Engineering Commons^™

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.

Globule Masks-Exact.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.

Globule Masks-Dilatedellipsekernel3.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.

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 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

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

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

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 ...

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 ...

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 ...

Non-Contact Heart Rate Estimation In Low Snr Environments Using Mmwave Radar, Chandler J. Bauder, Aly E. Fathy

Faculty Publications and Other Works -- EECS

Extracting accurate heart rate estimates of human subjects from a distance in high-noise scenarios using radar is a common problem. Often, frequency components from sources such as movement and vital signs from other subjects can overpower the weak reflected signal of the heart. In this study, we propose a signal processing scheme using a state-of-the-art Adaptive Multi-Trace Carving algorithm (AMTC) to accurately detect the heart rate signal over time in non-ideal scenarios. In our initial proof-of-concept results, we show a low heart rate estimation mean absolute error (MAE) of 3bpm for a single subject marching in place and less than ...

Download Bmp Trains 2020 Newest Version 4.3.5, Martin Wanielista

BMP Trains

This is version 4.3.5 BMP Trains 2020. It is a computer program used to assess the average annual removal effectiveness of nutrients. It is based on research from the State of Florida and uses design criteria in the State. It is accepted by regulatory agencies in the State. It was posted for use stating on December 1, 2021.

This version allows for greater flexibility in media selection. Noted is the choice of treatment rate to calculated service life. Treatment rate is usually decreased by 2 to incorporate a factor of safety. It also increases the reporting decimal places ...

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 ...

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

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

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 ...

Paulownia Tomentosa, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Ulmus Rubra, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Liriodendron Tulipifera, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Acer Monspessulanum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Aesculus Hippocastanum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cercis Canadensis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Crataegus Phaenopyrum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Acer Ginnala, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Acer Palmatum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Aesculus Chinensis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Amelanchier Ovalis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Buxus Sempervirens, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Carpinus Caroliniana, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Castanea Dentata, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.