Computational Engineering Commons^™

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 …

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 …

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 …

Hybrid Modelling For Stroke Care: Review And Suggestions Of New Approaches For Risk Assessment And Simulation Of Scenarios, Tilda Herrgårdh, Vince I. Madai, John Kelleher, Rasmus Magnusson, Mika Gustafsson, Lili Milani, Peter Gennemark, Gunnar Cedersund

Articles

Stroke is an example of a complex and multi-factorial disease involving multiple organs, timescales, and disease mechanisms. To deal with this complexity, and to realize Precision Medicine of stroke, mathematical models are needed. Such approaches include: 1) machine learning, 2) bioinformatic network models, and 3) mechanistic models. Since these three approaches have complementary strengths and weaknesses, a hybrid modelling approach combining them would be the most beneficial. However, no concrete approach ready to be implemented for a specific disease has been presented to date. In this paper, we both review the strengths and weaknesses of the three approaches, and propose …

Renewable Energy Production By Solar Chimney: The Influence Of Curved Guide Vanes On The Performance Of A Solar Chimney Using Cfd Simulation, Haokun Xue

Theses, Dissertations and Capstones

The aim of this study is to investigate the effect of the guide vanes on the efficiency of the turbine of solar chimney power plant using Computational Fluid Dynamics (CFD). In this study, a 3-Dimentional CFD simulation of solar chimney power plant based on the Manzanares prototype is performed. The CFD simulation is validated by comparing the experimental data from the Manzanares prototype and simulation data with both 2D and 3D cases. To capture turbulent flow inside the chimney, the SST 𝑘 − 𝜔 turbulence model is used. The first object is to investigate the flow performance under the influence …

The Diffuse Bounce Back Lattice Boltzmann Method And Its Applications On The Study Of Fluid-Particle Interactions, Geng Liu

Dissertations and Theses

Fluid-structure interaction is very broadly seen and widely used in many industrial, engineering and environmental processes. The lattice Boltzmann method has been preferred for simulating particulate flows due to its advantages of easy implementation, micro- and mesoscopic physical insights and parallel algorithm. Both sharp and diffuse boundary treatments are studied to recover curved and moving boundaries on structured orthogonal grids for the lattice Boltzmann method. These methods can describe curved boundaries more accurately and more smoothly than the naive staircase approximation. However, to improve the order of velocity accuracy and to reduce the fluctuation of force, either interpolation or additional …

Inclusive Access For All, Marcia Dority Baker, Jaci Lindburg

Information Technology Services: Publications

Inclusive Access provides a framework for digital course material delivered via the learning management system (LMS) day-one to students. This platform assists instructors with selecting current, quality, affordable material, and supports learning analytics by providing engagement data in Canvas. The University of Nebraska Provost office has funded an initial series of grants to support open educational resources (OER) initiatives at the Lincoln, Kearney, and Omaha campuses for several years. The vast majority of these dollars went to incentivize faculty in the adoption of OER. The OER and Inclusive Access pilots are ready to mature into a service supported by Academic …

Computational Analysis And Prediction Of Intrinsic Disorder And Intrinsic Disorder Functions In Proteins, Akila I. Katuwawala

Theses and Dissertations

COMPUTATIONAL ANALYSIS AND PREDICTION OF INTRINSIC DISORDER AND INTRINSIC DISORDER FUNCTIONS IN PROTEINS

By Akila Imesha Katuwawala

A dissertation submitted in partial fulfillment of the requirements for the degree of Engineering, Doctor of Philosophy with a concentration in Computer Science at Virginia Commonwealth University.

Virginia Commonwealth University, 2021

Director: Lukasz Kurgan, Professor, Department of Computer Science

Proteins, as a fundamental class of biomolecules, have been studied from various perspectives over the past two centuries. The traditional notion is that proteins require fixed and stable three-dimensional structures to carry out biological functions. However, there is mounting evidence regarding a “special” class …

Preference-Aware Task Assignment In Mobile Crowdsensing, Fatih Yucel

Theses and Dissertations

Mobile crowdsensing (MCS) is an emerging form of crowdsourcing, which facilitates the sensing data collection with the help of mobile participants (workers). A central problem in MCS is the assignment of sensing tasks to workers. Existing work in the field mostly seek a system-level optimization of task assignments (e.g., maximize the number of completed tasks, minimize the total distance traveled by workers) without considering individual preferences of task requesters and workers. However, users may be reluctant to participate in MCS campaigns that disregard their preferences. In this dissertation, we argue that user preferences should be a primary concern in the …

Towards A Holistic Risk Model For Safeguarding The Pharmaceutical Supply Chain: Capturing The Human-Induced Risk To Drug Quality, Heather R. Campbell

Theses and Dissertations--Pharmacy

Counterfeit, adulterated, and misbranded medicines in the pharmaceutical supply chain (PSC) are a critical problem. Regulators charged with safeguarding the supply chain are facing shrinking resources for inspections while concurrently facing increasing demands posed by new drug products being manufactured at more sites in the US and abroad. To mitigate risk, the University of Kentucky (UK) Central Pharmacy Drug Quality Study (DQS) tests injectable drugs dispensed within the UK hospital. Using FT-NIR spectrometry coupled with machine learning techniques the team identifies and flags potentially contaminated drugs for further testing and possible removal from the pharmacy. Teams like the DQS are …

Impacts Of Using Tubular Sections In Open Web Steel Joists, Hollis (Cas) L. Caswell V

Honors Theses

Open web steel joists are lightweight structural trusses used in place of I-beams to support long-span floors and roofs of open space buildings. Their slender geometry makes them highly efficient in resisting flexure, but susceptible to out-of-plane buckling in a failure mode known as lateral-torsional buckling. This failure can be avoided by running lateral bracing between joists called bridging or potentially by using tubular sections to build up the joists rather than angle sections.

It is possible that a joist design using tubular cross-sections could require less bridging and prevent the need to use erection bridging for initial joist construction. …

Water Surfaces Detection From Sentinel-1 Sar Images Using Deep Learning, Chao Huang Lin

All Master's Theses

Nowadays, Synthetic Aperture Radar (SAR) images have been widely used in the industry and the scientific community for different remote sensing applications. The main advantage of SAR technology is that it can acquire images from nighttime since it does not require sunlight. Additionally, it can capture images under the cloud where the traditional optical sensor is limited. It is very convenient to use SAR image for surface water detection because the flatness of the calm water surface reflects off all the energy from the radar and this makes the surface water appears in a SAR image as dark pixels. The …

Bias And Fairness Of Evasion Attacks In Image Perturbation, Sichong Qin

All Master's Theses

When talking about protecting privacy of personal images, adversarial attack methods play key roles. These methods are created to protect against the unauthorized usage of personal images. Such methods protect personal privacy by adding some amount of perturbations, otherwise known as "noise", to input images to enhance privacy protection. Fawkes in Clean Attack method is one adversarial machine learning approach aimed at protecting personal privacy against abuse of personal images by unauthorized AI systems. In leveraging the Fawkes in Evasion Attack method and through running additional experiments against the Fawkes system, we were able to prove that the effectiveness of …

Visualization For Solving Non-Image Problems And Saliency Mapping, Divya Chandrika Kalla

All Master's Theses

High-dimensional data play an important role in knowledge discovery and data science. Integration of visualization, visual analytics, machine learning (ML), and data mining (DM) are the key aspects of data science research for high-dimensional data. This thesis is to explore the efficiency of a new algorithm to convert non-images data into raster images by visualizing data using heatmap in the collocated paired coordinates (CPC). These images are called the CPC-R images and the algorithm that produces them is called the CPC-R algorithm. Powerful deep learning methods open an opportunity to solve non-image ML/DM problems by transforming non-image ML problems into …

Bibliometric Analysis Of Plant Disease Prediction Using Climatic Condition, Shivali Amit Wagle, Harikrishnan R

Library Philosophy and Practice (e-journal)

The changes in the climatic conditions are having beneficial as well as harmful effects on crop yields depending on the drastic changes. There can be a yield loss due to the occurrence of disease in crops. Apart from severe yield losses, infected yield can be harmful and threatening to living being’s health as that is the source of food. This also affects the economy of the agricultural depended country. Disease prediction tools advance in the management of exertions for diseases in plants. Machine learning techniques help in elucidating complex associations between hosts and pathogens without invoking difficult-to-satisfy expectations. For the …

Novel Methods In Computational Imaging With Applications In Remote Sensing, Adam Webb

Dissertations, Master's Theses and Master's Reports

This dissertation is devoted to novel computational imaging methods with applications in remote sensing. Computational imaging methods are applied to three distinct applications including imaging and detection of buried explosive hazards utilizing array radar, high resolution imaging of satellites in geosynchronous orbit utilizing optical hypertelescope arrays, and characterization of atmospheric turbulence through multi-frame blind deconvolution utilizing conventional optical digital sensors.

The first application considered utilizes a radar array employed as a forward looking ground penetrating radar system with applications in explosive hazard detection. A penalized least squares technique with sparsity-inducing regularization is applied to produce imagery, which is consistent with …

Computational Decision Support For The Covid-19 Healthcare Coalition, Andreas Tolk, Christopher Glazner, Joseph Ungerleider

VMASC Publications

In the early months of 2020, the SARS-CoV-2 Coronavirus took the world by surprise, resulting in the COVID-19 pandemic that has caused significant loss of lives and challenged the sustainability of our health care systems. In mid-March, it became obvious that government and communities had to react immediately. Under the lead of the Mayo Clinic and The MITRE Corporation, the COVID-19 Healthcare Coalition (C19HCC) was established as a coordinated public-interest, private-sector response. The coalition brought healthcare organizations, technology firms, nonprofits, academia, and startups to support supply chains, inform coordinated social policies, and provide data-driven insights to protect people and preserve …

Review Of Forecasting Univariate Time-Series Data With Application To Water-Energy Nexus Studies & Proposal Of Parallel Hybrid Sarima-Ann Model, Cory Sumner Yarrington

Graduate Theses, Dissertations, and Problem Reports (ETD)

The necessary materials for most human activities are water and energy. Integrated analysis to accurately forecast water and energy consumption enables the implementation of efficient short and long-term resource management planning as well as expanding policy and research possibilities for the supportive infrastructure. However, the integral relationship between water and energy (water-energy nexus) poses a difficult problem for modeling. The accessibility and physical overlay of data sets related to water-energy nexus is another main issue for a reliable water-energy consumption forecast. The framework of urban metabolism (UM) uses several types of data to build a global view and highlight issues …

Support To Design For Air Traffic Management: An Approach With Agent-Based Modelling And Evolutionary Search, Gabriella Gigante, Roberto Palumbo, Domenico Pascarella, Alessandro Pellegrini, Gabriella Duca, Miquel Angel Piera, Juan José Ramos

International Journal of Aviation, Aeronautics, and Aerospace

This paper presents a methodology to manage the support to design in ATM operations. We propose a workflow for the design of ATM solutions in a performance-based setting. The methodology includes the evaluation of the impact on human behaviour and exploits a combination of different paradigms, such as Agent-Based Modelling and Simulation, and Agent-Based Evolutionary Search. We prove the soundness of the methodology by carrying out a real case study, which is the transition from Direct Routing to Free Routing in the Italian airspace. The validation results exhibit limited errors for the assessment of the performance metrics under evaluation. Furthermore, …

Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani

College of Graduate Studies: Theses & Dissertations

Pneumonia is one of the leading causes of infections in the lung area and deaths worldwide. The mortality rate is 24.8% for patients over 70 years of age due to other health complications present along with it. In least fortunate countries, pneumonia can often times go untreated because of how cost extensive it is to diagnose, especially severe cases that cannot be seen by a plain X-ray. Other scanning methods can find the lung abnormality but are time-extensive and not cost effective. An autonomous approach however can help aid diagnosing pneumonia with a plain X-ray scan due to the structural …

Interactive Visual Self-Service Data Classification Approach To Democratize Machine Learning, Sridevi Narayana Wagle

All Master's Theses

Machine learning algorithms often produce models considered as complex black-box models by both end users and developers. Such algorithms fail to explain the model in terms of the domain they are designed for. The proposed Iterative Visual Logical Classifier (IVLC) is an interpretable machine learning algorithm that allows end users to design a model and classify data with more confidence and without having to compromise on the accuracy. Such technique is especially helpful when dealing with sensitive and crucial data like cancer data in the medical domain with high cost of errors. With the help of the proposed interactive and …

An Accurate And Efficient Methodology To Obtain Surges For Risk Analyses For The Coast Of Bangladesh, A S M Alauddin Al Azad

UNF Graduate Theses and Dissertations

Bangladesh is one of the worst affected countries in the world in terms of tropical cyclone and storm surge effects. Until now, most of the research on annual exceedance of flood elevation for the coast of Bangladesh was based upon historical cyclone tracks along the coast. One of the major constraints of using historical tracks or tide gauge data to determine the annual exceedance of surge elevation is that the available sample size is often inadequate to capture the broad range of storm characteristics over the geographic region of interest. Over the years, several methods have been developed to increase …

Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …