a clear problem that affects every stylist: they struggle to reap the benefits of their self-employment. Most stylists become independent contractors where they are constrained by the salon's management. They are generally forced to work during the salon's hours of operations, promote specific products, adhere to a dress code, and forfeit their clients information. On the other hand, freelance workers outside of salons do enjoy greater freedoms within their work but with significant hurdles to overcome. They have a much harder time building a client base and face prohibitive start-up costs that make it harder to break into the industry.
ContributorsGottfried, Eric (Co-author) / Lynch, Adam (Co-author) / Sebold, Brent (Thesis director) / Balasooriya, Janaka (Committee member) / Computer Science and Engineering Program (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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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
Description

The NCAA is changing the current rules and regulations around a student-athlete’s name, image, and likeness. Previously, student-athletes were not allowed to participate in business activities or noninstitutional promotional activities. With the new rule changes, student-athletes will be able to engage in business activities related to their own name, image,

The NCAA is changing the current rules and regulations around a student-athlete’s name, image, and likeness. Previously, student-athletes were not allowed to participate in business activities or noninstitutional promotional activities. With the new rule changes, student-athletes will be able to engage in business activities related to their own name, image, and likeness. The goal of the team was to help “prepare athletes to understand and properly navigate the evolving restrictions and guidelines around athlete name, image, and likeness”. In order to accomplish this, the team had to understand the problems student-athletes face with these changing rules and regulations. The team conducted basic market research to identify the problem. The problem discovered was the lack of communication between student-athletes and businesses. In order to verify this problem, the team conducted several interviews with Arizona State University Athletic Department personnel. From the interviews, the team identified that the user is the student-athletes and the buyer is the brands and businesses. Once the problem was verified and the user and buyer were identified, a solution that would best fit the customers was formulated. The solution is a platform that assists student-athletes navigate the changing rules of the NCAA by providing access to a marketplace optimized to working with student-athletes and offering an ease of maintaining relationships between student-athletes and businesses. The solution was validated through meetings with interested brands. The team used the business model and market potential to pitch the business idea to the brands. Finally, the team gained traction by initiating company partnerships.

ContributorsSchulte, Brooke (Co-author) / Recato, Bella (Co-author) / Winston, Blake (Co-author) / Byrne, Jared (Thesis director) / Lee, Christopher (Committee member) / Kunowski, Jeffrey (Committee member) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Obesity rates among adults have steadily grown in recent decades all the way up to<br/>42.4% in 2018. This is a 12% increase from the turn of the century (Center for Disease Control<br/>and Prevention, 2021). A major reason for this rise is increased consumption of processed,<br/>high-calorie foods. People eat these foods

Obesity rates among adults have steadily grown in recent decades all the way up to<br/>42.4% in 2018. This is a 12% increase from the turn of the century (Center for Disease Control<br/>and Prevention, 2021). A major reason for this rise is increased consumption of processed,<br/>high-calorie foods. People eat these foods at a young age and develop bad eating habits that can<br/>last for the rest of their lives. It is essential to intervene early and help adolescents form<br/>balanced, healthy eating habits before bad habits are already formed. Our solution to this<br/>problem is Green Gamers. Green Gamers combines adolescent’s passion for gaming with<br/>healthy eating via in-game rewards for healthy eating. People will be able to purchase healthy<br/>food items, such as a bag of carrots, and on the packaging there will be a QR code. They will<br/>then be able to scan the code on our website, and earn points which will unlock in-game items<br/>and other rewards. Video game rewards act as effective motivators for you people to eat more<br/>healthy foods. After the solution was formulated, a preliminary survey was conducted to<br/>confirm that video game related rewards would inspire children to eat more healthy foods.<br/>Based on those results, we are currently in the process of running a secondary market research<br/>campaign to learn if gift card rewards are a stronger motivator. Our end goal for Green Gamers<br/>would be to partner with large gaming studios and food producers. This would allow us access to<br/>many gaming franchises, so that rewards are available from a wide variety of games: making the<br/>platform appealing to a diverse audience of gamers. Similarly, a relationship with large food<br/>producers would give us the ability to place QR codes on a greater assortment of healthy food<br/>items. Although no relationships with large companies have been forged yet, we plan to utilize<br/>funding to test our concept on small focus groups in schools

ContributorsKim, Hwan (Co-author) / Wong, Brendan (Co-author) / Davis, Ben (Co-author) / Mckearney, Jack (Co-author) / Byrne, Jared (Thesis director) / Hall, Rick (Committee member) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

When examining the average college campus, it becomes obvious that students feel rushed from one place to another as they try to participate in class, clubs, and extracurricular activities. One way that students can feel more comfortable and relaxed around campus is to introduce the aspect of gaming. Studies show

When examining the average college campus, it becomes obvious that students feel rushed from one place to another as they try to participate in class, clubs, and extracurricular activities. One way that students can feel more comfortable and relaxed around campus is to introduce the aspect of gaming. Studies show that “Moderate videogame play has been found to contribute to emotional stability” (Jones, 2014). This demonstrates that the stress of college can be mitigated by introducing the ability to interact with video games. This same concept has been applied in the workplace, where studies have shown that “Gaming principles such as challenges, competition, rewards and personalization keep employees engaged and learning” (Clark, 2020). This means that if we manage to gamify the college experience, students will be more engaged which will increase and stabilize the retention rate of colleges which utilize this type of experience. Gaming allows students to connect with their peers in a casual environment while also allowing them to find resources around campus and find new places to eat and relax. We plan to gamify the college experience by introducing augmented reality in the form of an app. Augmented reality is “. . . a technology that combines virtual information with the real world” (Chen, 2019). College students will be able to utilize the resources and amenities available to them on campus while completing quests that help them within the application. This demonstrates the ability for video games to engage students using artificial tasks but real actions and experiences which help them feel more connected to campus. Our Founders Lab team has developed and tested an AR application that can be used to connect students with their campus and the resources available to them.

ContributorsRangarajan, Padmapriya (Co-author) / Klein, Jonathan (Co-author) / Li, Shimei (Co-author) / Byrne, Jared (Thesis director) / Pierce, John (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05