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The Synapse: Intercollegiate science magazine

No abstract provided.

The Celestial Standoff, Timo Nurmi

The Synapse: Intercollegiate science magazine

No abstract provided.

Implanting The Future At Your Fingertips: The Epitome Of Advancements In Bio Wearables, Jungsuk Lee

The Synapse: Intercollegiate science magazine

No abstract provided.

Considering Equity In Infrastructure Planning Processes And Outcomes For Coastal Resilience, Wie Yusuf, Marina Saitgalina, Tom Allen, Nicole S. Hutton, Jennifer L. Whytlaw, Joshua Behr

School of Public Service Faculty Publications

No abstract provided.

Evolving Availability And Standardization Of Patient Attributes For Matching, Elmer V Bernstam, Theresa Cullen, Ramkiran Gouripeddi, Christopher Harle, David F Hesse, Jacob Kean, John Lee, Tanja Magoc, Daniella Meeker, Toan Ong, Jyotishman Pathak, Marc Rosenman, Laura K Rusie, Akash J Shah, Lizheng Shi, Aaron Thomas, William E Trick, Shaun Grannis, Abel Kho

Faculty, Staff and Student Publications

Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010-2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes …

Biopsychosocial Resilience Through A Complex Adaptive Systems Lens: A Narrative Review Of Nonlinear Modeling Approaches, Adam W. Kiefer, David Pincus

Psychology Faculty Articles and Research

Human resilience is often considered as static traits using a reductionist approach. More recent work has demonstrated it to be a dynamic and emergent property of complex systems. This narrative review explores human resilience through a self-organizing framework with a specific emphasis on the application of nonlinear modeling approaches. Four classes of approaches are examined: univariate dynamics, bivariate coupling, topological modeling, and network modeling. Univariate dynamics capture the temporal structure and flexibility within a single time series, while bivariate coupling approaches quantify the interaction dynamics and coordination between two time series. Topological modeling identifies bifurcations and attractor dynamics as signals …

Discoverpath: A Knowledge Refinement And Retrieval System For Interdisciplinarity On Biomedical Research, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

The exponential growth in scholarly publications necessitates advanced tools for efficient article retrieval, especially in interdisciplinary fields where diverse terminologies are used to describe similar research. Traditional keyword-based search engines often fall short in assisting users who may not be familiar with specific terminologies. To address this, we present a knowledge graph based paper search engine for biomedical research to enhance the user experience in discovering relevant queries and articles. The system, dubbed DiscoverPath, employs Named Entity Recognition (NER) and part-of-speech (POS) tagging to extract terminologies and relationships from article abstracts to create a KG. To reduce information overload, DiscoverPath …

Machine Learning Approach To Activity Categorization In Young Adults Using Biomechanical Metrics, Nathan Q. C. Holland

Mechanical & Aerospace Engineering Theses & Dissertations

Inactive adults often have decreased musculoskeletal health and increased risk factors for chronic diseases. However, there is limited data linking biomechanical measurements of generally healthy young adults to their physical activity levels assessed through questionnaires. Commonly used data collection methods in biomechanics for assessing musculoskeletal health include but are not limited to muscle quality (measured as echo intensity when using ultrasound), isokinetic (i.e., dynamic) muscle strength, muscle activations, and functional movement assessments using motion capture systems. These assessments can be time consuming for both data collection and processing. Therefore, understanding if all biomechanical assessments are necessary to classify the activity …

Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (CAPs) together with cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in …

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …

Interferometry Of Efimov States In Thermal Gases By Modulated Magnetic Fields, G. Bougas, Simeon I. Mistakidis, P. Schmelcher, C. H. Greene, P. Giannakeas

Physics Faculty Research & Creative Works

We Demonstrate That An Interferometer Based On Modulated Magnetic Field Pulses Enables Precise Characterization Of The Energies And Lifetimes Of Efimov Trimers Irrespective Of The Magnitude And Sign Of The Interactions In Rb85 Thermal Gases. Despite Thermal Effects, Interference Fringes Develop When The Dark Time Between The Pulses Is Varied. This Enables The Selective Excitation Of Coherent Superpositions Of Trimer, Dimer, And Free-Atom States. The Interference Patterns Possess Two Distinct Damping Timescales At Short And Long Dark Times That Are Either Equal To Or Twice As Long As The Lifetime Of Efimov Trimers, Respectively. Specifically, This Behavior At Long Dark …

Affine Image Registration Of Arterial Spin Labeling Mri Using Deep Learning Networks, Zongpai Zhang, Huiyuan Yang, Yanchen Guo, Nicolas R. Bolo, Matcheri Keshavan, Eve Derosa, Adam K. Anderson, David C. Alsop, Lijun Yin, Weiying Dai

Computer Science Faculty Research & Creative Works

Convolutional neural networks (CNN) have demonstrated good accuracy and speed in spatially registering high signal-to-noise ratio (SNR) structural magnetic resonance imaging (sMRI) images. However, some functional magnetic resonance imaging (fMRI) images, e.g., those acquired from arterial spin labeling (ASL) perfusion fMRI, are of intrinsically low SNR and therefore the quality of registering ASL images using CNN is not clear. In this work, we aimed to explore the feasibility of a CNN-based affine registration network (ARN) for registration of low-SNR three-dimensional ASL perfusion image time series and compare its performance with that from the state-of-the-art statistical parametric mapping (SPM) algorithm. The …

2023 October - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken

Faculty Publications

Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.

Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Abstract © Emerald Publishing …

Geographic Differences In The Magnitude Of Black-White Disparities In Having Obesity, Steven A. Cohen, Monique J. Brown, Furong Xu, Caitlin C. Nash, Mary L. Greaney

Faculty Publications

Background

Obesity disparities in the United States are well documented, but the limited body of research suggests that geographic factors may alter the magnitude of these disparities. A growing body of evidence has identified a “rural mortality penalty” where morbidity and mortality rates are higher in rural than urban areas, even after controlling for other factors. Black-White differences in health and mortality are more pronounced in rural areas than in urban areas.

Objective

Therefore, the purpose of this study was to explore how rural-urban status and region moderate Black-White health disparities in obesity.

Methods

Data were abstracted from the 2012 …

Remedial Action Work Plan - East Middle School, Environmental Protection Agency

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Examination And Application Of Body Condition Methods In Cetaceans, Kira Anne Telford

Theses and Dissertations

Body condition assessments are a valuable tool for evaluating the relative health of a population through various metrics, indexes, or proxies. Long-term data collection can be used to examine the relationship between fluctuations in body condition and natural or anthropogenic drivers. Application of this information is vital for monitoring the success of the conservation management decisions for a species or population. Cetaceans have a variety of methods available to assess body condition, including invasive methods like biopsies and necropsies or observational methods such as photogrammetry. Exploration of the application of these methods in the literature revealed an emphasis on necropsies …

Poor Water Quality Persists In Diverse Urban Communities, Rae Cade, Danlin Yu, Kyle Whyte, Pankaj Lal, Cortni Borgerson

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

While humans need water to survive, water can also efficiently transmit microbial diseases and heavy metals to consumers. Over 50,000 water violations occurred in 2020 and such burdens were not borne equally amongst consumers. Yet, the factors that drive such variation remain unclear. We examined the interactions between water quality and inherited equity gaps in one of the most diverse urban areas in the United States. We used publicly available drinking water datasets to determine which contaminant was most prevalent between 2010–2020 and who was significantly more likely to be affected by this contamination. We found that a lack of …

Water Wise Landscape Practices: A Case Study For The City Of Gering, Christina E. Land

Community and Regional Planning Program: Professional Projects

This professional project is founded on my education, experiences, and networks. I have had the opportunity to use what I have learned thus far and be challenged to look at public planning from a different perspective. In partnership with the City of Gering I was able to get knee deep in the facility planning of the city owned property which is home to the Community Ever Green House. The project reviews how the property is integrated into the community and the impact it has. Then, identifies opportunities to improve overall functionality with a closer look at addressing hazard mitigation using …

Rapid: Region-Based Pointer Disambiguation, Khushboo Chitre, Piyus Kedia, Rahul Purandare

School of Computing: Faculty Publications

Interprocedural alias analyses often sacrifice precision for scalability. Thus, modern compilers such as GCC and LLVM implement more scalable but less precise intraprocedural alias analyses. This compromise makes the compilers miss out on potential optimization opportunities, affecting the performance of the application. Modern compilers implement loop-versioning with dynamic checks for pointer disambiguation to enable the missed optimizations. Polyhedral access range analysis and symbolic range analysis enable O(1) range checks for non-overlapping of memory accesses inside loops. However, these approaches work only for the loops in which the loop bounds are loop invariants. To address this limitation, researchers proposed a …

Optimal Agricultural Land Use: An Efficient Neutrosophic Linear Programming Method, Maissam Jdid, Florentin Smarandache

Neutrosophic Systems with Applications

The increase in the size of the problems facing humans, their overlap, the division of labor, the multiplicity of departments, as well as the diversity of products and commodities, led to the complexity of business and the emergence of many administrative and production problems. It was necessary to search for appropriate methods to confront these problems. The science of operations research, with its diverse methods, provided the optimal solutions. It addresses many problems and helps in making scientific and thoughtful decisions to carry out the work in the best way within the available capabilities. Operations research is one of the …

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Academic Evaluation From The Perspective Of Multi-Source Eterogeneous Data:Connotation, Status And Prospect, Sanhong Deng, Jie Yang, Hao Wang, Jia Shen

Journal of Scientific Information Research

[Purpose/significance]Academic evaluation and scientometric methods of synthesizing multisource heterogeneous data have gradually become hot spots in the field. At present， there is no systematic theoretical discussion on academic evaluation from the perspective of multisource heterogeneous data.[Method/process]In view of insufficient utilization of multi-source heterogeneous data， inappropriate research methods， and unclear research objectives， this paper combs the development of academic evaluation from the perspective of multi-source heterogeneous data， and clarifies the connotation and extension of the field， and analyzes the frontiers and hot spots in the field.[Result/conclusion]The results state clearly that from the perspective of multi-source heterogeneous data， academic evaluation manifests the …

A Systematic Review Of The Governance Of Internet Information's Content Ecosystem In China, Weichao Li, Yi Zhou

Journal of Scientific Information Research

[Purpose/significance]This study aims to provide valuable references for future research and governance practices by reviewing the research on the governance of Internet information's content ecosystem in China.[Method/process]This paper collects literature data from the core journal library of CNKI, reveals the macro situation of this topic research by using the bibliometric method, selects the literature that meets the quality standards by using the systematic review method, summarizes relevant studies from four dimensions: governance bodies, governance objects, governance tools and governance mechanisms.[Result/conclusion]The co-governance of multi-subjects  has become the basic consensus of the academic circle. Solving the problem of subjects failure and promoting …

Structure Estimation Of Adversarial Distributions For Enhancing Model Robustness: A Clustering-Based Approach, Bader Rasheed, Adil Khan, Asad Masood Khattak

All Works

In this paper, we propose an advanced method for adversarial training that focuses on leveraging the underlying structure of adversarial perturbation distributions. Unlike conventional adversarial training techniques that consider adversarial examples in isolation, our approach employs clustering algorithms in conjunction with dimensionality reduction techniques to group adversarial perturbations, effectively constructing a more intricate and structured feature space for model training. Our method incorporates density and boundary-aware clustering mechanisms to capture the inherent spatial relationships among adversarial examples. Furthermore, we introduce a strategy for utilizing adversarial perturbations to enhance the delineation between clusters, leading to the formation of more robust and …

Effective Entity Augmentation By Querying External Data Sources, Christopher Buss, Jasmin Mousavi, Mikhail Tokarev, Arash Termehchy, David Maier, Stefan Lee

Computer Science Faculty Publications and Presentations

Users often want to augment and enrich entities in their datasets with relevant information from external data sources. As many external sources are accessible only via keyword-search interfaces, a user usually has to manually formulate a keyword query that extract relevant information for each entity. This approach is challenging as many data sources contain numerous tuples, only a small fraction of which may contain entity-relevant information. Furthermore, different datasets may represent the same information in distinct forms and under different terms (e.g., different data source may use different names to refer to the same person). In such cases, it is …

The Encyclopedia Of Neutrosophic Researchers, 5th Volume, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy.

In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements.

There are about 7,000 neutrosophic researchers, within 89 countries around the …

Application And Use Of Artificial Intelligence (Ai) For Library Services Delivery In Academic Libraries In Kwara State, Nigeria, Abdullahi Olayinka Isiaka

Library Philosophy and Practice (e-journal)

The application and use Artificial Intelligence (AI) in library services delivery and operations has modernized traditional practices, enabling libraries to adapt to the evolving information needs of patrons in the digital era. The main purpose of this study is to investigate the application and use of Artificial Intelligence (AI) Technologies for Library Services Delivery in Academic Libraries in Kwara State, Nigeria. The study used a descriptive survey approach. The population was the 108 librarians in academic libraries in Kwara State, Nigeria. A total enumeration technique was employed, and a questionnaire was used to collect data from the library staff. The …

Boosting Adversarial Training In Safety-Critical Systems Through Boundary Data Selection, Yifan Jia, Christopher M. Poskitt, Peixin Zhang, Jingyi Wang, Jun Sun, Sudipta Chattopadhyay

Research Collection School Of Computing and Information Systems

AI-enabled collaborative robots are designed to be used in close collaboration with humans, thus requiring stringent safety standards and quick response times. Adversarial attacks pose a significant threat to the deep learning models of these systems, making it crucial to develop methods to improve the models' robustness against them. Adversarial training is one approach to improve their robustness: it works by augmenting the training data with adversarial examples. This, unfortunately, comes with the cost of increased computational overhead and extended training times. In this work, we balance the need for additional adversarial data with the goal of minimizing the training …

Objectfusion: Multi-Modal 3d Object Detection With Object-Centric Fusion, Q. Cai, Y. Pan, T. Yao, Chong-Wah Ngo, T. Mei

Research Collection School Of Computing and Information Systems

Recent progress on multi-modal 3D object detection has featured BEV (Bird-Eye-View) based fusion, which effectively unifies both LiDAR point clouds and camera images in a shared BEV space. Nevertheless, it is not trivial to perform camera-to-BEV transformation due to the inherently ambiguous depth estimation of each pixel, resulting in spatial misalignment between these two multi-modal features. Moreover, such transformation also inevitably leads to projection distortion of camera image features in BEV space. In this paper, we propose a novel Object-centric Fusion (ObjectFusion) paradigm, which completely gets rid of camera-to-BEV transformation during fusion to align object-centric features across different modalities for …