Physical Sciences and Mathematics Commons^™

Product Review Classification Using Machine Learning And Statistical Data Analysis, Kajal Singh

Independent Student Projects and Publications

The aim of the paper is to implement and analyze the machine learning models for product review dataset. The project focuses on binary classification, multi-class classification, and clustering approaches to analyze and categorize product reviews. The performance of the models over each of the five classification tasks is measured by the 5-fold cross-validation scores over the training data.

Interpretable Learning In Multivariate Big Data Analysis For Network Monitoring, José Camacho, Rasmus Bro, David Kotz

Dartmouth Scholarship

There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it cannot be interpreted by a human operator. In this paper, we present an extension of the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool. In this extension, we propose a solution to the automatic derivation of features, a cornerstone step for the application of MBDA when the amount of data is massive. The resulting network monitoring approach allows …

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Reasoning About The Conant Gasket, M. Douglas Mcilroy

Computer Science Technical Reports

Previously conjectured properties of the Conant gasket, a particular non-periodic tiling of the non-negative integer grid, are proved using new recurrences. A slabwise periodicity property is identified and proved. Further fractal properties are conjectured.

A Smartwatch Step-Counting App For Older Adults: Development And Evaluation Study, George Boateng, Curtis L. Petersen, David Kotz, Karen L. Fortuna, Rebecca Masutani, John A. Batsis

Dartmouth Scholarship

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have …

The Feasibility And Utility Of Harnessing Digital Health To Understand Clinical Trajectories In Medication Treatment For Opioid Use Disorder: D-Tect Study Design And Methodological Considerations, Lisa A. Marsch, Ching-Hua Chen, Sara R. Adams, Asma Asyyed, Monique B. Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C. Jacobson, Heather K. Jones, David Kotz, Chantal A. Lambert-Harris, Zhiguo Li, Bethany Mcleman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Cynthia I. Campbell

Dartmouth Scholarship

Introduction: Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substance use during substance use disorder treatment. However, much of this literature has examined a small set of potential moderators or mediators of outcomes in MOUD treatment and may lead to over-simplified accounts of treatment non-adherence. Digital health methodologies offer great promise for capturing intensive, longitudinal ecologically-valid …

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

Eating Detection With A Head-Mounted Video Camera, Shengjie Bi, David Kotz

Computer Science Technical Reports

In this paper, we present a computer-vision based approach to detect eating. Specifically, our goal is to develop a wearable system that is effective and robust enough to automatically detect when people eat, and for how long. We collected video from a cap-mounted camera on 10 participants for about 55 hours in free-living conditions. We evaluated performance of eating detection with four different Convolutional Neural Network (CNN) models. The best model achieved accuracy 90.9% and F1 score 78.7% for eating detection with a 1-minute resolution. We also discuss the resources needed to deploy a 3D CNN model in wearable or …

Timescales Of Magma Transport In The Columbia River Flood Basalts, Determined By Paleomagnetic Data, Joseph Biasi, Leif Karlstrom

Other Staff Materials

Flood basalts represent major events in Earth History, in part because they are linked to large climate perturbations and mass extinctions. However, the durations of individual flood basalt eruptions, which directly impact potential environmental crises, are poorly constrained. Here we use a combination of paleomagnetic data and thermal modeling to create a magnetic geothermometer (MGT) that can constrain the active transport lifetime of magmatic conduits and intrusions. We apply the MGT technique to eight feeder dike segments of the Columbia River basalts (CRB), demonstrating that some dike segments were actively heating host rocks for less than one month, while other …

Detecting Receptivity For Mhealth Interventions In The Natural Environment, Varun Mishra, Florian Künzler, Jan-Niklas Kramer, Elgar Fleisch, Tobias Kowatsch, David Kotz

Dartmouth Scholarship

Just-In-Time Adaptive Intervention (JITAI) is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is properly timing the delivery of interventions, to ensure that a user is receptive and ready to process and use the support provided. Some prior works have explored the association of context and some user-specific traits on receptivity, and have built post-study machine-learning models to detect receptivity. For effective intervention delivery, however, a JITAI system needs to make in-the-moment decisions about a user's receptivity. To this end, …

A Foray Into Laboratory Scale Soil Incubations With Corn Stover And High Lignin Fermentation Byproduct, Michelle Wang

ENGS 88 Honors Thesis (AB Students)

As the production of biofuels increases to meet the demands of a growing low carbon economy, questions of sustainability surrounding its feedstock and waste streams have become increasingly relevant. In the biofuel production process, crop residues like corn stover are harvested from the field and converted to biofuels leaving generating a residue called high lignin fermentation byproduct (HLFB). From extensive process modelling in the literature, it is suggested that HLFB should be either combusted to fuel auxiliary conversion processes or returned to the soil in place of the crop residues that were harvested. Currently, there is little literature testing the …

Application Of Cycle-By-Cycle Analysis To Eeg Data From Individuals With Phelan-Mcdermid Syndrome, Naomi Miller

ENGS 88 Honors Thesis (AB Students)

This study aimed to analyze a novel method of processing data from electroencephalography (EEG) recordings, which implements time-domain cycle-by-cycle analysis. This "bycycle" method, developed by the Cole & Voytek laboratory, was implemented on a EEG dataset of children with and without Phelan-McDermid Syndrome in the hopes of uncovering network-level explanations for the genetic disorder. A supplemental Python pipeline was developed to organize and visualize the data. This led to the discovery of group-level differences in measures of cycle symmetry in alpha band waves over the sensorimotor electrodes. Through the same pipeline, the bycycle tool was validated as a sound EEG …

When Do Drivers Interact With In-Vehicle Well-Being Interventions? An Exploratory Analysis Of A Longitudinal Study On Public Roads, Kevin Koch, Varun Mishra, Shu Liu, Thomas Berger, Elgar Fleisch, David Kotz, Felix Wortmann

Dartmouth Scholarship

Recent developments of novel in-vehicle interventions show the potential to transform the otherwise routine and mundane task of commuting into opportunities to improve the drivers' health and well-being. Prior research has explored the effectiveness of various in-vehicle interventions and has identified moments in which drivers could be interruptible to interventions. All the previous studies, however, were conducted in either simulated or constrained real-world driving scenarios on a pre-determined route. In this paper, we take a step forward and evaluate when drivers interact with in-vehicle interventions in unconstrained free-living conditions.

To this end, we conducted a two-month longitudinal study with 10 …

On Mentzer’S Hardness Of The K-Center Problem On The Euclidean Plane., Raymond Chen

Computer Science Technical Reports

An instance of the k-center problem consists of n points in a metric space along with a positive integer k. The goal is to find the smallest radius r such that there exists a subset of k centers picked among them such that every point is within distance r of at least one center. Stuart Mentzer (Mentzer, 1988) wrote a paper showing that in the Euclidean plane, it is NP-Hard to approximate this problem up to a factor of √2 +√3 ≈ 1.93. However, his report is missing some details. In this note, we present details of his full construction.

Characterizing The Geomagnetic Field At High Southern Latitudes: Evidence From The Antarctic Peninsula, Joseph Biasi, Joseph Kirschvink, Roger Fu

Other Staff Materials

Due to a dearth of data from high-latitude paleomagnetic sites, it is not currently clear if the geocentric axial dipole (GAD) hypothesis accurately describes the long-term behavior of the geomagnetic field at high latitudes. Here we present new paleomagnetic and paleointensity data from the James Ross Island (JRI) volcanic group, located on the Antarctic Peninsula. This data set addresses a notable lack of data from the 60°–70°S latitude bin and includes 251 samples from 31 sites, spanning 0.99–6.8 Ma in age. We also include positive fold, conglomerate, and baked contact tests. Paleointensity data from three methods (Thellier- Thellier, pseudo-Thellier, and …

Toward A Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (A Case Study And Framework For Progress), Ryan C. Mcgranaghan, Jack Ziegler, Téo Bloch, Spencer Hatch, Enrico Camporeale, Kristina A. Lynch, Mathew Owens, Jesper Gjerloev, Binzheng Zhang, Susan Skone

Dartmouth Scholarship

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by ML approaches to appropriately utilize diverse …

Examining The Auroral Ionosphere In Three Dimensions Using Reconstructed 2d Maps Of Auroral Data To Drive The 3d Gemini Model, Robert Clayton, Meghan Burleigh, Kristina A. Lynch, Matt Zettergren, Tucker Evans, Guy Grubbs, Donald L. Hampton, David Hysell, Stephen Kaeppler, Marc Lessard, Robert Mitchell, Ashton Reimer, T. Maximillian Roberts, Marilia Samara, Roger Varney

Dartmouth Scholarship

We use the Geospace Environment Model of Ion-Neutral Interactions (GEMINI) to create three-dimensional, time-dependent simulations of auroral ionospheric parameters in the localized, several 100 km region surrounding auroral arcs observed during a winter 2017 sounding rocket campaign, resolving three-dimensional features of fine-scale (km) flow structures in the vicinity of an auroral arc. The three-dimensional calculations of GEMINI allow (with sufficient driving data) auroral current closure to be investigated without idealizing assumptions of sheet-like structures or height integrated ionospheres. Datamaps for two nearly sheet-like arcs are reconstructed from replications of the Isinglass sounding rocket campaign data, and combined with camera-based particle …

Small-Scale Dynamic Aurora, Ryuho Kataoka, Christopher C. Chaston, David Knudsen, Kristina A. Lynch, Robert L. Lysak, Yan Song, Robert Rankin, Kiyoka Murase, Takeshi Sakanoi, Joshua Semeter, Tomo-Hiko Watanabe, Daniel Whiter

Dartmouth Scholarship

Small-scale dynamic auroras have spatial scales of a few km or less, and temporal scales of a few seconds or less, which visualize the complex interplay among charged particles, Alfvén waves, and plasma instabilities working in the magnetosphere-ionosphere coupled regions. We summarize the observed properties of flickering auroras, vortex motions, and filamentary structures. We also summarize the development of fundamental theories, such as dispersive Alfvén waves (DAWs), plasma instabilities in the auroral acceleration region, ionospheric feedback instabilities (IFI), and the ionospheric Alfvén resonator (IAR).

Thaw Publications, Carl Landwehr, David Kotz

Computer Science Technical Reports

In 2013, the National Science Foundation's Secure and Trustworthy Cyberspace program awarded a Frontier grant to a consortium of four institutions, led by Dartmouth College, to enable trustworthy cybersystems for health and wellness. As of this writing, the Trustworthy Health and Wellness (THaW) project's bibliography includes more than 130 significant publications produced with support from the THaW grant; these publications document the progress made on many fronts by the THaW research team. The collection includes dissertations, theses, journal papers, conference papers, workshop contributions and more. The bibliography is organized as a Zotero library, which provides ready access to citation materials …

Evaluating The Reproducibility Of Physiological Stress Detection Models, Varun Mishra, Sougata Sen, Grace Chen, Tian Hao, Jeffrey Rogers, Ching-Hua Chen, David Kotz

Dartmouth Scholarship

Recent advances in wearable sensor technologies have led to a variety of approaches for detecting physiological stress. Even with over a decade of research in the domain, there still exist many significant challenges, including a near-total lack of reproducibility across studies. Researchers often use some physiological sensors (custom-made or off-the-shelf), conduct a study to collect data, and build machine-learning models to detect stress. There is little effort to test the applicability of the model with similar physiological data collected from different devices, or the efficacy of the model on data collected from different studies, populations, or demographics.

This paper takes …

Barriers And Facilitators In Implementing A Pilot, Pragmatic, Telemedicine-Delivered Healthy Lifestyle Program For Obesity Management In A Rural, Academic Obesity Clinic, John A. Batsis, Auden C. Mcclure, Aaron B. Weintraub, Diane Sette, Sivan Rotenberg, Courtney J. Stevens, Diane Gilbert-Diamond, David Kotz, Stephen Bartels, Summer B. Cook, Richard I. Rothstein

Dartmouth Scholarship

Few evidence-based strategies are specifically tailored for disparity populations such as rural adults. Two-way video-conferencing using telemedicine can potentially surmount geographic barriers that impede participation in high-intensity treatment programs offering frequent visits to clinic facilities. We aimed to understand barriers and facilitators of implementing a telemedicine-delivered tertiary-care, rural academic weight-loss program for the management of obesity.

Using Natural Language Processing And Sentiment Analysis To Augment Traditional User-Centered Design: Development And Usability Study, Curtis L. Petersen, Ryan Halter, David Kotz, Lorie Loeb, Summer B. Cook, Dawna M. Pidgeon, Brock Christensen, John A. Batsis

Dartmouth Scholarship

Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process.

Objective: This study aims …

Automatic Recognition, Segmentation, And Sex Assignment Of Nocturnal Asthmatic Coughs And Cough Epochs In Smartphone Audio Recordings: Observational Field Study, Filipe Barata, Peter Tinschert, Frank Rassouli, Claudia Steurer-Stey, Elgar Fleisch, Milo Puhan, Martin Brutsche, David Kotz, Tobias Kowatsch

Dartmouth Scholarship

Background: Asthma is one of the most prevalent chronic respiratory diseases. Despite increased investment in treatment, little progress has been made in the early recognition and treatment of asthma exacerbations over the last decade. Nocturnal cough monitoring may provide an opportunity to identify patients at risk for imminent exacerbations. Recently developed approaches enable smartphone-based cough monitoring. These approaches, however, have not undergone longitudinal overnight testing nor have they been specifically evaluated in the context of asthma. Also, the problem of distinguishing partner coughs from patient coughs when two or more people are sleeping in the same room using contact-free audio …

Feasibility Of Electric Field Assisted Clogging Reduction In Cold Gas Spraying Nozzle, Hendric Tronsson

ENGS 88 Honors Thesis (AB Students)

The relatively novel cold spraying process expands its range of applications constantly. In order to continue this trend, this process still has various hurdles that need to be overcome such as clogging. Clogging within the cold gas spraying process causes porous coatings with less material properties and lower durability; a solution is needed in order to reduce the clogging and so expand the cold gas spraying applications. This study aimed to explore the feasibility of using an electric field to reduce clogging. To do so a simplified channel was used to simulate charged particle trajectory shifts under the influence of …

Cup-Net: Compressed Ultrafast Photography Using Convolutional Neural Networks, Matthew Parker

ENGS 88 Honors Thesis (AB Students)

Compressed ultrafast photography (CUP) is a cutting-edge imaging technique that uses a variation of the traditional streak camera to obtain video at 100 billion frames per second with a single exposure. In order to achieve this level of temporal detail, CUP leverages compressed sensing (CS). Compressed sensing theory states that a compressed representation of an image can be directly acquired using a non-adaptive measurement matrix so long as the encoding matrix follows certain properties such as restrictive isometry and incoherence. This compressed representation of the original scene can later be reconstructed back into the original form. CUP applies CS by …

Utilizing Neural Networks And Wearables To Quantify Hip Joint Angles And Moments During Walking And Stair Ascent, Megan V. Mccabe

ENGS 88 Honors Thesis (AB Students)

Wearable sensors were leveraged to develop two methods for computing hip joint angles and moments during walking and stair ascent that are more portable than the gold standard. The Insole-Standard (I-S) approach replaced force plates with force-measuring insoles and achieved results that match the curvature of results from similar studies. Peaks in I-S kinetic results are high due to error induced by applying the ground reaction force to the talus. The Wearable-ANN (W-A) approach combines wearables with artificial neural networks to compute the same results. Compared against the I-S, the W-A approach performs well (average rRMSE = 18%, R^{2 …}

On Session Languages, Prashant Anantharaman, Sean W. Smith

Computer Science Technical Reports

The LangSec approach defends against crafted input attacks by defining a formal language specifying correct inputs and building a parser that decides that language. However, each successive input is not necessarily in the same basic language---e.g., most communication protocols use formats that depend on values previously received, or on some other additional context. When we try to use LangSec in these real-world scenarios, most parsers we write need additional mechanisms to change the recognized language as the execution progresses. This paper discusses approaches researchers have previously taken to build parsers for such protocols and provides formal descriptions of new sets …

Distributed Iot Attestation Via Blockchain (Extended Version), Ira Ray Jenkins, Sean W. Smith

Computer Science Technical Reports

The growing number and nature of Internet of Things (IoT) devices makes these resource-constrained appliances particularly vulnerable and increasingly impactful in their exploitation. Current estimates for the number of connected "things" commonly reach the tens of billions. The low-cost and limited computational strength of these devices can preclude security features. Additionally, economic forces and a lack of industry expertise in security often contribute to a rush to market with minimal consideration for security implications. It is essential that users of these emerging technologies, from consumers to IT professionals, be able to establish and retain trust in the multitude of diverse …

The Application Of Digital Health To The Assessment And Treatment Of Substance Use Disorders: The Past, Current, And Future Role Of The National Drug Abuse Treatment Clinical Trials Network, Lisa A. Marsch, Aimee Campbell, Cynthia Campbell, Ching-Hua Chen, Emre Ertin, Udi Ghitza, Chantal Lambert-Harris, Saeed Hassanpour, August F. Holtyn, Yih-Ing Hser, Petra Jacobs, Jeffrey D. Klausner, Shea Lemley, David Kotz, Andrea Meier, Bethany Mcleman, Jennifer Mcneely, Varun Mishra, Larissa Mooney, Edward Nunes, Chrysovalantis Stafylis, Catherine Stanger, Elizabeth Saunders, Geetha Subramaniam, Sean Young

Dartmouth Scholarship

The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research that leverages digital technologies to glean new insights into SUDs and provide science-based therapeutic tools to a diverse array of persons with SUDs.

This manuscript provides an overview of the breadth and impact of research conducted in the realm of digital health within the CTN. This work has …

Apparatus For Securely Configuring A Target Device And Associated Methods, Timothy J. Pierson, Xiaohui Liang, Ronald Peterson, David Kotz

Other Faculty Materials

Apparatus and method securely transfer first data from a source device to a target device. A wireless signal having (a) a higher speed channel conveying second data and (b) a lower speed channel conveying the first data is transmitted. The lower speed channel is formed by selectively transmitting the wireless signal from one of a first and second antennae of the source device based upon the first data. The first and second antenna are positioned a fixed distance apart and the target device uses a received signal strength indication (RSSI) of the first signal to decode the lower speed channel …

Workshop On The Development And Evaluation Of Digital Therapeutics For Health Behavior Change: Science, Methods, And Projects, Alan J. Budney, Lisa A. Marsch, Will M. Aklin, Jacob T. Borodovsky, Mary F. Brunette, Andrew T. Campbell, Jesse Dallery, David Kotz, Ashley A. Knapp, Sarah E. Lord, Edward V. Nunes, Emily A. Scherer, Catherine Stanger, William C. Torrey

Dartmouth Scholarship

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that …