Matching Items (15)
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- Creators: Computer Science and Engineering Program
- Creators: Economics Program in CLAS
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
Description
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
Description
The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and FLAC. Finally, the project is also to be driven by a mobile app running on a smartphone or tablet. To achieve this, a client server design was employed where the Raspberry Pi acts as the server and the mobile app is the client. The server functionality was achieved using a Python script that listens on a socket and calls various executables that handle the different formats of music being played. The client functionality was achieved by programming an Android app in Java that sends encoded commands to the server, which the server decodes and begins playing the music that command dictates. The designs for both the client and server are easily extensible and allow for any future modifications to the project to be easily made.
ContributorsStorto, Michael Olson (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Agent Based modeling has been used in computer science to simulate complex phenomena. The introduction of Agent Based Models into the field of economics (Agent Based Computational Economics ACE) is not new, however work on making model environments simpler to design for individuals without a background in computer science or computer engineering is a constantly evolving topic. The issue is a trade off of how much is handled by the framework and how much control the modeler has, as well as what tools exist to allow the user to develop insights from the behavior of the model. The solutions looked at in this thesis are the construction of a simplified grammar for model construction, the design of an economic based library to assist in ACE modeling, and examples of how to construct interactive models.
ContributorsAnderson, Brandon David (Author) / Bazzi, Rida (Thesis director) / Kuminoff, Nicolai (Committee member) / Roberts, Nancy (Committee member) / Computer Science and Engineering Program (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The rising age of the Baby Boomer generation has made a significant impact on the workforce, leaving leadership gaps that Generation X is unable to fill. This leaves an opportunity for the Millennial generation to step up and use their strengths and skills to become stronger leaders of the business and sales industry.
To bridge the gap between the growing sales industry there is the ability to properly train Millennials so they are successful and stay within their roles longer. By attacking this problem from a university level by strengthening sales programs as well as having employers understand and respond to needs of the Millennial generation, this will create an overall successful Millennial salesperson that will stay with their employer long term.
Strengths and weaknesses of this generation are also important to understand. Millennials are known to be tech-savvy, open-minded, collaborative, and connected, resourceful networkers. They also carry weaknesses and stereotypes of being lazy, lacking communication skills, impatient, entitled, and demanding of feedback and work flexibility. From an employer, they expect a large salary as well as a good culture, manager feedback, a mentor, work-life integration, an employer with a social responsibility mindset, and a sense of purpose.
An analysis of 12 sales programs at various universities across the country helped to understand what is being taught and offered to students as well as commonalities and differences that make a strong sales program. Commonalities among these programs include, about 250+ students, high job placement, sales labs, hosting and competing in sales competitions, and a desire to expand and grow their programs. Unique aspects of various programs were partnerships with the sales industry, hosting fundraisers, student ambassadors for the sales program, CRM courses, and internships and competition requirements.
Primary research was conducted to understand various sales development programs from companies in the sales industry. The 12 companies that participated in this research were from Arizona State University’s Sales Advisory Board. These companies completed a survey that provided detailed information of their onboarding and training process as well as their opinions of Millennial employees.
From this research, recommendations were formed for employers,
• creating a collaborative and innovative culture
• A mentorship program
• work flexibility
• continuous learning
• sense of purpose
As for Arizona State’s Sales Program, recommendations include,
• a mentorship program between Sales Scholars and the Sales Advisory Board
• creating a sales lab
• implementing CRM curriculum in classes
• continued support from the Board and alumni of the sales program
To bridge the gap between the growing sales industry there is the ability to properly train Millennials so they are successful and stay within their roles longer. By attacking this problem from a university level by strengthening sales programs as well as having employers understand and respond to needs of the Millennial generation, this will create an overall successful Millennial salesperson that will stay with their employer long term.
Strengths and weaknesses of this generation are also important to understand. Millennials are known to be tech-savvy, open-minded, collaborative, and connected, resourceful networkers. They also carry weaknesses and stereotypes of being lazy, lacking communication skills, impatient, entitled, and demanding of feedback and work flexibility. From an employer, they expect a large salary as well as a good culture, manager feedback, a mentor, work-life integration, an employer with a social responsibility mindset, and a sense of purpose.
An analysis of 12 sales programs at various universities across the country helped to understand what is being taught and offered to students as well as commonalities and differences that make a strong sales program. Commonalities among these programs include, about 250+ students, high job placement, sales labs, hosting and competing in sales competitions, and a desire to expand and grow their programs. Unique aspects of various programs were partnerships with the sales industry, hosting fundraisers, student ambassadors for the sales program, CRM courses, and internships and competition requirements.
Primary research was conducted to understand various sales development programs from companies in the sales industry. The 12 companies that participated in this research were from Arizona State University’s Sales Advisory Board. These companies completed a survey that provided detailed information of their onboarding and training process as well as their opinions of Millennial employees.
From this research, recommendations were formed for employers,
• creating a collaborative and innovative culture
• A mentorship program
• work flexibility
• continuous learning
• sense of purpose
As for Arizona State’s Sales Program, recommendations include,
• a mentorship program between Sales Scholars and the Sales Advisory Board
• creating a sales lab
• implementing CRM curriculum in classes
• continued support from the Board and alumni of the sales program
ContributorsQuinn, Jacklyn Michelle (Author) / Montoya, Detra (Thesis director) / Dietrich, John (Committee member) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Becoming good at selling is a nuanced skill. Many pivotal techniques are often not communicated properly in the training and onboarding phases, leaving many members of the sales force "crippled" before they even get into the field. We set out to discern the "best practices" of selling, and the underlying causes as to why they work. Through meticulous research obtained via study of experiments, sourced articles and other academic papers we compiled a thorough outline detailing the most efficient ways to build a relationship with the buyer and close the sale. From there we discussed the methodology to implement those skills into a complete sales training program. This paper serves as an informational guide to the necessary skills to complete a sale and how to train for those skills.
ContributorsSweeney, Connor (Co-author) / Reid, Tyler (Co-author) / Dietrich, John (Thesis director) / Ostrom, Lonnie (Committee member) / Economics Program in CLAS (Contributor) / Department of Management and Entrepreneurship (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The millennial generation is quickly solidifying its place as the dominate generation within the workforce. As millennials transition through workplace hierarchy it is essential organizations understand how to properly develop incoming talent. This is especially important within sales as the opportunity cost for hiring and developing new sales professionals is much higher compared to other professions. Downward trends in millennial retention rates is also a strong contributing factor to the importance of understanding the millennial generation. This paper aims to identify key concepts and elements employers should incorporate into their sales training programs in order to better develop millennials entering sales roles. Through an analysis of each generation and sales training a clear framework will be identified to achieve this goal. Analyzing millennials unique strengths and weaknesses will provide the basis for the key areas employers need to focus on when designing their sales development programs. The framework identified is easily adaptable within any organizations as the concepts discussed can be universally applied.
ContributorsStensland, Zachary William (Author) / Montoya, Detra (Thesis director) / Schlacter, John (Committee member) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Machine learning has a near infinite number of applications, of which the potential has yet to have been fully harnessed and realized. This thesis will outline two departments that machine learning can be utilized in, and demonstrate the execution of one methodology in each department. The first department that will be described is self-play in video games, where a neural model will be researched and described that will teach a computer to complete a level of Super Mario World (1990) on its own. The neural model in question was inspired by the academic paper “Evolving Neural Networks through Augmenting Topologies”, which was written by Kenneth O. Stanley and Risto Miikkulainen of University of Texas at Austin. The model that will actually be described is from YouTuber SethBling of the California Institute of Technology. The second department that will be described is cybersecurity, where an algorithm is described from the academic paper “Process Based Volatile Memory Forensics for Ransomware Detection”, written by Asad Arfeen, Muhammad Asim Khan, Obad Zafar, and Usama Ahsan. This algorithm utilizes Python and the Volatility framework to detect malicious software in an infected system.
ContributorsBallecer, Joshua (Author) / Yang, Yezhou (Thesis director) / Luo, Yiran (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
When creating computer vision applications, it is important to have a clear image of what is represented such that further processing has the best representation of the underlying data. A common factor that impacts image quality is blur, caused either by an intrinsic property of the camera lens or by introducing motion while the camera’s shutter is capturing an image. Possible solutions for reducing the impact of blur include cameras with faster shutter speeds or higher resolutions; however, both of these solutions require utilizing more expensive equipment, which is infeasible for instances where images are already captured. This thesis discusses an iterative solution for deblurring an image using an alternating minimization technique through regularization and PSF reconstruction. The alternating minimizer is then used to deblur a sample image of a pumpkin field to demonstrate its capabilities.
ContributorsSmith, Zachary (Author) / Espanol, Malena (Thesis director) / Ozcan, Burcin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2023-05
Description
In this work, we explore the potential for realistic and accurate generation of hourly traffic volume with machine learning (ML), using the ground-truth data of Manhattan road segments collected by the New York State Department of Transportation (NYSDOT). Specifically, we address the following question– can we develop a ML algorithm that generalizes the existing NYSDOT data to all road segments in Manhattan?– by introducing a supervised learning task of multi-output regression, where ML algorithms use road segment attributes to predict hourly traffic volume. We consider four ML algorithms– K-Nearest Neighbors, Decision Tree, Random Forest, and Neural Network– and hyperparameter tune by evaluating the performances of each algorithm with 10-fold cross validation. Ultimately, we conclude that neural networks are the best-performing models and require the least amount of testing time. Lastly, we provide insight into the quantification of “trustworthiness” in a model, followed by brief discussions on interpreting model performance, suggesting potential project improvements, and identifying the biggest takeaways. Overall, we hope our work can serve as an effective baseline for realistic traffic volume generation, and open new directions in the processes of supervised dataset generation and ML algorithm design.
ContributorsOtstot, Kyle (Author) / De Luca, Gennaro (Thesis director) / Chen, Yinong (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
Phishing is one of most common and effective attack vectors in modern cybercrime. Rather than targeting a technical vulnerability in a computer system, phishing attacks target human behavioral or emotional tendencies through manipulative emails, text messages, or phone calls. Through PyAntiPhish, I attempt to create my own version of an anti-phishing solution, through a series of experiments testing different machine learning classifiers and URL features. With an end-goal implementation as a Chromium browser extension utilizing Python-based machine learning classifiers (those available via the scikit-learn library), my project uses a combination of Python, TypeScript, Node.js, as well as AWS Lambda and API Gateway to act as a solution capable of blocking phishing attacks from the web browser.
ContributorsYang, Branden (Author) / Osburn, Steven (Thesis director) / Malpe, Adwith (Committee member) / Ahn, Gail-Joon (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05