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Articles 1 - 30 of 13417

Full-Text Articles in Engineering

The Ftc And Ai Governance: A Regulatory Proposal, Michael Spiro Dec 2020

The Ftc And Ai Governance: A Regulatory Proposal, Michael Spiro

Seattle Journal of Technology, Environmental & Innovation Law

No abstract provided.


Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal Oct 2020

Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

In the blooming era of smart edge devices, surveillance cam- eras have been deployed in many locations. Surveillance cam- eras are most useful when they are spaced out to maximize coverage of an area. However, deciding where to place cam- eras is an NP-hard problem and researchers have proposed heuristic solutions. Existing work does not consider a signifi- cant restriction of computer vision: in order to track a moving object, the object must occupy enough pixels. The number of pixels depends on many factors (how far away is the object? What is the camera resolution? What is the focal length ...


A Real-Time Feature Indexing System On Live Video Streams, Aditya Chakraborty, Akshay Pawar, Hojoung Jang, Shunqiao Huang, Sripath Mishra, Shuo-Han Chen, Yuan-Hao Chang, George K. Thiruvathukal, Yung-Hsiang Lu Jul 2020

A Real-Time Feature Indexing System On Live Video Streams, Aditya Chakraborty, Akshay Pawar, Hojoung Jang, Shunqiao Huang, Sripath Mishra, Shuo-Han Chen, Yuan-Hao Chang, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Most of the existing video storage systems rely on offline processing to support the feature-based indexing on video streams. The feature-based indexing technique provides an effec- tive way for users to search video content through visual features, such as object categories (e.g., cars and persons). However, due to the reliance on offline processing, video streams along with their captured features cannot be searchable immediately after video streams are recorded. According to our investigation, buffering and storing live video steams are more time-consuming than the YOLO v3 object detector. Such observation motivates us to propose a real-time feature indexing (RTFI ...


Rapid Restoration Techniques For Software-Defined Networks, Ali Malik, Ruairí De Fréin, Benjamin Aziz May 2020

Rapid Restoration Techniques For Software-Defined Networks, Ali Malik, Ruairí De Fréin, Benjamin Aziz

Articles

There is increasing demand in modern day business applications for communication networks to be robust and reliable due to the complexity and critical nature of such applications. As such, data delivery is expected to be reliable and secure even in the harshest of environments. Software-Defined Networking (SDN) is gaining traction as a promising approach for designing network architectures which are robust and flexible. One reason for this is that separating the data plane from the control plane, increases the controller’s ability to configure the network rapidly. When network failure events occur, the network manager may trade-off the optimality of ...


Trading Up: Exchanging Our Data For A Better Life, Nathan Turner May 2020

Trading Up: Exchanging Our Data For A Better Life, Nathan Turner

Marriott Student Review

We live in a data-driven economy. Many people feel like consumers are on the losing end of an economic data-battle with tech giants, but this is simply not true; our data can drive innovation. That’s right—personal data collected from you and me can influence new technologies that will improve our lives. This should excite us, but our fear of losing data privacy can quell our excitement for progress and even restrict innovation. Our quality of life has already begun to improve through data driven innovation, and technological progress is not slowing down. If we let our fear of ...


Security Camera Using Raspberry Pi, Tejendra Khatri May 2020

Security Camera Using Raspberry Pi, Tejendra Khatri

Student Academic Conference

No abstract provided.


Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling May 2020

Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling

Student Academic Conference

Overview of a predictive analysis regression developed using machine learning alongside ETL process techniques.


Estimating The Tempo Of Audio Files, Parker Ostertag May 2020

Estimating The Tempo Of Audio Files, Parker Ostertag

Student Academic Conference

On the market today, there exists a multitude of software that allows for the detection and prediction of beats per minute (BPM) contained in audio files. There are both free and monetized versions of these programs, but there is one thing that they all have in common: they are inaccurate. This is simply because the science behind beat detection is unfinished, and may never be. In this project, I decided to use a method of audio peak detection to help me detect the tempo that may exist in any audio file. I started by researching existing programs and the science ...


Methods To Detect Forgeries In Static Signatures, Jennifer Lauriello May 2020

Methods To Detect Forgeries In Static Signatures, Jennifer Lauriello

Honors Theses

Statistical and machine learning approaches to forgery detection in offline sig- natures are attempted and evaluated. Offline signatures are static signatures found on physical media, mainly a piece of paper. A dataset of 330 signatures for 33 people is used, containing five genuine and five forged signatures for each person. The statistical analysis approach proves more successful than a machine learning approach, likely due to the size of the dataset.


Empirical Evaluation Of Vehicle Detection, Tracking And Recognition Algorithms Operating On Real Time Video Feeds, Yunik Tamrakar May 2020

Empirical Evaluation Of Vehicle Detection, Tracking And Recognition Algorithms Operating On Real Time Video Feeds, Yunik Tamrakar

Honors Theses

A traffic surveillance camera system is an important part of an intelligent transportation system.(Zhang et al., 2013) This system is capable of performing useful object detections on the incoming feed. These detected objects can then be used for tracking purposes which forms the basis for monitoring important traffic data such as collisions, vehicle count, pedestrian count and so on. Furthermore, other additional information such as the weather conditions, time of day as well as date can also be extracted from a live feed. (Sun et al., 2004) Different algorithms can yield different results for any given video input. Not ...


Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes May 2020

Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes

Honors Theses

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified ...


Zenneck Waves In Decision Agriculture: An Empirical Verification And Application In Em-Based Underground Wireless Power Transfer, Usman Raza, Abdul Salam May 2020

Zenneck Waves In Decision Agriculture: An Empirical Verification And Application In Em-Based Underground Wireless Power Transfer, Usman Raza, Abdul Salam

Faculty Publications

In this article, the results of experiments for the observation of Zenneck surface waves in sub GHz frequency range using dipole antennas are presented. Experiments are conducted over three different soils for communications distances of up to 1 m. This empirical analysis confirms the existence of Zenneck waves over the soil surface. Through the power delay profile (PDP) analysis, it has been shown that other subsurface components exhibit rapid decay as compared to the Zenneck waves. A potential application of the Zenneck waves for energy transmission in the area of decision agriculture is explored. Accordingly, a novel wireless through-the-soil power ...


Elicitation And Aggregation Of Data In Knowledge Intensive Crowdsourcing, Dohoon Kim May 2020

Elicitation And Aggregation Of Data In Knowledge Intensive Crowdsourcing, Dohoon Kim

All Computer Science and Engineering Research

With the significant advance of internet and connectivity, crowdsourcing gained more popularity and various crowdsourcing platforms emerged. This project focuses on knowledge-intensive crowdsourcing, in which agents are presented with the tasks that require certain knowledge in domain. Knowledge-intensive crowdsourcing requires agents to have experiences on the specific domain. With the constraint of resources and its trait as sourcing from crowd, platform is likely to draw agents with different levels of expertise and knowledge and asking same task can result in bad performance. Some agents can give better information when they are asked with more general question or more knowledge-specific task ...


Minet Magnetic Localization, Michael Robert Drake May 2020

Minet Magnetic Localization, Michael Robert Drake

Honors Theses

Indoor localization is a modern problem of computer science that has no unified solution, as there are significant trade-offs involved with every technique. Magnetic localization is a less popular sub-field that is rooted in infrastructure-free design, which can allow universal setup. Magnetic localization is also often paired with probabilistic programming, which provides a powerful method of estimation, given a limited understanding of the environment. This thesis presents Minet, which is a particle filter based localization system using the Earth's geomagnetic field. It explores the novel idea of state space limitation as a method of optimizing a particle filter, by ...


Centrality Of Blockchain, Zixuan Li May 2020

Centrality Of Blockchain, Zixuan Li

All Computer Science and Engineering Research

Decentralization is widely recognized as the property and one of most important advantage of blockchain over legacy systems. However, decentralization is often discussed on the consensus layer and recent research shows the trend of centralization on several subsystem of blockchain. In this project, we measured centralization of Bitcoin and Ethereum on source code, development eco-system, and network node levels. We found that the programming language of project is highly centralized, code clone is very common inside Bitcoin and Ethereum community, and developer contribution distribution is highly centralized. We further discuss how could these centralizations lead to security issues in blockchain ...


Understanding Eye Gaze Patterns In Code Comprehension, Jonathan Saddler May 2020

Understanding Eye Gaze Patterns In Code Comprehension, Jonathan Saddler

Computer Science and Engineering: Theses, Dissertations, and Student Research

Program comprehension is a sub-field of software engineering that seeks to understand how developers understand programs. Comprehension acts as a starting point for many software engineering tasks such as bug fixing, refactoring, and feature creation. The dissertation presents a series of empirical studies to understand how developers comprehend software in realistic settings. The unique aspect of this work is the use of eye tracking equipment to gather fine-grained detailed information of what developers look at in software artifacts while they perform realistic tasks in an environment familiar to them, namely a context including both the Integrated Development Environment (Eclipse or ...


Augmented Reality In A Dynamic Drone Based Environment, Christopher Davis May 2020

Augmented Reality In A Dynamic Drone Based Environment, Christopher Davis

Honors Theses

Augmented Reality (AR) and Unmanned Ariel Vehicles (UAVs) are fast advancing technologies, and this research seeks to combine them to offer an effective, user friendly approach for monitoring infrastructure. Drones provide a means to easily access otherwise difficult to reach locations and visualize useful information with Augmented Reality. A UAV employs a wide-angle view and, when paired with AR, this will enable the user to better complete their task by effortlessly providing the critical information they need in the most intuitive way possible. This research is particularly applicable for civil applications such as construction and monitoring of difficult to access ...


Predictive Modeling Of Iphone 7 Charge Rates Using Least Squares Curve Fitting, Grace Cahill May 2020

Predictive Modeling Of Iphone 7 Charge Rates Using Least Squares Curve Fitting, Grace Cahill

Honors Theses

In a time where individuals depend on their cell phones, the need for a long lasting and quick charging battery life is imperative. As information regarding how long a battery can remained charged is highly advertised, there is no information regarding how long it would take for a dead phone battery to completely charge. This study determined the amount of time it will take an iPhone 7 to charge from 0% to 100% using the standard charging cable under four different charging conditions. The charge percentage was recorded every two minutes until it was fully charged with this process being ...


Deep Learning And Polar Transformation To Achieve A Novel Adaptive Automatic Modulation Classification Framework, Pejman Ghasemzadeh May 2020

Deep Learning And Polar Transformation To Achieve A Novel Adaptive Automatic Modulation Classification Framework, Pejman Ghasemzadeh

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Automatic modulation classification (AMC) is an approach that can be leveraged to identify an observed signal's most likely employed modulation scheme without any a priori knowledge of the intercepted signal. Of the three primary approaches proposed in literature, which are likelihood-based, distribution test-based, and feature-based (FB), the latter is considered to be the most promising approach for real-world implementations due to its favorable computational complexity and classification accuracy. FB AMC is comprised of two stages: feature extraction and labeling. In this thesis, we enhance the FB approach in both stages. In the feature extraction stage, we propose a new ...


Efficient Elevator Algorithm, Sean M. Toll, Owen Barbour, Carl Edwards, Daniel Nichols, Austin Day May 2020

Efficient Elevator Algorithm, Sean M. Toll, Owen Barbour, Carl Edwards, Daniel Nichols, Austin Day

Chancellor’s Honors Program Projects

No abstract provided.


A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz May 2020

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.


Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca May 2020

Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca

Computer Science and Computer Engineering Undergraduate Honors Theses

Sentiment analysis is a natural language processing technique that aims to classify text based on the emotions expressed in them. It is a research area that has been around for almost 20 years and has seen a lot of development. The works presented in this paper attempts to target a less-developed area in sentiment analysis known as multilingual sentiment analysis. More specifically, multilingual sentiment analysis of micro-texts. Using the existing WordNet lexicon and a domain-specific lexicon for a corpus of Spanish tweets, we analyze the effectiveness of these techniques.


Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra May 2020

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility ...


Decoding Ldpc Codes With Probabilistic Local Maximum Likelihood Bit Flipping, Rejoy Roy Mathews May 2020

Decoding Ldpc Codes With Probabilistic Local Maximum Likelihood Bit Flipping, Rejoy Roy Mathews

All Graduate Theses and Dissertations

Communication channels are inherently noisy making error correction coding a major topic of research for modern communication systems. Error correction coding is the addition of redundancy to information transmitted over communication channels to enable detection and recovery of erroneous information. Low-density parity-check (LDPC) codes are a class of error correcting codes that have been effective in maintaining reliability of information transmitted over communication channels. Multiple algorithms have been developed to benefit from the LDPC coding scheme to improve recovery of erroneous information. This work develops a matrix construction that stores the information error probability statistics for a communication channel. This ...


Locating Relay Nodes To Maximize Wireless Sensor Network Lifetime: A Numerical Study, Maria Rene Arandia Jimenez May 2020

Locating Relay Nodes To Maximize Wireless Sensor Network Lifetime: A Numerical Study, Maria Rene Arandia Jimenez

Industrial Engineering Undergraduate Honors Theses

A wireless sensor network (WSN) is a group of sensors deployed over an area, which monitor changes in the environment, collects them as data and forwards it between sensors through wireless links. Data is routed, either in a single-hop or multi-hop manner, with the goal of getting this collected data to the sink nodes, which have higher computational capabilities and connects the network with a user interface. Studies have determined that multi-hop WSNs that integrate relay nodes, which function is to only receive and forward data, can maximize lifetime network. A linear programming model, created by Chang and Tassiulas in ...


Analog Versus Digital Guitar Pedals, Shaping Guitar Tones And Sparking Debates, Cameron Karren May 2020

Analog Versus Digital Guitar Pedals, Shaping Guitar Tones And Sparking Debates, Cameron Karren

Capstone Projects and Master's Theses

This paper goes into the history of guitar effects, what exactly they are, how they have evolved, and what they are like today. It also presents the results of an experiment that compares perceptions of differences between analog and digital guitar pedals.


Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi May 2020

Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi

Research Collection School Of Information Systems

Recommender systems play an important role in helping users discover items of interest from a large resource collection in various online services. Although current deep neural network-based collaborative filtering methods have achieved state-of-the-art performance in recommender systems, they still face a few major weaknesses. Most importantly, such deep methods usually focus on the direct interaction between users and items only, without explicitly modeling high-order co-occurrence contexts. Furthermore, they treat the observed data uniformly, without fine-grained differentiation of importance or relevance in the user-item interactions and high-order co-occurrence contexts. Inspired by recent progress in memory networks, we propose a novel multiplex ...


Emotional Awareness During Bug Fixes – A Pilot Study, Jada O. Loro, Abigail L. Schneff, Sarah J. Oran, Bonita Sharif Ph.D. Apr 2020

Emotional Awareness During Bug Fixes – A Pilot Study, Jada O. Loro, Abigail L. Schneff, Sarah J. Oran, Bonita Sharif Ph.D.

Computer Science and Engineering: Theses, Dissertations, and Student Research

This study examines the effects of a programmer's emotional awareness on progress while fixing bugs. The goal of the study is to capitalize on emotional awareness to ultimately increase progress made during software development. This process could result in improved software maintenance.


Minet Magnetic Indoor Localization, Michael Drake Apr 2020

Minet Magnetic Indoor Localization, Michael Drake

Honors Theses

Indoor localization is a modern problem of computer science that has no unified solution, as there are significant trade-offs involved with every technique. Magnetic localization, though less popular than WiFi signal based localization, is a sub-field that is rooted in infrastructure-free design, which can allow universal setup. Magnetic localization is also often paired with probabilistic programming, which provides a powerful method of estimation, given a limited understanding of the environment. This thesis presents Minet, which is a particle filter based localization system using the Earth's geomagnetic field. It explores the novel idea of state space limitation as a method ...


An Eye Tracking Replication Study Of A Randomized Controlled Trial On The Effects Of Embedded Computer Language Switching, Cole Peterson Apr 2020

An Eye Tracking Replication Study Of A Randomized Controlled Trial On The Effects Of Embedded Computer Language Switching, Cole Peterson

Computer Science and Engineering: Theses, Dissertations, and Student Research

The use of multiple programming languages (polyglot programming) during software development is common practice in modern software development. However, not much is known about how the use of these different languages affects developer productivity. The study presented in this thesis replicates a randomized controlled trial that investigates the use of multiple languages in the context of database programming tasks. Participants in our study were given coding tasks written in Java and one of three SQL-like embedded languages: plain SQL in strings, Java methods only, a hybrid embedded language that was more similar to Java. In addition to recording the online ...