Computational Engineering Commons^™

Desarrollo De Una Aplicación Móvil De Realidad Aumentada Para El Museo De Ciencias De La Universidad De La Salle, Laura Gabriela Munevar Barrera

Ingeniería en Automatización

El presente proyecto de grado se enmarca en el desarrollo de una aplicación móvil de realidad aumentada específicamente para realizar exhibiciones y recorridos en el museo de ciencias de la Universidad de la Salle. El proceso de presentación de los temas por parte de los curadores y expositores del museo, debido a la extensión y complejidad de los temas puede resultar arduo. Por ello se plantea el desarrollo de un aplicación móvil de realidad aumentada que permita determinar si aplicando su uso mediante la metodología mobile-D, mejora la facilidad de exposición y el interés de los visitantes en los temas …

Context-Aware Sensing And Fusion For Structural Health Monitoring And Night Time Traffic Surveillance, Xinxiang Zhang

Electrical Engineering Theses and Dissertations

Rapid developments in computer vision technologies have been transforming many traditional fields in engineering and science in the last few decades, especially in terms of diagnosing problems from visual images. Leveraging computer vision technologies to inspect, monitor, assess infrastructure conditions, and analyze traffic dynamics, has gained significant increase in both effectiveness and efficiency, compared to the cost of traditional instrumentation arrays to monitor, and manually inspect civil infrastructures and traffic conditions. Therefore, to construct the next-generation intelligent civil and transportation infrastructures, this dissertation develops a comprehensive computer-vision based sensing and fusion framework for structural health monitoring and intelligent transportation systems. …

Mtemp: An Ambient Temperature Estimation Method Using Acoustic Signal On Mobile Devices, Hao Guo

Masters Theses

Ambient temperature sensing plays an important role in a number of applications in agriculture, industry, daily health care. In this thesis project, we propose a new acoustic-based ambient temperature sensing method called Mtemp. Mtemp empowers acoustic-enabled IoT devices, smartphones to perform ambient air temperature sensing without additional hardware. Basically, Mtemp utilizes on-board speaker and microphone to calculate the propagation speed of acoustic signal by measuring the phrase of the target signal, thereby estimate the ambient temperature according to a roughly linear relationship between temperature and sound speed. Mtemp is portable and economical, making it competitive compared with traditional thermometers for …

A Deep Learning Model For Predicting Covid-19 Transmission In Connecticut, Nathan Choi

Honors Scholar Theses

COVID-19 has immensely impacted life as we know it, as the virus quickly spread throughout the entire world in a matter of weeks since its emergence. It has toppled economies, tested healthcare systems worldwide, and has un- fortunately taken the lives of many in the process. While extensive research has analyzed the issue on a large scale, focusing on entire countries and states, there has not been as much focus on the meso-scale, mainly compris- ing towns and cities, due to the lack of available COVID-19 data at this scale. However, in the case of countries like the United States …

Silicon Valley 2.0

In The Loop

The DePaul Innovation Development Lab is a collaborative ecosystem that joins business and academia in mutually beneficial, experimental enterprise. Students work in the techcentric think tank and consultancy that turns business problems into functional, testable software prototypes.

Sistema De Control Redundante Basado En Una Arquitectura Iot, Juan Pablo Velandia Suárez

Ingeniería en Automatización

En el presente trabajo se realizó la implementación de una arquitectura de control y comunicación para un tanque de característica no lineales, utilizando una red redundante basada en el protocolo MQTT. Se presenta el modelamiento del tanque, la técnica de control y la topología de comunicación utilizada a continuación los conceptos de control HSBY (Aldavert, 2019). La arquitectura se implementa con un lazo de control predeterminado que funciona en la nube y un lazo de control local, el cual entra en la operación en el momento en que el lazo de control en la nube falle. Los resultados fueron tomados …

A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi

Master's Theses

An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.

Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.

In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated …

Quantifying The Benefits Of A Collaborative Supply Chain Network Using A Discrete-Time Vehicle Routing Model, Matthew Walters

Industrial Engineering Undergraduate Honors Theses

The transportation industry contributed around one trillion dollars to the economy in 2016 accounting for 8.9% percent of the GDP. In 2017, it was responsible for 1.5 billion tons of CO₂ emissions. With the American Trucking agency predicting a 35% growth in the trucking industry between 2016 and 2027, there are rising concerns about the impact the trucking industry will have on the economy and the environment. The trucking industry is also very inefficient with many trucks driving with empty loads or with less than full capacity loads. There is potential to save billions of dollars and cut back …

The Future Of Artificial Intelligence, Alex Guerra

Emerging Writers

Whether we like it or not Artificial Intelligence (AI) is coming, and we are not ready for it. AI has unimaginable potential and will revolutionize the world over the next few decades, but with this great potential we are faced with choices that could prove detrimental to humanity. This article examines the challenges AI presents and explores possible solutions to make AI align with human interests.

Coding Club, Nicole Livingston, Madalyn Meyer

Honors Expanded Learning Clubs

Lesson plans for an about 12-week club designed to introduce middle schoolers to coding using Scratch. By the end of the club, every student will have made a game they can share with the class and have learned basic coding and game creation tools. Students can also miss classes or join late and still be able to join and enjoy the club with a different focus lesson every week.

Modern Methods Of Testing And Information Security Problems In Iot, Halim Khujamatov, Ernazar Reypnazarov, Amir Lazarev

Bulletin of TUIT: Management and Communication Technologies

This article analyzes the technology of the internet of things, ie its architecture, communication standards, threats to security and safety, methods and types of testing devices of the internet of things. In short, the architectures proposed by ITU-T and IWF, IEEE standards for Internet of Things, LPWAN standards, four levels of security (devices/gateways, network/transport, services and applications), components according to test methods, performance, loading, security, etc.

Evaluation Of Parametric And Nonparametric Statistical Models In Wrong-Way Driving Crash Severity Prediction, Sajidur Rahman Nafis

FIU Electronic Theses and Dissertations

Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Although crashes involving wrong-way drivers are relatively few, they often lead to fatalities and serious injuries. Researchers have been using parametric statistical models to identify factors that affect WWD crash severity. However, these parametric models are generally based on several assumptions, and the results could generate numerous errors and become questionable when these assumptions are violated. On the other hand, nonparametric methods such as data mining or machine learning techniques do not use a predetermined functional …

Application Of The Cluster Classification Data Mining Method To Child Illiteracy In Indonesia, Muhammad Arifin, Gita Widi Bhawika, M.A. Muazar Habibi, Winci Firdaus, Danu Eko Agustinova, Robbi Rahim

Library Philosophy and Practice (e-journal)

The objective of this study is to cluster and classify data using a combination of the k-means and C4.5 methods. The process involves clustering and subsequent classification. The classification process uses k-folds = 10 and samples = stratified sampling. In this study, analphabets in Indonesia of a minimum age of 15 years (15+) were evaluated. The data are the percentage of analogs between 2017 and 2019. The dataset was obtained from https://www.bps.go.id and is accessible at https://osf.io/crwug. In this study, the Davies Bouldin index (DBI) was used to determine the number of clusters with an optimal DBI value of k …

A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps …

Machine Learning Approaches To Historic Music Restoration, Quinn Coleman

Master's Theses

In 1889, a representative of Thomas Edison recorded Johannes Brahms playing a piano arrangement of his piece titled “Hungarian Dance No. 1”. This recording acts as a window into how musical masters played in the 19th century. Yet, due to years of damage on the original recording medium of a wax cylinder, it was un-listenable by the time it was digitized into WAV format. This thesis presents machine learning approaches to an audio restoration system for historic music, which aims to convert this poor-quality Brahms piano recording into a higher quality one. Digital signal processing is paired with two machine …

Mobile Application Development For University Library Services (Case Study: Library Of Uin Sunan Ampel Surabaya), Heri Cahyo Bagus, Firza Hardy Nugraha, Ilham M.Said, Yusuf Amrozy

Library Philosophy and Practice (e-journal)

This study was conducted to develop library services at UIN Sunan Ampel Surabaya by developing a system using the Rapid Application Development (RAD) method and the Mobile Library. This is done to complement the website services which can be accessed through catalog.uinsby.ac.id. Many users, especially students, experience restlessness in returning the book because there is no reminder feature for the deadline to return the book. As well as resulting in the number of fines that increase in number for each day. The purpose of this research is to make users more free to use the library services of UIN Sunan …

Unsupervised Data Mining Technique For Clustering Library In Indonesia, Robbi Rahim, Joseph Teguh Santoso, Sri Jumini, Gita Widi Bhawika, Daniel Susilo, Danny Wibowo

Library Philosophy and Practice (e-journal)

Organizing school libraries not only keeps library materials, but helps students and teachers in completing tasks in the teaching process so that national development goals are in order to improve community welfare by producing quality and competitive human resources. The purpose of this study is to analyze the Unsupervised Learning technique in conducting cluster mapping of the number of libraries at education levels in Indonesia. The data source was obtained from the Ministry of Education and Culture which was processed by the Central Statistics Agency (abbreviated as BPS) with url: bps.go.id/. The data consisted of 34 records where the attribute …

Parking Recommender System Privacy Preservation Through Anonymization And Differential Privacy, Yasir Saleem Shaikh, Mubashir Husain Rehmani, Noel Crespi, Roberto Minerva

Publications

Recent advancements in the Internet of Things (IoT) have enabled the development of smart parking systems that use services of third-party parking recommender system to provide recommendations of personalized parking spot to users based on their past experience. However, the indiscriminate sharing of users’ data with an untrusted (or semitrusted) parking recommender system may breach the privacy because users’ behavior and mobility patterns could be inferred by analyzing their past history. Therefore, in this article, we present two solutions that preserve privacy of users in parking recommender systems while analyzing the past parking history using k-anonymity (anonymization) and differential privacy …

A Single-Stage Passive Vibration Isolation System For Scanning Tunneling Microscopy, Toan T. Le

Master's Theses

Scanning Tunneling Microscopy (STM) uses quantum tunneling effect to study the surfaces of materials on an atomic scale. Since the probe of the microscope is on the order of nanometers away from the surface, the device is prone to noises due to vibrations from the surroundings. To minimize the random noises and floor vibrations, passive vibration isolation is a commonly used technique due to its low cost and simpler design compared to active vibration isolation, especially when the entire vibration isolation system (VIS) stays inside an Ultra High Vacuum (UHV) environment. This research aims to analyze and build a single-stage …

Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler

SMU Data Science Review

This study presents a novel approach to price optimization in order to maximize revenue for the distribution market of non-perishable products. Data analysis techniques such as association mining, statistical modeling, machine learning, and an automated machine learning platform are used to forecast the demand for products considering the impact of pricing. The techniques used allow for accurate modeling of the customer’s buying patterns including cross effects such as cannibalization and the halo effect. This study uses data from 2013 to 2019 for Super Premium Whiskey from a large distributor of alcoholic beverages. The expected demand and the ideal pricing strategy …