Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Social and Behavioral Sciences (74)
- Science and Technology Studies (72)
- Physical Sciences and Mathematics (33)
- Civil and Environmental Engineering (16)
- Environmental Sciences (16)
-
- Earth Sciences (15)
- Computer Engineering (8)
- Computer Sciences (6)
- Transportation Engineering (6)
- Electrical and Computer Engineering (5)
- Hydraulic Engineering (3)
- Mechanical Engineering (3)
- Water Resource Management (3)
- Aerospace Engineering (2)
- Aviation (2)
- Data Science (2)
- Data Storage Systems (2)
- Engineering Education (2)
- Environmental Health and Protection (2)
- Hydrology (2)
- Law (2)
- Medicine and Health Sciences (2)
- Natural Resources Management and Policy (2)
- Public Affairs, Public Policy and Public Administration (2)
- Public Health (2)
- Science and Technology Law (2)
- Aerodynamics and Fluid Mechanics (1)
- Aeronautical Vehicles (1)
- Agriculture (1)
- Institution
-
- University of Wollongong (93)
- University of Texas at Arlington (15)
- University of Kentucky (5)
- Technological University Dublin (4)
- Utah State University (4)
-
- Old Dominion University (3)
- University of South Carolina (3)
- Minnesota State University, Mankato (2)
- University of Colorado Law School (2)
- University of Nebraska - Lincoln (2)
- California Polytechnic State University, San Luis Obispo (1)
- Cleveland State University (1)
- Edith Cowan University (1)
- Elizabethtown College (1)
- Embry-Riddle Aeronautical University (1)
- Loyola University Chicago (1)
- University of Connecticut (1)
- University of Louisville (1)
- University of Vermont (1)
- Wayne State University (1)
- Whittier College (1)
- Publication Year
- Publication
-
- Faculty of Engineering and Information Sciences - Papers: Part A (56)
- Faculty of Engineering and Information Sciences - Papers: Part B (16)
- Earth & Environmental Sciences Datasets (13)
- Faculty of Engineering - Papers (Archive) (12)
- SMART Infrastructure Facility - Papers (9)
-
- Kentucky Transportation Center Research Report (5)
- Civil and Environmental Engineering Faculty Publications (3)
- Publications (3)
- Articles (2)
- Aviation Department Publications (2)
- Conference papers (2)
- Engineering Technology Faculty Publications (2)
- Civil and Environmental Engineering Faculty Research Publications (1)
- Coalbed Methane Development in the Intermountain West (April 4-5) (1)
- Computer Science and Engineering Datasets (1)
- Computer Science: Faculty Publications and Other Works (1)
- Daugherty Water for Food Global Institute: Faculty Publications (1)
- Engineering Datasets (1)
- Faculty Publications (1)
- Faculty Scholarship (1)
- Honors Scholar Theses (1)
- March 13, 2013: Regional Sea Level Rise Assessment, Adaptation and Flood Mitigation Projects (1)
- Mechanical Engineering Faculty Publications (1)
- Nebraska Agricultural Experiment Station: Historical Circulars (1)
- Research outputs 2014 to 2021 (1)
- STAR Program Research Presentations (1)
- Summer Scholarship, Creative Arts and Research Projects (SCARP) (1)
- UTA Libraries Datasets (1)
- Uncovering the Hidden Resource: Groundwater Law, Hydrology, and Policy in the 1990s (Summer Conference, June 15-17) (1)
- University of Vermont Transportation Research Center (1)
- File Type
Articles 1 - 30 of 144
Full-Text Articles in Engineering
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Whittier Scholars Program
The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.
Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi
Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi
Computer Science and Engineering Datasets
The CitDet dataset is composed of images captured at the USDA Agricultural Research Service Subtropical Insects and Horticulture Research Unit in Fort Pierce, FL, USA. Data was collected between October 2021 and October 2022. 579 images were captured from different sections of the orchard using the open-source application Field Book on Android tablets. While collecting images, we faced the camera in a portrait orientation directly centered on the tree of interest. All images were taken at the edge of the soil in the tree row to simulate a ground-based robot imaging the tree while moving between two rows of trees. …
Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth
Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth
Publications
Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …
The Infrastructure Metaverse Already Exists, Ankur Mitra, Ahmed Hassan, Mark Mulville
The Infrastructure Metaverse Already Exists, Ankur Mitra, Ahmed Hassan, Mark Mulville
Articles
The construction industry is currently undergoing a profound digital transformation, primarily driven by the innovative concept of digital twins. The United Kingdom's National Digital Twin Programme (NDTp) stands as a visionary initiative striving to establish a cohesive digital ecosystem wherein all forms of infrastructure, both existing and newly constructed, are replicated in the digital realm. Digital twins are not merely static visual representations; they serve as the cornerstone for a comprehensive information management framework that enables real-time data sharing. This data-sharing capability spans the entire lifecycle of construction projects. What makes this technology particularly powerful is its capacity to facilitate …
Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar
Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar
Engineering Technology Faculty Publications
Data science has gained the attention of various industries, educators, parents, and students thinking about their future careers. Statistics departments have traditionally offered data science courses for a long time. The main objective of these courses is to examine the fundamental concepts and theories. However, teaching data science courses has also expanded to other disciplines due to the vast amount of data being collected by numerous modern applications. Also, someone needs to learn how to collect and process data, especially from industrial devices, because of the recent development of Internet of Things (IoT) technologies. Hence, integrating data science into the …
Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel
Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel
Articles
In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated …
Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp
Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp
Engineering Technology Faculty Publications
The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …
Supplementary Information For "Understanding Mid-To Large Underground Leaks From Buried Pipelines As Affected By Soil And Atmospheric Conditions – Field Scale Experimental Study", Navodi J.R.R. Jayarathne, Kathleen M. Smits, Stuart N. Riddick, Daniel J. Zimmerle, Younki Cho, Michelle Schwartz, Fancy Cheptonui, Kevan Cameron, Peter Ronney
Supplementary Information For "Understanding Mid-To Large Underground Leaks From Buried Pipelines As Affected By Soil And Atmospheric Conditions – Field Scale Experimental Study", Navodi J.R.R. Jayarathne, Kathleen M. Smits, Stuart N. Riddick, Daniel J. Zimmerle, Younki Cho, Michelle Schwartz, Fancy Cheptonui, Kevan Cameron, Peter Ronney
Earth & Environmental Sciences Datasets
Reducing the amount of leaked natural gas (NG) from pipelines from production to use has become a high priority in efforts to cut anthropogenic emissions of methane and ensure public safety. However, tracking and evaluating NG pipeline leaks, especially at moderate to high flow rates, requires a better understanding of the leak from the source to the detector as well as more robust quantification methods. To better understand fugitive emissions from NG pipelines, we developed a field scale testbed that simulates mid and high-pressure gas leaks from belowground natural gas infrastructure. The system is equipped with subsurface, surface and atmospheric …
Replication Data For: Investigating Detection Probability Of Mobile Survey Solutions For Natural Gas Pipeline Leaks Under Different Atmospheric Conditions, Shanru Tian, Stuart Riddick, Younki Cho, Bell Clay, Daniel Zimmerle, Kathleen Smits
Replication Data For: Investigating Detection Probability Of Mobile Survey Solutions For Natural Gas Pipeline Leaks Under Different Atmospheric Conditions, Shanru Tian, Stuart Riddick, Younki Cho, Bell Clay, Daniel Zimmerle, Kathleen Smits
Earth & Environmental Sciences Datasets
The 2015 Paris agreement aims to cut greenhouse gas emissions and keep global temperature rise below 2 °C above pre-industrial levels. Reducing CH4 emissions from leaking pipelines presents a relatively achievable objective. While walking and driving surveys are commonly used to detect leaks, the detection probability (DP) is poorly characterized. This study aims to investigate how leak rates, survey distance and speed, and atmospheric conditions affect the DP in controlled belowground conditions with release rates of 0.5–8.5 g min−1. Results show that DP is highly influenced by survey speed, atmospheric stability, and wind speed. The average DP in Pasquill–Gifford stability …
Replication Data For: A Closer Look At Underground Natural Gas Pipeline Leaks Across The United States, Younki Cho, Kathleen M. Smits, Nathaniel L. Steadman, Bridget A. Ulrich, Clay S. Bell, Daniel J. Zimmerle
Replication Data For: A Closer Look At Underground Natural Gas Pipeline Leaks Across The United States, Younki Cho, Kathleen M. Smits, Nathaniel L. Steadman, Bridget A. Ulrich, Clay S. Bell, Daniel J. Zimmerle
Earth & Environmental Sciences Datasets
Underground natural gas (NG) pipeline leakage can result in methane (CH4) buildup and migration through the soil. What is not well understood in such scenarios is how the soil conditions affect the gas migration behavior, particularly in regard to the relative contributions of specific soil properties such as soil moisture content. The objective of this study was to investigate the effects of soil properties on CH4 concentration and migration from leaking underground NG pipelines. Site characteristics such as surface cover and spatial dimensions, soil samples, and gas concentration data were collected from over 70 gas leakage sites …
Replication Data For "Estimating Methane Emissions From Underground Natural Gas Pipelines Using An Atmospheric Dispersion-Based Method", Shanru Tian, Kathleen M. Smits, Younki Cho, Stuart Riddick, Daniel Zimmerle, Aidan Duggan
Replication Data For "Estimating Methane Emissions From Underground Natural Gas Pipelines Using An Atmospheric Dispersion-Based Method", Shanru Tian, Kathleen M. Smits, Younki Cho, Stuart Riddick, Daniel Zimmerle, Aidan Duggan
Earth & Environmental Sciences Datasets
Methane (CH4) leakage from natural gas (NG) pipelines poses an environmental, safety, and economic threat to the public. While previous leak detection and quantification studies focus on the aboveground infrastructure, the analysis of underground NG pipeline leak scenarios is scarce. Furthermore, no data from controlled release experiments have been published on the accuracy of methods used to (1) quantify emissions from an area source and (2) use these emissions to quantify the size of a subsurface leak. This proof-of-concept work uses CH4 mole fraction, as measured by a single gas sensor, as an input to a simple …
Performance Improvements In Inner Product Encryption, Serena Riback
Performance Improvements In Inner Product Encryption, Serena Riback
Honors Scholar Theses
Consider a database that contains thousands of entries of the iris biometric. Each entry identifies an individual, so it is especially important that it remains secure. However, searching for entries among an encrypted database proves to be a security problem - how should one search encrypted data without leaking any information to a potential attacker? The proximity searchable encryption scheme, as discussed in the work by Cachet et al., uses the notions of inner product encryption developed by Kim et al.. In this paper, we will focus on the efficiency of these schemes. Specifically, how the symmetry of the bilinear …
Ccrpc Bicycle Count Data Analysis And Count Program Design Strategies, Gregory Rowangould, Eliana Fox, Rose O'Brien, Julia Clarke
Ccrpc Bicycle Count Data Analysis And Count Program Design Strategies, Gregory Rowangould, Eliana Fox, Rose O'Brien, Julia Clarke
University of Vermont Transportation Research Center
In 2017, the Chittenden County Regional Planning Commission (CCRPC) completed the most recent update of the region’s Active Transportation Plan (ATP) with the goal of creating “a safe, comfortable, and connected regional network of pedestrian and bicycle routes that appeal to all ages and abilities”. Developing a “robust” bicycle count program was one of the key non-infrastructure recommendations in the ATP (CCRPC, 2017). The UVM Transportation Research Center (“TRC”) was contracted to evaluate current bicycle data collection efforts in the region, identify gaps and limitations and make recommendations on how to develop a comprehensive bicycle count program that could better …
Etherapy App Phase 2, Angelo Botticelli
Etherapy App Phase 2, Angelo Botticelli
Summer Scholarship, Creative Arts and Research Projects (SCARP)
The eTherapy app Phase 2 development cycle transformed the app to its next version. The app was designed to read motion sensor data to assist in Occupational Therapy and with phase 2, the app has been changed based on the feedback of prior testers. Phase 2 expanded upon the data storage and motion reading capabilities of the app. The landmark achievement of Phase 2 is the introduction of custom exercises where the therapist can store readings of their patient's motion data to make custom exercises which the patient can repeat.
Replication Data For: Characterization Of Grain-Size Distribution, Thermal Conductivity, And Gas Diffusivity In Variably Saturated Binary Sand Mixtures, C. T.K.K. Deepagoda, Kathleen Smits
Replication Data For: Characterization Of Grain-Size Distribution, Thermal Conductivity, And Gas Diffusivity In Variably Saturated Binary Sand Mixtures, C. T.K.K. Deepagoda, Kathleen Smits
Earth & Environmental Sciences Datasets
Characterization of differently textured porous materials, as well as different volumetric porous media mixtures, in relation to mass and heat transport is vital for many engineering and research applications. Functional relations describing physical (e.g., grain-size distribution, total porosity), thermal, and gas diffusion properties of porous media and mixtures are necessary to optimize the design of porous systems that involve heat and gas transport processes. However, only a limited number of studies provide characterization of soil physical, thermal, and gas diffusion properties and the functional relationships of these properties under varying soil water contents, especially for soil mixtures, complicating optimization efforts. …
Replication Data For: Effect Of Varying Atmospheric Conditions On Methane Boundary-Layer Development In A Free Flow Domain Interfaced With A Porous Media Domain, C. T.K.K. Deepagoda, Kathleen Smits
Replication Data For: Effect Of Varying Atmospheric Conditions On Methane Boundary-Layer Development In A Free Flow Domain Interfaced With A Porous Media Domain, C. T.K.K. Deepagoda, Kathleen Smits
Earth & Environmental Sciences Datasets
Mitigation of atmospheric emission of methane from leaky underground infrastructure is important for controlling the global anthropogenic greenhouse gas burden. Overexposure to methane may also cause occupational health problems in indoor/outdoor environments at the local scale. Subsurface soil conditions (e.g. soil heterogeneity) affect methane migration in soils while near-surface atmospheric boundary conditions (e.g. wind and temperature) affect off-site emissions across the soil-atmosphere interface. This study investigated the above-surface methane concentration boundary-layer development under different soil conditions (homogenous and layered) and atmospheric boundary controls (wind and temperature). A series of controlled bench-scale experiments was conducted using an open-loop boundary-layer wind tunnel …
Replication Data For: Thermal Conductivity Of Binary Sand Mixtures Evaluated Through Full Water Content Range, Benjamin Wallen, Kathleen Smits
Replication Data For: Thermal Conductivity Of Binary Sand Mixtures Evaluated Through Full Water Content Range, Benjamin Wallen, Kathleen Smits
Earth & Environmental Sciences Datasets
A soil's grain-size distribution affects its physical and hydraulic properties; however, little is known about its effect on soil thermal properties. To better understand how grain-size distribution affects soil thermal properties, specifically the effective thermal conductivity, a set of laboratory experiments was performed using binary mixtures of two uniform sands tightly packed with seven different mixing fractions over the full range of saturation. For each binary mixture, the effective thermal conductivity, λ, capillary pressure, hc, and volumetric water content, θ, were measured. Results demonstrated that the λ–θ relationship exhibited distinct characteristics based on the percentage of fine- and coarse-grained sands. …
Replication Data For: Evaporation From Undulating Soil Surfaces Under Turbulent Airflow Through Numerical And Experimental Approaches, Bo Gao, Kathleen Smits, John Farnsworth
Replication Data For: Evaporation From Undulating Soil Surfaces Under Turbulent Airflow Through Numerical And Experimental Approaches, Bo Gao, Kathleen Smits, John Farnsworth
Earth & Environmental Sciences Datasets
Evaporation from undulating soil surfaces is rarely studied due to limited modeling theory and inadequate experimental data linking dynamic soil and atmospheric interactions. The goal of this paper is to provide exploratory insights into evaporation behavior from undulating soil surfaces under turbulent conditions through numerical and experimental approaches. A previously developed and verified coupled free flow and porous media flow model was extended by incorporating turbulent airflow through Reynolds-averaged Navier–Stokes equations. The model explicitly describes the relevant physical processes and the key properties in the free flow, porous media, and at the interface, allowing for the analysis of coupled exchange …
Replication Data For: Effect Of Subsurface Soil Moisture Variability And Atmospheric Conditions On Methane Gas Migration In Shallow Subsurface, C. T.K.K. Deepagoda, Kathleen Smits
Replication Data For: Effect Of Subsurface Soil Moisture Variability And Atmospheric Conditions On Methane Gas Migration In Shallow Subsurface, C. T.K.K. Deepagoda, Kathleen Smits
Earth & Environmental Sciences Datasets
A major concern resulting from the increased use and production of natural gas has been how to mitigate fugitive greenhouse gas emissions (predominantly methane) from natural gas infrastructure (e.g., leaky shallow pipelines). Subsurface migration and atmospheric loading of methane from pipeline leakage is controlled by source configurations and subsurface soil conditions (e.g., soil heterogeneity and soil moisture) and are further affected by atmospheric conditions (e.g., wind and temperature). However, the transport and attenuation of methane under varying subsurface and atmospheric conditions are poorly understood, making it difficult to estimate leakage fluxes from methane concentration measurements at and above the soil …
Replication Data For: Evaluation Of Model Concepts To Describe Water Transport In Shallow Subsurface Soil And Across The Soil–Air Interface, Zhen Li, Kathleen Smits
Replication Data For: Evaluation Of Model Concepts To Describe Water Transport In Shallow Subsurface Soil And Across The Soil–Air Interface, Zhen Li, Kathleen Smits
Earth & Environmental Sciences Datasets
Soil water evaporation plays a critical role in mass and energy exchanges across the land–atmosphere interface. Although much is known about this process, there is no agreement on the best modeling approaches to determine soil water evaporation due to the complexity of the numerical modeling scenarios and lack of experimental data available to validate such models. Existing studies show numerical and experimental discrepancies in the evaporation behavior and soil water distribution in soils at various scales, driving us to revisit the key process representation in subsurface soil. Therefore, the goal of this work is to test different mathematical formulations used …
Replication Data For: The Effect Of The Top Soil Layer On Moisture And Evaporation Dynamics, Zhen Li, Kathleen Smits
Replication Data For: The Effect Of The Top Soil Layer On Moisture And Evaporation Dynamics, Zhen Li, Kathleen Smits
Earth & Environmental Sciences Datasets
Understanding the effect of the top soil layer on surface evaporation and water distribution is critical to modeling hydrological systems. However, the dependency of near-surface soil moisture and fluxes on layering characteristics remains unclear. To address this uncertainty, we investigate how the arrangement of soil horizons affects the evaporation and soil moisture, specifically, the near-surface soil moisture, through the combination of numerical simulations and evaporation experiments. The characteristics of fluxes and moisture from different soil profiles are then used to understand the soil layering conditions. Results show that the top soil layer can significantly affect the evolution of soil moisture …
Replication Data For: Study Of Methane Migration In The Shallow Subsurface From A Gas Pipe Leak, Kathleen Smits
Replication Data For: Study Of Methane Migration In The Shallow Subsurface From A Gas Pipe Leak, Kathleen Smits
Earth & Environmental Sciences Datasets
With the increased use of natural gas, safety and environmental concerns from underground leaking natural gas pipelines are becoming more widespread. What is not well understood in leakage incidents is how the soil conditions affect gas migration behavior, making it difficult to estimate the gas distribution. To shed light on these concerns, an increased understanding of subsurface methane migration after gas release is required to support efficient leak response and effective use of available technologies. In this study, three field-scale experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of soil …
Kinetic Study Of Product Distribution Using Various Data-Driven And Statistical Models For Fischer-Tropsch Synthesis, Yixiao Wang, Jing Hu, Xiyue Zhang, Abubakar Yusuf, Binbin Qi, Huan Jin, Yiyang Liu, Jun He, Yunshan Wang, Gang Yang, Yong Sun
Kinetic Study Of Product Distribution Using Various Data-Driven And Statistical Models For Fischer-Tropsch Synthesis, Yixiao Wang, Jing Hu, Xiyue Zhang, Abubakar Yusuf, Binbin Qi, Huan Jin, Yiyang Liu, Jun He, Yunshan Wang, Gang Yang, Yong Sun
Research outputs 2014 to 2021
Three modeling techniques, namely, a radial basis function neural network (RBFNN), a comprehensive kinetic with genetic algorithm (CKGA), and a response surface methodology (RSM), were used to study the kinetics of Fischer-Tropsch (FT) synthesis. Using a 29 × 37 (4 independent process parameters as inputs and corresponding 36 responses as outputs) matrix with total 1073 data sets for data training through RBFNN, the established model is capable of predicting hydrocarbon product distribution i.e., the paraffin formation rate (C2-C15) and the olefin to paraffin ratio (OPR) within acceptable uncertainties. With additional validation data sets (15 × 36 matrix with total 540 …
Replication Data For: Comparing Teamwork & Collaboration Competencies Between A Technology In Art Education Course And An Engineering Project Management Course, Martin Wallace, Ryan Hulla
Replication Data For: Comparing Teamwork & Collaboration Competencies Between A Technology In Art Education Course And An Engineering Project Management Course, Martin Wallace, Ryan Hulla
UTA Libraries Datasets
This data was collected over two academic years, 2018/19 and 2019/20 from students enrolled in two courses at UTA: ART 4365 Technology in Art Education and IE 4340 Engineering Project Management. The data collection instruments were pre- and post-self assessment surveys, distributed at the beginning and end of the semester. The data includes student-self reported competencies for Maker Competencies 9 and 10, "Assembles Effective Teams" and "Collaborates Effectively" on a range of 1 (low) to 5 (high).
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Publications
The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis …
A Pulse-Decay Method For Low Permeability Analyses Of Granular Porous Media: Mathematical Solutions And Experimental Methodologies, Quinhong Hu
Earth & Environmental Sciences Datasets
This dataset is for a manuscript titled "A pulse-decay method for low permeability analyses of granular porous media: Mathematical solutions and experimental methodologies" being reviewed by Water Resources Research, a journal of American Geophysical Union and Wiley (2020-07-29)
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Faculty Scholarship
AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. The data science community has to work on collecting and aggregating such data in a common and widely available format, so that any AI researcher can easily look up the applicable limit measurements for their latest project. AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. Data science community has to work on collecting and …
Developing A Taxonomy For Success In Commercial Pilot Behaviors, Kristine Kiernan, David S. Cross, Mark Scharf Ph.D.
Developing A Taxonomy For Success In Commercial Pilot Behaviors, Kristine Kiernan, David S. Cross, Mark Scharf Ph.D.
Publications
Human error has been well studied in aviation. However, less is known about the ways in which human performance maintains and contributes to aviation safety. The lack of data on positive human performance prevents consideration of the full range of human behaviors when making safety and risk management decisions. The concept of resilient performance provides a framework to understand and classify positive human behaviors. Through interviews with commercial airline pilots, this study examined routine airline operations to evaluate the concept of resilient performance and to develop a taxonomy for success. The four enablers of resilient performance, anticipation, learning, responding, and …
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam
Faculty of Engineering and Information Sciences - Papers: Part B
Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …
On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin
On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin
Faculty of Engineering and Information Sciences - Papers: Part B
Smart meter electricity data presents privacy risks when malicious agents gain insights of private information, including residents’ lifestyle and daily habits. When allowing access to record-level data, we apply the multiplicative noise method to mask individual smart meter data, which simultaneously aims to minimise disclosure of a dwelling’s consumption signal to any third party and to enable accurate estimation of the sum of a cluster of households. Three testing criteria are introduced to measure the performance of multiplicative noise masking approach relevant to the smart meter data. We propose a novel ‘Twin Uniform’ noise distribution and derive relevant theoretical results. …