Computer Sciences Commons^™

Proximity Detection With Single-Antenna Iot Devices, Timothy J. Pierson, Travis Peters, Ronald Peterson, David Kotz

Dartmouth Scholarship

Providing secure communications between wireless devices that encounter each other on an ad-hoc basis is a challenge that has not yet been fully addressed. In these cases, close physical proximity among devices that have never shared a secret key is sometimes used as a basis of trust; devices in close proximity are deemed trustworthy while more distant devices are viewed as potential adversaries. Because radio waves are invisible, however, a user may believe a wireless device is communicating with a nearby device when in fact the user’s device is communicating with a distant adversary. Researchers have previously proposed methods for …

Exploring The Uncanny Valley Effect In Vr/Ar, Ting Yan

Dartmouth College Master’s Theses

This research is focused on the Uncanny Valley Effect of humanoid avatars, in a Virtual Reality (VR) /Augmented Reality (AR) environment. We designed and conducted a user study to observe people's reaction and behavior when interacting with virtual avatars of different levels of human likeness in VR and AR. Subjective surveys and objective measurement including EEG (Electroencephalogram), GSR (Galvanic Skin Response), Pupil Dilation sensors are used for quantification. Our result shows that, overall, in AR, people tend to like more human-like avatars, and users are more sensitive to facial expressions compared to body resemblance, especially on highly human likeness avatars. …

Using Vibrations From A Smartring As An Out-Of-Band Channel For Sharing Secret Keys, Sougata Sen, Varun Mishra, David Kotz

Dartmouth Scholarship

With the rapid growth in the number of Internet of Things (IoT) devices with wireless communication capabilities, and sensitive information collection capabilities, it is becoming increasingly necessary to ensure that these devices communicate securely with only authorized devices. A major requirement of this secure communication is to ensure that both the devices share a secret, which can be used for secure pairing and encrypted communication. Manually imparting this secret to these devices becomes an unnecessary overhead, especially when the device interaction is transient. In this work, we empirically investigate the possibility of using an out-of-band communication channel – vibration, generated …

Interlocking Structure Design And Assembly, Yinan Zhang

Dartmouth College Ph.D Dissertations

Many objects in our life are not manufactured as whole rigid pieces. Instead, smaller components are made to be later assembled into larger structures. Chairs are assembled from wooden pieces, cabins are made of logs, and buildings are constructed from bricks. These components are commonly designed by many iterations of human thinking. In this report, we will look at a few problems related to interlocking components design and assembly. Given an atomic object, how can we design a package that holds the object firmly without a gap in-between? How many pieces should the package be partitioned into? How can we …

Trustworthy Wireless Personal Area Networks, Travis W. Peters

Dartmouth College Ph.D Dissertations

In the Internet of Things (IoT), everyday objects are equipped with the ability to compute and communicate. These smart things have invaded the lives of everyday people, being constantly carried or worn on our bodies, and entering into our homes, our healthcare, and beyond. This has given rise to wireless networks of smart, connected, always-on, personal things that are constantly around us, and have unfettered access to our most personal data as well as all of the other devices that we own and encounter throughout our day. It should, therefore, come as no surprise that our personal devices and data …

Networkmetrics Unraveled: Mbda In Action, José Camacho, Rasmus Bro, David Kotz

Other Faculty Materials

We propose networkmetrics, a new data-driven approach for monitoring, troubleshooting and understanding communication networks using multivariate analysis. Networkmetric models are powerful machine-learning tools to interpret and interact with data collected from a network. In this paper, we illustrate the application of Multivariate Big Data Analysis (MBDA), a recently proposed networkmetric method with application to Big Data sets. We use MBDA for the detection and troubleshooting of network problems in a campus-wide Wi-Fi network. Data includes a seven-year trace (from 2012 to 2018) of the network’s most recent activity, with approximately 3,000 distinct access points, 40,000 authenticated users, and 600,000 distinct …

Use Of Amulet In Behavioral Change For Geriatric Obesity Management, John A. Batsis, Alexandra B. Zagaria, Ryan J. Halter, George G. Boateng, Patrick Proctor, Stephen J. Bartels, David Kotz

Dartmouth Scholarship

Background: Obesity in older adults is a significant public health concern. Weight-loss interventions are known to improve physical function but risk the development of sarcopenia. Mobile health devices have the potential to augment existing interventions and, if designed accordingly, could improve one’s physical activity and strength in routine physical activity interventions.

Methods and results: We present Amulet, a mobile health device that has the capability of engaging patients in physical activity. The purpose of this article is to discuss the development of applications that are tailored to older adults with obesity, with the intention to engage and improve their health. …

Multi-Ontology Refined Embeddings (More): A Hybrid Multi-Ontology And Corpus-Based Semantic Representation For Biomedical Concepts, Steven Jiang

Dartmouth College Undergraduate Theses

Objective: Currently, a major limitation for natural language processing (NLP) analyses in clinical applications is that a concept can be referenced in various forms across different texts. This paper introduces Multi-Ontology Refined Embeddings (MORE), a novel hybrid framework for incorporating domain knowledge from various ontologies into a distributional semantic model, learned from a corpus of clinical text. This approach generates word embeddings that are more accurate and extensible for computing the semantic similarity of biomedical concepts than previous methods. Materials and Methods: We use the RadCore and MIMIC-III free-text datasets for the corpus-based component of MORE. For the ontology-based component, …

Orthogonal Array Sampling For Monte Carlo Based Rendering, Afnan Enayet

Dartmouth College Undergraduate Theses

In computer graphics (especially in offline rendering), the current state of the art rendering techniques utilize Monte Carlo integration to simulate light and calculate the value of each pixel in order to generate a realistic-looking image. Monte Carlo integration is a highly efficient method to estimate an integral that scales extremely well to a high number of dimensions, making it well suited for graphics, because generating images creates a high-dimensional integrand. The efficiency of these Monte Carlo integrations depends on the sampling techniques used, and using a more efficient sampling technique can make a Monte Carlo simulation converge to the …

Evaluating The Efficacy Of Magnetometer-Based Vehicle Sensors, Luke A. Hudspeth

Dartmouth College Undergraduate Theses

The issue of parking is more at the forefront of urban development than one might believe. In fact, academic studies have shown that roughly 30% of city traffic is due to drivers circling city blocks attempting to find an open spot. Due to such congestion people often avoid urban centers and downtown areas for shopping or dining because parking is such a hassle and assumed to be unavailable. If drivers knew where parking was available in real time, they could proceed directly to open spaces as opposed to their congestion-inducing attempts to park. A better solution would guide drivers to …

Development And Usability Assessment Of A Connected Resistance Exercise Band Application For Strength-Monitoring, John A. Batsis, George G. Boateng, Lillian M. Seo, Curtis L. Petersen, Karen L. Fortuna, Emily V. Wechsler, Ronald J. Peterson, Summer B. Cook, Dawna Pidgeon, Rachel S. Dokko, Ryan J. Halter, David F. Kotz

Dartmouth Scholarship

Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults …

Closetalker: Secure, Short-Range Ad Hoc Wireless Communication, Timothy J. Pierson, Travis Peters, Ronald Peterson, David Kotz

Dartmouth Scholarship

Secure communication is difficult to arrange between devices that have not previously shared a secret. Previous solutions to the problem are susceptible to man-in-the-middle attacks, require additional hardware for out-of-band communication, or require an extensive public-key infrastructure. Furthermore, as the number of wireless devices explodes with the advent of the Internet of Things, it will be impractical to manually configure each device to communicate with its neighbors. Our system, CloseTalker, allows simple, secure, ad hoc communication between devices in close physical proximity, while jamming the signal so it is unintelligible to any receivers more than a few centimeters away. CloseTalker …

Application Of Binary Search To Video Annotation And Behavior Tracking For The Social Sciences, Caitlyn Lee

Dartmouth College Undergraduate Theses

Annotation and labeling is a critical component of computer vision. However, completed manually, this process is time and cost-intensive. In particular, video annotation is particularly arduous in terms of manual annotation and therefore is additionally costly. Because videos are often annotated frame by frame, making little use of the fact that the data between any two consecutive frames are closely related, the process of completing a single video annotation is the equivalent of the cumulative work of annotating and labeling an equal number of distinct images. For certain applications of video annotation, we can leverage assumptions about the objects in …

Comparing Brain-Like Representations Learned By Vanilla, Residual, And Recurrent Cnn Architectures, Cara E. Van Uden

Dartmouth College Undergraduate Theses

Though it has been hypothesized that state-of-the art residual networks approximate the recurrent visual system, it is yet to be seen if the representations learned by these "biologically inspired" CNNs actually have closer representations to neural data. It is likely that CNNs and DNNs that are most functionally similar to the brain will contain mechanisms that are most like those used by the brain. In this thesis, we investigate how different CNN architectures approximate the representations learned through the ventral-object recognition and processing-stream of the brain. We specifically evaluate how recent approximations of biological neural recurrence-such as residual connections, dense …

Fair Algorithms For Clustering, Nicolas J. Flores

Dartmouth College Undergraduate Theses

As algorithms play a large role in our decision making, the possibility of algorithmic bias has led researchers to explore the realm of fair algorithms. In this thesis, we explore the design of a fair algorithm for clustering a problem in unsupervised machine learning algorithm. Our algorithm aims to balance the representation of an arbitrary number of protected groups in each cluster. We extend prior work by allowing the points to belong to multiple protected groups and for users to compromise between stricter fairness and the clustering objective. We provide experimental validation of our work on the k-median, k-means and …

Is Augmented Reality In Denial Of The Convention? Examining The Presence Of Uncanny Valley In Augmented Reality, Sung Jun Park

Dartmouth College Undergraduate Theses

Uncanny valley is a theorized psychological phenomenon, which captures a non-monotonic relationship between an entity's anthropomorphic level and the shinwakan (affinity) its viewers feel toward the entity. According to the theory, viewers feel a stronger affinity to an anthropomorphic entity as its level of human likeness increases until it reaches a certain point where that affinity is brought to a sudden drop. This valley, although frequently observed, still remains not well understood or explained. That said, most studies purport to present an explanation to the valley in context of robotics or computer-generated images portrayed on 2D surfaces, but it is …

Convergence Times Of Decentralized Graph Coloring Algorithms, Paul B. De Supinski

Dartmouth College Undergraduate Theses

Ordinary graph coloring algorithms are nothing without their calculations, memorizations, and inter-vertex communications. We investigate a class of ultra simple algorithms which can find (Delta+1)-colorings despite drastic restrictions. For each procedure, conflicted vertices randomly recolor one at a time until the graph coloring is valid. We provide an array of run time bounds for these processes, including an O(n*log(Delta)) bound for a variant we propose, and an O(n*Delta) bound which applies to even the most adversarial scenarios.

Twitter Bot Detection In The Context Of The 2018 Us Senate Elections, Wes Kendrick

Dartmouth College Undergraduate Theses

A growing percentage of public political communication takes place on social media sites such as Twitter, and not all of it is posted by humans. If citizens are to have the final say online, we must be able to detect and weed out bot accounts. The objective of this thesis is threefold: 1) expand the pool of Twitter election data available for analysis, 2) evaluate the bot detection performance of humans on a ground-truth dataset, and 3) learn what features humans associate with accounts that they believe to be bots. In this thesis, we build a large database of over …

Technology For Behavioral Change In Rural Older Adults With Obesity, John A. Batsis, John A. Naslund, Alexandra B. Zagaria, David Kotz, Rachel Dokko, Stephen J. Bartels, Elizabeth Carpenter-Song

Dartmouth Scholarship

Background: Mobile health (mHealth) technologies comprise a multidisciplinary treatment strategy providing potential solutions for overcoming challenges of successfully delivering health promotion interventions in rural areas. We evaluated the potential of using technology in a high-risk population.

Methods: We conducted a convergent, parallel mixed-methods study using semi-structured interviews, focus groups, and self-reported questionnaires, using purposive sampling of 29 older adults, 4 community leaders and 7 clinicians in a rural setting. We developed codes informed by thematic analysis and assessed the quantitative data using descriptive statistics.

Results: All groups expressed that mHealth could improve health behaviors. Older adults were optimistic that mHealth …

Continuous Smartphone Authentication Using Wristbands, Shrirang Mare, Reza Rawassizadeh, Ronald Peterson, David Kotz

Dartmouth Scholarship

Many users find current smartphone authentication methods (PINs, swipe patterns) to be burdensome, leading them to weaken or disable the authentication. Although some phones support methods to ease the burden (such as fingerprint readers), these methods require active participation by the user and do not verify the user’s identity after the phone is unlocked. We propose CSAW, a continuous smartphone authentication method that leverages wristbands to verify that the phone is in the hands of its owner. In CSAW, users wear a wristband (a smartwatch or a fitness band) with built-in motion sensors, and by comparing the wristband’s motion with …

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.

Pymol Plugin To Build Protein Structures Based On Natural Term Overlaps, Noah T. Paravicini

Dartmouth College Undergraduate Theses

This project is a continuation of the Grigoryan Lab's exploration of TERMs. A TERM is a tertiary structural motif, which is a fragment of a protein that includes the secondary, tertiary, and quaternary environments around a certain residue. As displayed in past publications discussing TERMs, they are a useful way of decomposing proteins into smaller components that help in understanding design and prediction of protein structures. The Grigoryan Lab developed a database that keeps track of naturally occurring overlaps between TERMs, which gives a user the information they would need to put these TERMs together into complex structures. These events …

Orecchio: Extending Body-Language Through Actuated Static And Dynamic Auricular Postures, Da-Yuan Huang, Teddy Seyed, Jun Gong, Zhihao Yao, Yuchen Jiao, Xiang Anthony Chen, Xing-Dong Yang

Dartmouth Scholarship

In this paper, we propose using the auricle – the visible part of the ear – as a means of expressive output to extend body language to convey emotional states. With an initial exploratory study, we provide an initial set of dynamic and static auricular postures. Using these results, we examined the relationship between emotions and auricular postures, noting that dynamic postures involving stretching the top helix in fast (e.g., 2Hz) and slow speeds (1Hz) conveyed intense and mild pleasantness while static postures involving bending the side or top helix towards the center of the ear were associated with intense …

Self-Powered Gesture Recognition With Ambient Light, Yichen Li, Tianxing Li, Ruchir Patel, Xia Zhou, Xing-Dong Yang

Dartmouth Scholarship

We present a self-powered module for gesture recognition that utilizes small, low-cost photodiodes for both energy harvesting and gesture sensing. Operating in the photovoltaic mode, photodiodes harvest energy from ambient light. In the meantime, the instantaneously harvested power from individual photodiodes is monitored and exploited as a clue for sensing finger gestures in proximity. Harvested power from all photodiodes are aggregated to drive the whole gesture-recognition module including a micro-controller running the recognition algorithm. We design robust, lightweight algorithm to recognize finger gestures in the presence of ambient light fluctuations. We fabricate two prototypes to facilitate user’s interaction with smart …

Indutivo: Contact-Based, Object-Driven Interactions With Inductive Sensing, Jun Gong, Xin Yang, Teddy Seyed, Josh Urban Davis, Xing-Dong Yang

Dartmouth Scholarship

We present Indutivo, a contact-based inductive sensing technique for contextual interactions. Our technique recognizes conductive objects (metallic primarily) that are commonly found in households and daily environments, as well as their individual movements when placed against the sensor. These movements include sliding, hinging, and rotation. We describe our sensing principle and how we designed the size, shape, and layout of our sensor coils to optimize sensitivity, sensing range, recognition and tracking accuracy. Through several studies, we also demonstrated the performance of our proposed sensing technique in environments with varying levels of noise and interference conditions. We conclude by presenting demo …

Battery-Free Eye Tracker On Glasses, Tianxing Li, Xia Zhou

Dartmouth Scholarship

This paper presents a battery-free wearable eye tracker that tracks both the 2D position and diameter of a pupil based on its light absorption property. With a few near-infrared (NIR) lights and photodiodes around the eye, NIR lights sequentially illuminate the eye from various directions while photodiodes sense spatial patterns of reflected light, which are used to infer pupil’s position and diameter on the fly via a lightweight inference algorithm. The system also exploits characteristics of different eye movement stages and adjusts its sensing and computation accordingly for further energy savings. A prototype is built with off-the-shelf hardware components and …

Phasorsec: Protocol Security Filters For Wide Area Measurement Systems, Prashant Anantharaman, Kartik Palani, Rafael Brantley, Sergey Bratus, Sean W. Smith

Dartmouth Scholarship

The addition of synchrophasors to the power grid to improve observability comes at the cost of an increased attack surface: the wide area measurement system. A common source of zero-days, that can be used to exploit the system, is improper input validation. The strict availability and timing requirements of the grid make it critical that input validation be done right and in a timely fashion. PhasorSec is a hardened security filter for the synchrophasor communication protocol, C37.118. PhasorSec is built using language theoretic principles which treat all input as a language with a specific grammar that defines what input must …

Evaluating Prose Style Transfer With The Bible, Keith Carlson, Allen Riddell, Daniel Rockmore

Dartmouth Scholarship

In the prose style transfer task a system, provided with text input and a target prose style, produces output which preserves the meaning of the input text but alters the style. These systems require parallel data for evaluation of results and usually make use of parallel data for training. Currently, there are few publicly available corpora for this task. In this work, we identify a high-quality source of aligned, stylistically distinct text in different versions of the Bible. We provide a standardized split, into training, development and testing data, of the public domain versions in our corpus. This corpus is …

Auracle: Detecting Eating Episodes With An Ear-Mounted Sensor, Shengjie Bi, Tao Wang, Nicole Tobias, Josephine Nordrum, Shang Wang, George Halvorsen, Sougata Sen, Ron Peterson, Kelly Caine, Kofi Odame, Ryan Halter, Jacob Sorber, David Kotz

Dartmouth Scholarship

In this paper, we propose Auracle, a wearable earpiece that can automatically recognize eating behavior. More specifically, in free-living conditions, we can recognize when and for how long a person is eating. Using an off-the-shelf contact microphone placed behind the ear, Auracle captures the sound of a person chewing as it passes through the bone and tissue of the head. This audio data is then processed by a custom analog/digital circuit board. To ensure reliable (yet comfortable) contact between microphone and skin, all hardware components are incorporated into a 3D-printed behind-the-head framework. We collected field data with 14 participants for …

Saw: Wristband-Based Authentication For Desktop Computers, Shrirang Mare, Reza Rawassizadeh, Ronald Peterson, David Kotz

Dartmouth Scholarship

Token-based proximity authentication methods that authenticate users based on physical proximity are effortless, but lack explicit user intentionality, which may result in accidental logins. For example, a user may get logged in when she is near a computer or just passing by, even if she does not intend to use that computer. Lack of user intentionality in proximity-based methods makes them less suitable for multi-user shared computer environments, despite their desired usability benefits over passwords. \par We present an authentication method for desktops called Seamless Authentication using Wristbands (SAW), which addresses the lack of intentionality limitation of proximity-based methods. SAW …