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Articles 421 - 450 of 2904
Full-Text Articles in Engineering
Images.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Images.Zip, Ananad K. Nambisan, Norsang Lama, Jason Hagerty, Colin Smith, Ahmad Rajeh, Thanh Phan, Samantha Swinfard, R. Joe Stanley
Deep Learning-based Dot and Globule Segmentation with Pixel and Blob-based Metrics for Evaluation – Data
No abstract provided.
Effects Of Different Crash Data Variables On Ems Response Time For A Rural County In Alabama, Sneha R. Vanga, Phillip M. Ligrani, Mehrnaz Doustmohammadi, Michael Anderson
Effects Of Different Crash Data Variables On Ems Response Time For A Rural County In Alabama, Sneha R. Vanga, Phillip M. Ligrani, Mehrnaz Doustmohammadi, Michael Anderson
PRC-Affiliated Research
Response time of Emergency Medical Services (EMS) is an important factor related to preventable deaths in road crash incidents. This study focuses on analyzing the effects of different independent variables on the EMS Response Time (ERT). Independent variables considered for this investigation are travel time, day of the week, crash severity, weather, time of the day, and lighting condition. Understanding outcomes resulting from variations of the considered parameters on ERT is crucial to minimize the possibility of adverse outcomes which are tied to different types of injuries, and vital to limit the prospect of fatalities. Crash data used for this …
Bcse: Blockchain-Based Trusted Service Evaluation Model Over Big Data, Fengyin Li, Xinying Yu, Rui Ge, Yanli Wang, Yang Cui, Huiyu Zhou
Bcse: Blockchain-Based Trusted Service Evaluation Model Over Big Data, Fengyin Li, Xinying Yu, Rui Ge, Yanli Wang, Yang Cui, Huiyu Zhou
Big Data Mining and Analytics
The blockchain, with its key characteristics of decentralization, persistence, anonymity, and auditability, has become a solution to overcome the overdependence and lack of trust for a traditional public key infrastructure on third-party institutions. Because of these characteristics, the blockchain is suitable for solving certain open problems in the service-oriented social network, where the unreliability of submitted reviews of service vendors can cause serious security problems. To solve the unreliability problems of submitted reviews, this paper first proposes a blockchain-based identity authentication scheme and a new trusted service evaluation model by introducing the scheme into a service evaluation model. The new …
Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu
Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu
Big Data Mining and Analytics
With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …
Exploiting More Associations Between Slots For Multi-Domain Dialog State Tracking, Hui Bai, Yan Yang, Jie Wang
Exploiting More Associations Between Slots For Multi-Domain Dialog State Tracking, Hui Bai, Yan Yang, Jie Wang
Big Data Mining and Analytics
Dialog State Tracking (DST) aims to extract the current state from the conversation and plays an important role in dialog systems. Existing methods usually predict the value of each slot independently and do not consider the correlations among slots, which will exacerbate the data sparsity problem because of the increased number of candidate values. In this paper, we propose a multi-domain DST model that integrates slot-relevant information. In particular, certain connections may exist among slots in different domains, and their corresponding values can be obtained through explicit or implicit reasoning. Therefore, we use the graph adjacency matrix to determine the …
Sampling With Prior Knowledge For High-Dimensional Gravitational Wave Data Analysis, He Wang, Zhoujian Cao, Yue Zhou, Zong-Kuan Guo, Zhixiang Ren
Sampling With Prior Knowledge For High-Dimensional Gravitational Wave Data Analysis, He Wang, Zhoujian Cao, Yue Zhou, Zong-Kuan Guo, Zhixiang Ren
Big Data Mining and Analytics
Extracting knowledge from high-dimensional data has been notoriously difficult, primarily due to the so-called "curse of dimensionality" and the complex joint distributions of these dimensions. This is a particularly profound issue for high-dimensional gravitational wave data analysis where one requires to conduct Bayesian inference and estimate joint posterior distributions. In this study, we incorporate prior physical knowledge by sampling from desired interim distributions to develop the training dataset. Accordingly, the more relevant regions of the high-dimensional feature space are covered by additional data points, such that the model can learn the subtle but important details. We adapt the normalizing flow …
Toward Intelligent Financial Advisors For Identifying Potential Clients: A Multitask Perspective, Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu
Toward Intelligent Financial Advisors For Identifying Potential Clients: A Multitask Perspective, Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu
Big Data Mining and Analytics
Intelligent Financial Advisors (IFAs) in online financial applications (apps) have brought new life to personal investment by providing appropriate and high-quality portfolios for users. In real-world scenarios, identifying potential clients is a crucial issue for IFAs, i.e., identifying users who are willing to purchase the portfolios. Thus, extracting useful information from various characteristics of users and further predicting their purchase inclination are urgent. However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. In this study, we formalize a potential conversion relationship, i.e., user→activated user→client and decompose this relationship into …
A Comparison Of Computational Approaches For Intron Retention Detection, Jiantao Zheng, Cuixiang Lin, Zhenpeng Wu, Hong-Dong Li
A Comparison Of Computational Approaches For Intron Retention Detection, Jiantao Zheng, Cuixiang Lin, Zhenpeng Wu, Hong-Dong Li
Big Data Mining and Analytics
Intron Retention (IR) is an alternative splicing mode through which introns are retained in mature RNAs rather than being spliced in most cases. IR has been gaining increasing attention in recent years because of its recognized association with gene expression regulation and complex diseases. Continuous efforts have been dedicated to the development of IR detection methods. These methods differ in their metrics to quantify retention propensity, performance to detect IR events, functional enrichment of detected IRs, and computational speed. A systematic experimental comparison would be valuable to the selection and use of existing methods. In this work, we conduct an …
Field Retrofit And Testing Of A Corroded Metal Culvert Using Gfrp, Mahmoud Reda Taha, Susan Bogus, Mohammed Abdellatef, Daniel Heras Murcia
Field Retrofit And Testing Of A Corroded Metal Culvert Using Gfrp, Mahmoud Reda Taha, Susan Bogus, Mohammed Abdellatef, Daniel Heras Murcia
Data
One of the current pressing problem for all DOTs is the corrosion-oriented deterioration of the existing metal culverts. These metal culverts typically are designed for a life of 50 years. However, corrosion is making them last no longer than 30years. Here we propose use of Glass Fiber Reinforced Polymers (GFRP) pipe section as a fit-in GFRP profile liner for complete repair and rehabilitation of the corroded metal culvert with an expected life of 75 years. This is mainly because of the corrosion free nature of the GFRP material. In the current study, the design method for using glass fiber-reinforced polymer …
Experimental Study Of Turbulent Flow Heat Transfer And Pressure Loss Over Surfaces With Dense Micro-Depth Dimples Under Viscous Sublayer, Peng Zhang, Yu Rao, Phillip M. Ligrani
Experimental Study Of Turbulent Flow Heat Transfer And Pressure Loss Over Surfaces With Dense Micro-Depth Dimples Under Viscous Sublayer, Peng Zhang, Yu Rao, Phillip M. Ligrani
PRC-Affiliated Research
Presented are experimentally-measured heat transfer and pressure loss characteristics for dimpled surfaces, placed along one surface of a channel, with different ratios of dimple depth to channel height δ/H, and for Reynolds numbers ranging from 10,000 to 70,000. With the same relative dimple spacing to dimple print diameter, and the same ratio of dimple depth to dimple print diameter of δ/d = 0.20, experimental results for arrays of spherical indentation dimples with micro depths of δ = 0.6 and 1.0 mm (δ/H = 0.03 and 0.05) are compared with thermal characteristics for arrays of larger dimples with δ = 4.0 …
Flow And Heat Transfer Characteristics In A Pre-Swirl Rotor-Stator Cavity, Xiaoyu Yang, Zhong Ren, Jing Ren, Philip M. Ligrani
Flow And Heat Transfer Characteristics In A Pre-Swirl Rotor-Stator Cavity, Xiaoyu Yang, Zhong Ren, Jing Ren, Philip M. Ligrani
PRC-Affiliated Research
The present study investigates flow and heat transfer characteristics in a rotor-stator pre-swirl system. Considered are rotational Reynolds numbers ReФ ranging from 3.4 × 105 to 6.8 × 105, with jet Reynolds numbers Rew of approximately 8.8 × 104 to 3.81 × 105, and associated turbulent flow parameter λT = Cw/ReФ0.8 varying from 0 to 0.4. Experimentally-measured and numerically-predicted results illustrate the combined and separate influences of jet impingement and rotor entrainment, as they affect and govern flow and heat transfer characteristics within the cavity. These results show that the relative strength of the two effects varies with ReФ and …
Flow Structure And Surface Heat Transfer From Numerical Predictions For A Double Wall Effusion Plate With Impingement Jet Array Cooling, Hwabhin Kwon, Phillip M. Ligrani, Sneha Reddy Vanga, Heesung Park
Flow Structure And Surface Heat Transfer From Numerical Predictions For A Double Wall Effusion Plate With Impingement Jet Array Cooling, Hwabhin Kwon, Phillip M. Ligrani, Sneha Reddy Vanga, Heesung Park
PRC-Affiliated Research
To provide additional understanding of double wall cooling arrangements, especially local distributions of flow properties which are responsible for hot-side surface and cold-side surface heat transfer variations, investigated are numerically-simulated distributions of turbulent flow structural characteristics. Also considered are numerically-simulated surface heat transfer characteristics, including comparisons with experimentally-measured distributions. The numerical results are obtained using the ANSYS FLUENT Version 19.1 numerical code, with a k-ω SST turbulence model. The present arrangement includes a full-coverage effusion cooling plate, with coolant initially supplied by an impingement jet array. Considered are the effects of effusion blowing ratio, impingement jet Reynolds number, and streamwise …
Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang
Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
In recent years, there are such significant improvements on the performance and efficiency of big data technology and system. As it is widely applied in various fields, big data has empowered industrial intelligence, and is the key step into the intelligent stage of information society. Therefore, we are facing greater challenges nowadays, such as the paradox of data flooding and high-value data lacking, the complexity and uncertainty of big data analysis, and the difficulty to balance the data on sharing and circulation, and trustworthiness and security. Moreover, these challenges will not only promote the innovation and change of big data …
Ems Response Time Analyses For A Rural County Using Geographically Weighted Regression With Different Kernel Weighting Functions, Sneha R. Vanga, Phillip M. Ligrani, Mehrnaz Doustmohammadi, Michael Anderson
Ems Response Time Analyses For A Rural County Using Geographically Weighted Regression With Different Kernel Weighting Functions, Sneha R. Vanga, Phillip M. Ligrani, Mehrnaz Doustmohammadi, Michael Anderson
PRC-Affiliated Research
A Geographically Weighted Regression (GWR) is considered to compare results provided using two different kernel weighting functions: adaptive bi-square kernel and adaptive Gaussian kernel. To provide a baseline reference comparison, resulting data are also considered relative to Global Regression Analysis (GRA) calculations, which are obtained without the inclusion of geographical variability location data. For the analysis, data associated with a total of 214 crash cases for the dates between January 2016 and December 2019 are studied for a rural county in Alabama. Associated crash records are extracted from the Critical Analysis Reporting Environment (CARE) database. Six independent variables, including travel …
Characterization Of Effective Diffusion Within Viscoelastic Fluids With Elastic Instabilities, Valerie Hietsch, Phillip Ligrani, Mengying Su
Characterization Of Effective Diffusion Within Viscoelastic Fluids With Elastic Instabilities, Valerie Hietsch, Phillip Ligrani, Mengying Su
PRC-Affiliated Research
We considered effective diffusion, characterized by magnitudes of effective diffusion coefficients, in order to quantify mass transport due to the onset and development of elastic instabilities. Effective diffusion coefficient magnitudes were determined using different analytic approaches, as they were applied to tracked visualizations of fluorescein dye front variations, as circumferential advection was imposed upon a flow environment produced using a rotating Couette flow arrangement. Effective diffusion coefficient results were provided for a range of flow shear rates, which were produced using different Couette flow rotation speeds and two different flow environment fluid depths. To visualize the flow behavior within the …
Modeling Crash Severity And Collision Types Using Machine Learning, Amit Kumar, Hari Krishnan Melempat Kalapurayil
Modeling Crash Severity And Collision Types Using Machine Learning, Amit Kumar, Hari Krishnan Melempat Kalapurayil
Data
Traffic safety analysis is the fundamental step for reducing economic, social, and environmental cost incurred due to traffic accidents. The essence of traffic safety is understanding the factors affecting crash occurrence, injury severity and collision type and their underlying relationships and predict-prevent future crash instances. Crash injury severity studies in past have utilized numerous statistical, econometric and Machine Learning (ML) and Artificial Intelligence (AI) tools to extract the underlying relationship between the crash causal factors and the consequent severity or collision type. The study aims to explore the Multi-Label Classification (MLC) tool from the domain of Artificial Intelligence (AI) for …
Moisture Content Prediction In Polymer Composites Using Machine Learning Techniques, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Moisture Content Prediction In Polymer Composites Using Machine Learning Techniques, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
The principal objective of this study is to employ non-destructive broadband dielectric spectroscopy/impedance spectroscopy and machine learning techniques to estimate the moisture content in FRP composites under hygrothermal aging. Here, classification and regression machine learning models that can accurately predict the current moisture saturation state are developed using the frequency domain dielectric response of the composite, in conjunction with the time domain hygrothermal aging effect. First, to categorize the composites based on the present state of the absorbed moisture supervised classification learning models (i.e., quadratic discriminant analysis (QDA), support vector machine (SVM), and artificial neural network-based multilayer perceptron (MLP) classifier) …
Dielectric State Variables As Qualitative Indicators Of Moisture Absorption-Caused Mechanical Property Degradation In Gfrp Composite Structures, Partha Pratim Das, Vamsee Vadlamudi, Rassel Raihan
Dielectric State Variables As Qualitative Indicators Of Moisture Absorption-Caused Mechanical Property Degradation In Gfrp Composite Structures, Partha Pratim Das, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
Fiber reinforced polymer (FRP) composites are being used in numerous fields owing to their intrinsic strength to weight ratio and various design benefits. However, these materials are prone to environmental aging, particularly moisture absorption. In essence, absorbed moisture infiltrates the polymer matrix and induces changes in the polymer network through chain scission, plasticization, and other bonding interactions. This causes irreversible damages to the material and significantly decreases mechanical strength. In this study, Broadband Dielectric Spectroscopy (BbDS) has been used to identify the absorption mechanisms in glass fiber reinforced polymer (GFRP) composites by detecting the related polarization mechanisms. Here, results show …
Dielectric Analysis To Predict Moisture Absorption In Structural Composites: A Data-Driven Approach, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Dielectric Analysis To Predict Moisture Absorption In Structural Composites: A Data-Driven Approach, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
Due to continual exposure to moist environment, environmental degradation is a major threat to structural composites throughout their service life. Impedance Spectroscopy (IS)/Broadband Dielectric Spectroscopy (BbDS) is a reliable nondestructive method that has been used in polymer industries for dielectric characterization of material. While moisture absorption causes irreversible changes in the polymer matrix composites, it also alters the electrical properties of the system which is detectable using BbDS. Since the physics that drives the change in electrical characteristics is driven by the modifications imposed by water molecules (whether free or bound), both events can be linked. A dielectric spectrum over …
Coupled Effects In Dielectric And Thermal Properties Of Polymer Matrix Composite Structures Due To Moisture Absorption, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Coupled Effects In Dielectric And Thermal Properties Of Polymer Matrix Composite Structures Due To Moisture Absorption, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
Fiber reinforced polymer (FRP) composites are being used in number of fields including aerospace, marine, sports, medical, power sectors, etc. due to their lightweight nature while retaining high mechanical performance in terms of high specific strength, stiffness, and great fatigue properties. However, the applicability of these materials is restricted by their stability up to a certain temperature (i.e. glass transition temperature) and environmental degradation (i.e. moisture, UV light, etc.). Moisture ingression greatly reduces their mechanical properties altering material structure by causing polymer plasticization, chain scission and fiber-polymer interface deterioration. These changes instantaneously affect the thermal properties of the materials which …
The Effect Of Plasma Treatment On The Cure Behavior Of Out-Of-Life Prepregs And An Investigation Of The Mechanical Properties Of Composite Parts Manufactured From Plasma-Treated Prepregs, Monjur Morshed Rabby, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan
The Effect Of Plasma Treatment On The Cure Behavior Of Out-Of-Life Prepregs And An Investigation Of The Mechanical Properties Of Composite Parts Manufactured From Plasma-Treated Prepregs, Monjur Morshed Rabby, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
Many industries, including aircraft, automobiles, and marine, are using prepreg (pre-impregnated fibers and a partially cured polymer matrix) to manufacture composite parts to achieve optimum fiber and resin volume ratio and part repeatability. Since prepregs have a short out oflife (i.e., the maximum storing time allowed at room temperature), they must be stored in refrigerators at low temperatures, which, if not maintained, have an unfavorable influence on the intended quality of the final product. For the present study, glass/epoxy prepregs (expired out-life) were plasmatreated before being used to make the composite part to compensate for the room temperature aging effect. …
Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Susan Mckeever, Ayman Taha, Jane Courtney
Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Susan Mckeever, Ayman Taha, Jane Courtney
Datasets
Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the …
Replication Data For: Experimental And Numerical Study Of Evaporation From Wavy Surfaces By Coupling Free Flow And Porous Media Flow, Bo Gao, Kathleen Smits
Replication Data For: Experimental And Numerical Study Of Evaporation From Wavy Surfaces By Coupling Free Flow And Porous Media Flow, Bo Gao, Kathleen Smits
Earth & Environmental Sciences Datasets - Archive
The macroscale roughness of the soil surface has significant influences on the mass/energy interactions between the subsurface and the atmosphere during evaporation. However, most previous works only consider evaporation behavior from flat surfaces. Based on experimental and numerical approaches, the goal of this work is to provide a framework for the understanding of the mechanisms of evaporation from irregular soil surfaces at representative elementary volume scale. A coupling free flow-porous media flow model was developed to describe evaporation under nonisothermal conditions. For simplicity, sinusoidal-type wavy surfaces were considered. To validate this modeling approach, an experiment using an open-ended wind tunnel …
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 - Archive
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 …
Constraint Optimal Selection Techniques (Costs) For A Class Of Linear Programming Problems, Tai-Kuan Sung
Constraint Optimal Selection Techniques (Costs) For A Class Of Linear Programming Problems, Tai-Kuan Sung
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
This dissertation describes two classes of Constraint Optimal Selection Techniques (COSTs). An algorithm of each type is developed for solving nonnegative linear programming problems. In addition, geometric interpretations of these new algorithms are given, computational results for some large-scale problems are provided, and directions for future research are discussed.
Bridge Load Posting Prediction, Sabarethinam Kameshwar, Md. Manik Mia, Sai Bandaru
Bridge Load Posting Prediction, Sabarethinam Kameshwar, Md. Manik Mia, Sai Bandaru
Data
There are approximately 13,000 bridges in Louisiana facilitating movement of people, goods, and services. At present, about 12% of the bridges are load posted, i.e., they are deemed to lack the strength to safely carry all legal loads. With time bridges will age and deteriorate; at the same time, legal loads might increase. Load posted bridges disrupt the movement of goods and commerce. Therefore, objective of this research was to estimate the number of load posted bridges in Louisiana over the next 50 years. For this purpose, herein, a data based approach was used. For a given bridge type, the …
Smart Battery Management System For Electric Vehicles: Selflearning Algorithms For Simultaneous State And Parameter Estimation, And Stress Detection, Avimanyu Sahoo, Samir Ahmed
Smart Battery Management System For Electric Vehicles: Selflearning Algorithms For Simultaneous State And Parameter Estimation, And Stress Detection, Avimanyu Sahoo, Samir Ahmed
Data
The project proposes to develop parameter-varying SOH-coupled models for lithium-ion battery and self-learning algorithms to learn the model for simultaneous state and parameter estimation and fault detection. The traditional battery models use constant parameters, limiting their accuracy for predicting the state of the charge and health over the complete life-cycle. In practice, the battery parameters vary with the change in the state of charge and state of health. SOH-coupled models can be used to estimate the state of charge and health accurately. Further, obtaining the model parameters is also a challenging task for designing filters or observers for state estimation. …
Expanding The Concept Of Comprehensive Area Ratio Parameter To The South-Central States: Towards Simplifying The Structural Evaluation Of Flexible Pavements At The Network Level, Mena Souliman, Samer Dessouky, Nitish R. Bastola
Expanding The Concept Of Comprehensive Area Ratio Parameter To The South-Central States: Towards Simplifying The Structural Evaluation Of Flexible Pavements At The Network Level, Mena Souliman, Samer Dessouky, Nitish R. Bastola
Data
The surface deflection bowl data collected through falling weight deflectometer (FWD) test is utilized by highway agencies in assessing the performance of the flexible pavement. However, a robust method to evaluate pavement sections utilizing FWD data from all the sensors is seldom developed. There is always a need for DOTs and highway agencies to have a simplified procedure, which can be directly implemented in agencies' databases. This study focuses on expanding and validating the concept of previously developed area ratio parameters towards the pavement section of South-Central States (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) in effectively analyzing the pavement …
Field Implementation And Monitoring Of An Ultra-High Performance Concrete Bridge Deck Overlay, Craig Newtson, Brad Weldon, William Toledo, Andres Alvarez, Mark Manning
Field Implementation And Monitoring Of An Ultra-High Performance Concrete Bridge Deck Overlay, Craig Newtson, Brad Weldon, William Toledo, Andres Alvarez, Mark Manning
Data
This project focused on field implementation of an ultra-high performance concrete (UHPC) overlay during rehabilitation of an existing concrete bridge (No. 7032) deck in Socorro, New Mexico, USA. Bridge 7032 is a two-lane bridge that is approximately 300 ft. (91.4 m) long and 54 ft. (16.5 m) in width. Rehabilitation of bridge 7032 included removal of deteriorated concrete from the existing deck, installation of a high-performance deck (HPD) leveling course, and installation of a 1 in. (25 mm) UHPC overlay. An UHPC mixture with a 19.5 ksi (134 MPa) compressive strength developed in previous research was selected for this project. …
Ulmus Rubra, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar
Ulmus Rubra, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar
Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images
No abstract provided.