Physical Sciences and Mathematics Commons^™

Designing A Future: Silicon Valley-Born Brit Biddle '19 Melds Tech And Art Of Mayflower Hill, Mareisa Weil

Colby Magazine

"This education has taught me how to look at a problem and really think about it. And i've been able to balance that out with art." -Brit Biddle '19

The Use Of Digital Millenium Copyright Act To Stifle Speech Through Non-Copyright Related Takedowns, Miller Freeman

Seattle Journal of Technology, Environmental & Innovation Law

In 1998, Congress passed the Digital Millennium Copyright Act. This law provided new methods of protecting copyright in online media. These protections shift the normal judicial process that would stop the publication of infringing materials to private actors: the online platforms. As a result, online platforms receive notices of infringement and issue takedowns of allegedly copyrighted works without the judicial process which normally considers the purpose of the original notice of infringement. In at least one case, discussed in detail below, this has resulted in a notice and takedown against an individual for reasons not related to the purpose of …

Who Owns Bitcoin? Private Law Facing The Blockchain, Matthias Lehmann

Minnesota Journal of Law, Science & Technology

No abstract provided.

A Data Driven Approach To Forecast Demand, Hannah Kosinovsky, Sita Daggubati, Kumar Ramasundaram, Brent Allen

SMU Data Science Review

Abstract. In this paper, we present a model and methodology for accurately predicting the following quarter’s sales volume of individual products given the previous five years of sales data. Forecasting product demand for a single supplier is complicated by seasonal demand variation, business cycle impacts, and customer churn. We developed a novel prediction using machine learning methodology, based upon a Dense neural network (DNN) model that implicitly considers cyclical demand variation and explicitly considers customer churn while minimizing the least absolute error between predicted demand and actual sales. Using parts sales data for a supplier to the oil and gas …

Nerf This: Copyright Highly Creative Video Game Streams As Sports Broadcasts, Madeleine A. Ball

William & Mary Law Review

Since the 1980s, video games have grown exponentially as an entertainment medium. Once relegated to the niche subcultures of nerds, video games are now decidedly mainstream, drawing over 200 million American consumers yearly. As a result, the industry has stepped up its game. No longer simply a diversion to be enjoyed individually, Americans are increasingly watching others play video games like they might watch television. This practice, where enthusiastic gamers broadcast their video game session online to crowds of viewers, is called “live streaming.”

While streaming has become lucrative and popular, American copyright law currently nerfs this nascent industry. Streams …

The Internet Of Bodies, Andrea M. Matwyshyn

William & Mary Law Review

This Article introduces the ongoing progression of the Internet of Things (IoT) into the Internet of Bodies (IoB)—a network of human bodies whose integrity and functionality rely at least in part on the Internet and related technologies, such as artificial intelligence. IoB devices will evidence the same categories of legacy security flaws that have plagued IoT devices. However, unlike most IoT, IoB technologies will directly, physically harm human bodies—a set of harms courts, legislators, and regulators will deem worthy of legal redress. As such, IoB will herald the arrival of (some forms of) corporate software liability and a new legal …

On The Yellow Brick Road, A Path To Enterprise Architecture Maturity, Avsharn Bachoo

The African Journal of Information Systems

This study concentrated on the relationship between the Enterprise Architecture (EA) maturity of an organization and the business value associated with it in the South African financial services environment. It was developed within the critical realism philosophy, which states that mechanisms generate events by accentuating the underlying EA mechanisms that lead to business value, as well as provide insights into the opportunities and challenges organizations experienced as they progressed to higher levels of maturity. Constructed using the resource-based view of the firm as the underlying theoretical framework, this research examined EA as an intangible resource and maturity as a source …

Pristine Sentence Translation: A New Approach To A Timeless Problem, Meenu Ahluwalia, Brian Coari, Ben Brock

SMU Data Science Review

Abstract.

Pristine Sentence Translation (PST) is a new approach to language translation based upon sentence-level granularity. Traditional translation approaches, including those utilizing advanced machine learning or neural network-based approaches, translate on a word-by-word or phrase-by-phrase basis; thereby, potentially missing the context or meaning of the complete sentence. Instead of these piecewise translations, PST utilizes deep learning and predictive modeling techniques to translate complete sentences from their source language into their target language. With these approaches we were able to translate sentences that closely conveyed the meaning of the original sentences. Our results demonstrated that PST’s method of translating an entire …

Designing Of The Electronic Components Used In The Device For Biomedical Signals Measurement, H.N Zaynidinov, Sarvar Mahmudjonov

Bulletin of TUIT: Management and Communication Technologies

Wireless health care monitoring technologies have the energetic to replace our lifestyle with various application uses in the field of such as healthcare management, retailer, travels, company, dependents care and urgent management, in addition to many area for improving. Electrocardiography (ECG) is a common technique for recording the electrical activity of human heart. Accurate computer analysis of ECG signal is challenging, as it is exceedingly prone to high frequency noise and various other artifacts due to its low amplitude. The accuracy of these algorithms relies on the low-pass and high-pass filtration of the input ECG signal. In this paper, it …

Mathematical Model And Algorithm For Calculating Complex Words In The Karakalpak Language, Shaxnoza Abidova

Bulletin of TUIT: Management and Communication Technologies

The article examines the morphology of the Karakalpak language, which belongs to the Kipchak group of the Turkic language family. The forms of word formation in the Karakalpak language, their sequences and the affixes added to the core are analyzed. On the basis of the analyzed affixes and suffixes, a complex mathematical model of word formation in the Karakalpak language was developed. On the basis of the developed mathematical model, an algorithm for creating a complex word in the Karakalpak language was developed. Using the developed mathematical model, a four-stage scheme was created for creating complex words of the Karakalpak …

Low-Cost 8mm/Super 8 Film Digitization Using A Canon 9000f Ii Flatbed Scanner And Photoshop: A Case Study, Kenneth Eckert

Journal of Contemporary Archival Studies

For some fifty years, 8mm/Super 8 movie film was a widespread format for home movies and amateur hobbyists; yet the films and projection or telecine transfer equipment are now aging and obscure, presenting a difficulty for archivists and filmmakers. Online DIY solutions usually involve photographing the film with a DSLR and macro bellows, requiring a high degree of expertise and expense. This case study examines typical problems and proposes a simpler and low-cost solution involving using a Canon flatbed scanner with a transparency adapter and improvised film holder, and more importantly, describes technical solutions and script code to straighten and …

Orca Travel Grant Recipient An Interview With Emily Hoard, Emily Hoard

Steeplechase: An ORCA Student Journal

No abstract provided.

Comparisons Of Performance Between Quantum And Classical Machine Learning, Christopher Havenstein, Damarcus Thomas, Swami Chandrasekaran

SMU Data Science Review

In this paper, we present a performance comparison of machine learning algorithms executed on traditional and quantum computers. Quantum computing has potential of achieving incredible results for certain types of problems, and we explore if it can be applied to machine learning. First, we identified quantum machine learning algorithms with reproducible code and had classical machine learning counterparts. Then, we found relevant data sets with which we tested the comparable quantum and classical machine learning algorithm's performance. We evaluated performance with algorithm execution time and accuracy. We found that quantum variational support vector machines in some cases had higher accuracy …

A Comparative Evaluation Of Recommender Systems For Hotel Reviews, Ryan Khaleghi, Kevin Cannon, Raghuram Srinivas

SMU Data Science Review

There has been increasing growth in deployment of recommender systems across Internet sites, with various models being used. These systems have been particularly valuable for review sites, as they seek to add value to the user experience to gain market share and to create new revenue streams through deals. Hotels are a prime target for this effort, as there is a large number for most destinations and a lot of differentiation between them. In this paper, we present an evaluation of two of the most popular methods for hotel review recommender systems: collaborative filtering and matrix factorization. The accuracy of …

Agent-Based Modeling And Simulation Approaches In Stem Education Research, Shanna R. Simpson-Singleton, Xiangdong Che

Journal of International Technology and Information Management

The development of best practices that deliver quality STEM education to all students, while minimizing achievement gaps, have been solicited by several national agencies. ABMS is a feasible approach to provide insight into global behavior based upon the interactions amongst agents and environments. In this review, we systematically surveyed several modeling and simulation approaches and discussed their applications to the evaluation of relevant theories in STEM education. It was found that ABMS is optimal to simulate STEM education hypotheses, as ABMS will sensibly present emergent theories and causation in STEM education phenomena if the model is properly validated and calibrated.

Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr

Human–Wildlife Interactions

In this study, we examined the use of an unmanned aerial system (UAS) to monitor fish-eating birds on catfish (Ictalurus spp.) aquaculture facilities in Mississippi, USA. We tested 2 automated computer algorithms to identify bird species using mosaicked imagery taken from a UAS platform. One algorithm identified birds based on color alone (color segmentation), and the other algorithm used shape recognition (template matching), and the results of each algorithm were compared directly to manual counts of the same imagery. We captured digital imagery of great egrets (Ardea alba), great blue herons (A. herodias), …

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

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

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.

Social Engineering In Non-Linear Warfare, Bill Gardner

Journal of Applied Digital Evidence

This paper explores the use of hacking, leaking, and trolling by Russia to influence the 2016 United States Presidential Elections. These tactics have been called “the weapons of the geek” by some researchers. By using proxy hackers and Russian malware to break into the email of the Democratic National Committee and then giving that email to Wikileaks to publish on the Internet, the Russian government attempted to swing the election in the favor of their preferred candidate.

The source of the malware used in the DNC hack was determined to be of Russian in nature and has been used on …

Accuracy Evaluation Of The Canadian Openstreetmap Road Networks, Hongyu Zhang, Jacek Malczewski

International Journal of Geospatial and Environmental Research

Volunteered geographic information (VGI) has been applied in many fields such as participatory planning, humanitarian relief and crisis management. One of the reasons for popularity of VGI is its cost-effectiveness. However, the coverage and accuracy of VGI cannot be guaranteed. The issue of geospatial data quality in the OpenStreetMap (OSM) project has become a trending research topic because of the large size of the dataset and the multiple channels of data access. This paper focuses on a national study of the Canadian OSM road network data for the assessment of completeness, positional accuracy, attribute accuracy, semantic accuracy and lineage. The …

An Adapted Framework For Environmental Sustainability Reporting Using Mobile Technologies, Andre P. Calitz, Jaco F. Zietsman

The African Journal of Information Systems

Corporate governance is the process by which organisations are directed and controlled. King IV is regarded as the cornerstone of corporate governance for businesses and emphasises the importance of sustainability reporting in South Africa. Sustainability reporting guidelines inform organisations how to disclose their most critical affects on the environment, society and the economy. The Global Reporting Initiative (GRI) G4 sustainability reporting framework recommends the Standard Disclosures that all organisations should use to report their sustainability impacts and performance. Sustainability reporting frameworks proposed for the Higher Education sector require reporting principles specific to the needs of Higher Education Institutions (HEIs). The …

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

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

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 …

Blockchain: Technical Review, Evan D. Poff

Marriott Student Review

This review of blockchain technology accompanies the article "Strategic Implications of Blockchain."

Semantic Markup For Geographic Web Maps In Html, Malte Reißig

Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings

In the recent years more and more geographical web maps have been developed and published on the Open Web Platform. Technically this has turned all variants of these maps into documents of the Hypertext Markup Language (HTML) making them appear to us naturally as graph-like and semi-structured data. In this dispute with geographical web maps and HTML we draw on the notion of so called “map mashups”. Requiring an alternative model and definition of what such a map is, our research allows us to build and refine supportive technology which helps us in analyzing and interpreting information map makers code …

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.

Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang

Journal of the Arkansas Academy of Science

The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.

Scenario Development For Unmanned Aircraft System Simulation-Based Immersive Experiential Learning, Nickolas D. Macchiarella, Alexander J. Mirot

Journal of Aviation/Aerospace Education & Research

Application of scenario-based training can serve as practical means of educating remote pilots and sensor operators as they seek professional levels of knowledge. Both education and training can build upon time-tested training and simulation methodologies that apply simulators in settings that mirror real-world operations. Embry-Riddle Aeronautical University’s unmanned aircraft system (UAS) program curriculum is rooted in immersive simulation that offers students an experiential learning experience that is aimed to develop higher-order thinking skills. Skills that are critical to professional levels of performance. The degree program builds from basic application skills to critical thinking skills by using immersive scenario-based training in …