Physical Sciences and Mathematics Commons^™

Hydrological Drought Forecasting Using A Deep Transformer Model, Amobichukwu C. Amanambu, Joann Mossa, Yin-Hsuen Chen

University Administration Publications

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were …

Polymer Mimetics For Soil Modeling And Detection Of Biomarkers, Md Ragib Hasan

LSU Doctoral Dissertations

The population of the world is increasing day by day and is expected to reach 9.8 billion by the year 2050. The ever-increasing demand for agricultural products is putting an unprecedented strain on the world's soils as the human population continues to expand. Soil degradation caused by over-farming and the agrochemicals (fertilizers, pesticides, etc.) used in agriculture is a growing problem, although its causes remain murky. In addition, little is understood about the molecular-level interactions of substances that are subsequently introduced to soils, such as agricultural chemicals (ACs). Therefore, it is expected that these constraints may be circumvented by the …

Canonical Quantile Regression, Stephen Portnoy

Mathematics and Statistics Faculty Publications and Presentations

In using multiple regression methods for prediction, one often considers the linear combination of explanatory variables as an index. Seeking a single such index when here are multiple responses is rather more complicated. One classical approach is to use the coefficients from the leading Canonical Correlation. However, methods based on variances are unable to disaggregate responses by quantile effects, lack robustness, and rely on normal assumptions for inference. An alternative canonical regression quantile (CanRQ) approach seeks to find the linear combination of explanatory variables that best predicts the τ" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: …

Thermal Degradation Of Erythritol, Sudheendra Gamoji

Physics

The Insulated Solar Electric Cooker (ISEC) is a double walled Aluminum pot with a resistive heater directly connected to a solar panel whose goal is to create and disseminate cheap solar cookers in rural areas that primarily rely on biomass for cooking. Phase Change Materials (PCMs) like Erythritol, a sugar substitute, take a tremendous amount of energy to melt, and when they solidify they release the energy. Through the use of PCMs, the ISECs will produce enough heat to cook food even after the sun sets. However, PCMs like Erythritol degrade over repeated heat exposure, so the purpose of this …

Understanding Deviance And Victimization In Cyber Space Among Diverse Populations, Insun Park

International Journal of Cybersecurity Intelligence & Cybercrime

Recent years have witnessed a growing academic interest in deviance and victimization in the cyber space. The current issue of the International Journal of Cybersecurity Intelligence and Cybercrime features three empirical research articles on online behavior of traditionally under-researched populations and a review of much waited book on digital forensics and investigation. This paper was prepared to introduce these important scholarly works in the context of newly emerging scholarship that focuses on the experiences of diverse subgroups in cyberspace.

Emerging Trends In Cybercrime Awareness In Nigeria, Ogochukwu Favour Nzeakor, Bonaventure N. Nwokeoma, Ibrahim Hassan, Benjamin Okorie Ajah, John T. Okpa

International Journal of Cybersecurity Intelligence & Cybercrime

The study examined the current trend in cybercrime awareness and the relationship such trend has with cybercrime vulnerability or victimization. Selecting a sample of 1104 Internet users from Umuahia, Abia State, Nigeria, We found that: 1) awareness of information security was high in that about 2 in every 3 (68%) participants demonstrated a favorable awareness of information security and cybercrime. It was, however, revealed that such a high level of awareness could be partial and weak. 2) most Internet users demonstrated the awareness of fraud-related cybercrime categories (39%), e-theft (15%), hacking (12%), and ATM theft (10%). However, they were rarely …

Magnetism In Doped And Hybrid Two – Dimensional Transition Metal Dichalcogenides, Nalaka Kapuruge

USF Tampa Graduate Theses and Dissertations

In recent years, spintronics has gained increasing interest due to the possibility of storing and processing information through the manipulation of both the charge and spin of an electron. Dilute magnetic semiconductors are ideal for the fabrication of such devices as they display carrier-mediated ferromagnetism which allows the electronic control of magnetism. Transferring these properties into the two-dimensional (2D) realm is very attractive for both fundamental research and novel applications. The recent discovery of long-range magnetic order in 2D materials has attracted a growing effort in the search for new functional 2D materials that can display ferromagnetic properties at room-temperature. …

Tourgether360: Collaborative Exploration Of 360° Videos Using Pseudo-Spatial Navigation, Kartikaeya Kumar, Lev Poretski, Jianan Li, Anthony Tang

Research Collection School Of Computing and Information Systems

Collaborative exploration of 360 videos with contemporary interfaces is challenging because collaborators do not have awareness of one another's viewing activities. Tourgether360 enhances social exploration of 360° tour videos using a pseudo-spatial navigation technique that provides both an overhead "context" view of the environment as a minimap, as well as a shared pseudo-3D environment for exploring the video. Collaborators are embodied as avatars along a track depending on their position in the video timeline and can point and synchronize their playback. We evaluated the Tourgether360 concept through two studies: first, a comparative study with a simplified version of Tourgether360 with …

Effects Of Position And Gap Orientation Of The Split Ring Resonator Structure Excited By Microstrip Transmission Line On The Transmission Characteristics, Nezi̇he Karacan, Nesli̇han Kader Bulut, Evren Ekmekçi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the effects of the position and the gap orientation of the split ring resonator (SRR) structure, which is applied as a superstrate, on transmission characteristics (i.e. S21 ) are investigated numerically and experimentally. For that purpose, the left edge of the transmission line has been designated as the reference line and the SRR structure is shifted towards both left and right for three different gap orientations. Subsequently, S21 characteristics of the SRR structure having several substrate thicknesses and several substrate dielectric constants are investigated parametrically for three different gap orientations. The results reveal that the position and …

Compact Dual-Band Rectangular T E10 Mode To Circular Tm01 Mode Converter For Telemetry/Telecommand Applications In Satellite Communication: Design, Equivalent Circuit Modeling, Mode Level Measurement Technique And 3d Printed Manufacturing, Esra Alkin, Ceyhan Türkmen, Mustafa Seçmen

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the design of a dual-band mode converter, which provides transition from rectangular waveguide T E10 mode to circular waveguide TM01 mode and operates simultaneously in telemetry/telecommand (TT&C) frequencies, is presented along with its equivalent circuit and a mode level measurement technique. This dual-band converter is designed to uniformly excite TT&C slot antennas used in satellite communication with symmetric circular TM01 mode. The structure can work as a transceiver due to having one common rectangular waveguide feed. As a Ku-band application, a converter giving high purity TM01 mode at circular waveguide at 11.75 GHz/TX …

A Fine-Grained Data Set And Analysis Of Tangling In Bug Fixing Commits, Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristóf Szabados, Helge Spieker, Matej Madeja, Nathaniel G. Hoy, Christoph Treude, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo-Palacios, Roberto Verdecchia, Paramvir Singh

Research Collection School Of Computing and Information Systems

Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs.Objective: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits.Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the …

A Method To Solve One-Dimensional Nonlinear Fractional Differential Equation Using B-Polynomials, Md. Habibur Rahman, Muhammad I. Bhatti, Nicholas Dimakis

Physics and Astronomy Faculty Publications and Presentations

In this article, the fractional Bhatti-Polynomial bases are applied to solve one-dimensional nonlinear fractional differential equations (NFDEs). We derive a semi-analytical solution from a matrix equation using an operational matrix which is constructed from the terms of the NFDE using Caputo’s fractional derivative of fractional B-polynomials (B-polys). The results obtained using the prescribed method agree well with the analytical and numerical solutions presented by other authors. The legitimacy of this method is demonstrated by using it to calculate the approximate solutions to four NFDEs. The estimated solutions to the differential equations have also been compared with other known numerical and …

A Quality Metric For K-Means Clustering Based On Centroid Locations, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

K-Means clustering algorithm does not offer a clear methodology to determine the appropriate number of clusters; it does not have a built-in mechanism for K selection. In this paper, we present a new metric for clustering quality and describe its use for K selection. The proposed metric, based on the locations of the centroids, as well as the desired properties of the clusters, is developed in two stages. In the initial stage, we take into account the full covariance matrix of the clustering variables, thereby making it mathematically similar to a reduced chi2. We then extend it to account for …

Investigating Bloom's Cognitive Skills In Foundation And Advanced Programming Courses From Students' Discussions, Joel Jer Wei Lim, Gottipati Swapna, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Programming courses provide students with the skills to develop complex business applications. Teaching and learning programming is challenging, and collaborative learning is proposed to help with this challenge. Online discussion forums promote networking with other learners such that they can build knowledge collaboratively. It aids students open their horizons of thought processes to acquire cognitive skills. Cognitive analysis of discussion is critical to understand students' learning process. In this paper, we propose Bloom's taxonomy based cognitive model for programming discussion forums. We present machine learning (ML) based solution to extract students' cognitive skills. Our evaluations on compupting courses show that …

Recipegen++: An Automated Trigger Action Programs Generator, Imam Nur Bani Yusuf, Diyanah Abdul Jamal, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

Trigger Action Programs (TAPs) are event-driven rules that allow users to automate smart-devices and internet services. Users can write TAPs by specifying triggers and actions from a set of predefined channels and functions. Despite its simplicity, composing TAPs can still be challenging for users due to the enormous search space of available triggers and actions. The growing popularity of TAPs is followed by the increasing number of supported devices and services, resulting in a huge number of possible combinations between triggers and actions. Motivated by such a fact, we improve our prior work and propose RecipeGen++, a deep-learning-based approach that …

Gis Data: St Mary’S County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Study Of Flow Of Buongiorno Nanofluid In A Conical Gap Between A Cone And A Disk, Mahanthesh Basavarajappa, Dambaru Bhatta

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

The cone–disk apparatus consists of a cone that touches the disk at its apex and is used in medical evices, viscosimeters, conical diffusers, etc. Theoretically, a three-dimensional flow of a nanofluid in a conical gap of a cone–disk apparatus is studied for four different physical configurations. Buongiorno nanofluid model, consisting of thermophoresis and Brownian diffusion mechanisms, is used to describe the convective heat transport of the nanofluid. The continuity equation, the Navier–Stokes momentum equation, the heat equation, and the conservation of nanoparticle volume fraction equation constitute the governing system for the flow of nanofluids. The Lie group approach is used …

Multi-Scale Hybridized Topic Modeling: A Pipeline For Analyzing Unstructured Text Datasets Via Topic Modeling, Keyi Cheng, Stefan Inzer, Adrian Leung, Xiaoxian Shen, Michael Perlmutter, Michael Lindstrom, Joyce Chew, Todd Presner, Deanna Needell

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

We propose a multi-scale hybridized topic modeling method to find hidden topics from transcribed interviews more accurately and efficiently than traditional topic modeling methods. Our multi-scale hybridized topic modeling method (MSHTM) approaches data at different scales and performs topic modeling in a hierarchical way utilizing first a classical method, Nonnegative Matrix Factorization, and then a transformer-based method, BERTopic. It harnesses the strengths of both NMF and BERTopic. Our method can help researchers and the public better extract and interpret the interview information. Additionally, it provides insights for new indexing systems based on the topic level. We then deploy our method …

Labeling Microplastics With Fluorescent Dyes For Detection, Recovery, And Degradation Experiments, Zhiqiang Gao, Kendall Wontor, James V. Cizdziel

Faculty and Student Publications

Staining microplastics (MPs) for fluorescence detection has been widely applied in MP analyses. However, there is a lack of standardized staining procedures and conditions, with different researchers using different dye concentrations, solvents, incubation times, and staining temperatures. Moreover, with the limited types and morphologies of commercially available MPs, a simple and optimized approach to making fluorescent MPs is needed. In this study, 4 different textile dyes, along with Nile red dye for comparison, are used to stain 17 different polymers under various conditions to optimize the staining procedure. The MPs included both virgin and naturally weathered polymers with different sizes …

From Machine Learning To Deep Learning: A Comprehensive Study Of Alcohol And Drug Use Disorder, Banafsheh Rekabdar, David L. Albright, Haelim Jeong, Sameerah Talafha

Computer Science Faculty Publications and Presentations

This study aims to train and validate machine learning and deep learning models to identify patients with risky alcohol and drug misuse in a Screening, Brief Intervention, and Referral to Treatment (SBIRT) program. An observational cohort of 6978 adults was admitted in the western region of Alabama at three medical facilities between January and December of 2019. Data were cleaned and pre-processed using data imputation techniques and an augmented sampling data method. The primary analysis involved the multi-class classification of alcohol and drug misuse. Our study shows that accurate identification of alcohol and drug use screening instrument scores was best …

Hierarchical Structure Of Yso Clusters In The W40 And Serpens South Region: Group Extraction And Comparison With Fractal Clusters, Jia Sun, Robert A. Gutermuth, Hongchi Wang, Shuinai Zhang, Min Long

Computer Science Faculty Publications and Presentations

Young stellar clusters are believed to inherit the spatial distribution like hierarchical structures of their natal molecular cloud during their formation. However, the change of the structures between the cloud and the young clusters is not well constrained observationally. We select the W40–Serpens South region (∼7 × 9 pc²) of the Aquila Rift as a testbed and investigate hierarchical properties of spatial distribution of young stellar objects (YSOs) in this region. We develop a minimum spanning tree (MST) based method to group stars into several levels by successively cutting down edges longer than an algorithmically determined critical value. …

Efficient Navigation For Constrained Shortest Path With Adaptive Expansion Control, Wenwen Xia, Yuchen Li, Wentian Guo, Shenghong Li

Research Collection School Of Computing and Information Systems

In many route planning applications, finding constrained shortest paths (CSP) is an important and fundamental problem. CSP aims to find the shortest path between two nodes on a graph while satisfying a path constraint. Solving CSPs requires a large search space and is prohibitively slow on large graphs, even with the state-of-the-art parallel solution on GPUs. The reason lies in the lack of effective navigational information and pruning strategies in the search procedure. In this paper, we propose SPEC, a Shortest Path Enhanced approach for solving the exact CSP problem. Our design rationales of SPEC rely on the observation that …

Cscw 2022 Chairs' Welcome, Gary Hsieh, Anthony Tang

Research Collection School Of Computing and Information Systems

We are excited to bring you the 25th ACM Conference on Computer-Supported Cooperative Work and Social Computing – CSCW 2022 – virtually. We were initially poised to hold CSCW 2022 in Taiwan to help strengthen the CSCW community’s relationship with Asia, but the uncertainty around COVID-19 pandemic restrictions made this an impractical idea. Yet, as designers, we view challenges as learning opportunities and know learning opportunities lead to new ideas and approaches. From the online and virtual conferences experiences of the past few years, we considered questions like: what makes conferences interesting, what makes conferences worth attending, how can we …

Daot: Domain-Agnostically Aligned Optimal Transport For Domain-Adaptive Crowd Counting, Huilin Zhu, Jingling Yuan, Xian Zhong, Zhengwei Yang, Zheng Wang, Shengfeng He

Research Collection School Of Computing and Information Systems

Domain adaptation is commonly employed in crowd counting to bridge the domain gaps between different datasets. However, existing domain adaptation methods tend to focus on inter-dataset differences while overlooking the intra-differences within the same dataset, leading to additional learning ambiguities. These domain-agnostic factors,e.g., density, surveillance perspective, and scale, can cause significant in-domain variations, and the misalignment of these factors across domains can lead to a drop in performance in cross-domain crowd counting. To address this issue, we propose a Domain-agnostically Aligned Optimal Transport (DAOT) strategy that aligns domain-agnostic factors between domains. The DAOT consists of three steps. First, individual-level differences …

Predictive Self-Organizing Neural Networks For In-Home Detection Of Mild Cognitive Impairment, Seng Khoon Teh, Iris Rawtaer, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

In-home sensing of daily living patterns from older adults coupled with machine learning is a promisingapproach to detect Mild Cognitive Impairment (MCI), a potentially reversible condition with early detectionand appropriate intervention. However, the number of subjects involved in such real-world studies istypically limited, posing the so-called small data problem to most predictive models which rely on a sizablenumber of labeled data. In this work, a predictive self-organizing neural network known as fuzzy AdaptiveResonance Associate Map (fuzzy ARAM) is proposed to detect MCI using in-home sensor data collected from aunique Singapore cross-sectional study. Specifically, mean and standard deviation of nine in-home …

Mando-Guru: Vulnerability Detection For Smart Contract Source Code By Heterogeneous Graph Embeddings, Huu Hoang Nguyen, Nhat Minh Nguyen, Hong-Phuc Doan, Zahrai Ahmadi, Thanh Nam Doan, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Smart contracts are increasingly used with blockchain systems for high-value applications. It is highly desired to ensure the quality of smart contract source code before they are deployed. This paper proposes a new deep learning-based tool, MANDO-GURU, that aims to accurately detect vulnerabilities in smart contracts at both coarse-grained contract-level and fine-grained line-level. Using a combination of control-flow graphs and call graphs of Solidity code, we design new heterogeneous graph attention neural networks to encode more structural and potentially semantic relations among different types of nodes and edges of such graphs and use the encoded embeddings of the graphs and …

Towards Automated Safety Vetting Of Smart Contracts In Decentralized Applications, Yue Duan, Xin Zhao, Yu Pan, Shucheng Li, Minghao Li, Fengyuan Xu, Mu Zhang

Research Collection School Of Computing and Information Systems

We propose VetSC, a novel UI-driven, program analysis guided model checking technique that can automatically extract contract semantics in DApps so as to enable targeted safety vetting. To facilitate model checking, we extract business model graphs from contract code that capture its intrinsic business and safety logic. To automatically determine what safety specifications to check, we retrieve textual semantics from DApp user interfaces. To exclude untrusted UI text, we also validate the UI-logic consistency and detect any discrepancies. We have implemented VetSC and applied it to 34 real-world DApps. Experiments have demonstrated that VetSC can accurately interpret smart contract code, …

Itiger: An Automatic Issue Title Generation Tool, Ting Zhang, Ivana Clairine Irsan, Thung Ferdian, Donggyun Han, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

In both commercial and open-source software, bug reports or issues are used to track bugs or feature requests. However, the quality of issues can differ a lot. Prior research has found that bug reports with good quality tend to gain more attention than the ones with poor quality. As an essential component of an issue, title quality is an important aspect of issue quality. Moreover, issues are usually presented in a list view, where only the issue title and some metadata are present. In this case, a concise and accurate title is crucial for readers to grasp the general concept …

Autopruner: Transformer-Based Call Graph Pruning, Cong Thanh Le, Hong Jin Kang, Truong Giang Nguyen, Stefanus Agus Haryono, David Lo, Xuan-Bach D. Le, Huynh Quyet Thang

Research Collection School Of Computing and Information Systems

Constructing a static call graph requires trade-offs between soundness and precision. Program analysis techniques for constructing call graphs are unfortunately usually imprecise. To address this problem, researchers have recently proposed call graph pruning empowered by machine learning to post-process call graphs constructed by static analysis. A machine learning model is built to capture information from the call graph by extracting structural features for use in a random forest classifier. It then removes edges that are predicted to be false positives. Despite the improvements shown by machine learning models, they are still limited as they do not consider the source code …

How To Formulate Specific How-To Questions In Software Development?, Mingwei Liu, Xin Peng, Andrian Marcus, Christoph Treude, Jiazhan Xie, Huanjun Xu, Yanjun Yang

Research Collection School Of Computing and Information Systems

Developers often ask how-to questions using search engines, technical Q&A communities, and interactive Q&A systems to seek help for specific programming tasks. However, they often do not formulate the questions in a specific way, making it hard for the systems to return the best answers. We propose an approach (TaskKG4Q) that interactively helps developers formulate a programming related how-to question. TaskKG4Q is using a programming task knowledge graph (task KG in short) mined from Stack Overflow questions, which provides a hierarchical conceptual structure for tasks in terms of [actions], [objects], and [constraints]. An empirical evaluation of the intrinsic quality of …