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Articles 1 - 7 of 7
Full-Text Articles in Other Computer Sciences
Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis
Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis
SMU Data Science Review
A quantitative analysis will be performed on experiments utilizing three different tools used for Data Science. The analysis will include replication of analysis along with comparisons of code length, output, and results. Qualitative data will supplement the quantitative findings. The conclusion will provide data support guidance on the correct tool to use for common situations in the field of Data Science.
Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi
Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi
SMU Data Science Review
In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate with …
Case Study: Using Crime Data And Open Source Data To Design A Police Patrol Area, Brent Allen
Case Study: Using Crime Data And Open Source Data To Design A Police Patrol Area, Brent Allen
SMU Data Science Review
This case study examines how to use existing crime data augmented with open source data to design a patrol area. We used the a demand signal of "calls for service" vice reports which summarize calls for service. Additionally, we augmented our existing data with traffic data from Google Maps. Traffic delays did not correspond to traffic incidents reported in the area examined. These data were plotted geographically to aid in the determination of the new patrol area. The new patrol area was created around natural geographic boundaries, the density of calls for service and police operational experience.
Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels
Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels
SMU Data Science Review
In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …
Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas
Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas
SMU Data Science Review
Abstract. In this paper, we present a cognitive virtual admissions counselor for the Master of Science in Data Science program at Southern Methodist University. The virtual admissions counselor is a system capable of providing potential students accurate information at the time that they want to know it. After the evaluation of multiple technologies, Amazon’s LEX was selected to serve as the core technology for the virtual counselor chatbot. Student surveys were leveraged to collect and generate training data to deploy the natural language capability. The cognitive virtual admissions counselor platform is currently capable of providing an end-to-end conversational dialog to …
Blockchain In Payment Card Systems, Darlene Godfrey-Welch, Remy Lagrois, Jared Law, Russell Scott Anderwald, Daniel W. Engels
Blockchain In Payment Card Systems, Darlene Godfrey-Welch, Remy Lagrois, Jared Law, Russell Scott Anderwald, Daniel W. Engels
SMU Data Science Review
Payment cards (e.g., credit and debit cards) are the most frequent form of payment in use today. A payment card transaction entails many verification information exchanges between the cardholder, merchant, issuing bank, a merchant bank, and third-party payment card processors. Today, a record of the payment transaction often records to multiple ledgers. Merchant’s incur fees for both accepting and processing payment cards. The payment card industry is in dire need of technology which removes the need for third-party verification and records transaction details to a single tamper-resistant digital ledger. The private blockchain is that technology. Private blockchain provides a linked …
Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems
Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems
Computer Science and Engineering Theses and Dissertations
Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …