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Full-Text Articles in Physical Sciences and Mathematics
Interlocking Structure Design And Assembly, Yinan Zhang
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
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 …
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
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
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 …
Application Of Binary Search To Video Annotation And Behavior Tracking For The Social Sciences, Caitlyn Lee
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
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
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 …
Convergence Times Of Decentralized Graph Coloring Algorithms, Paul B. De Supinski
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
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 …
Is Augmented Reality In Denial Of The Convention? Examining The Presence Of Uncanny Valley In Augmented Reality, Sung Jun Park
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 …