Physical Sciences and Mathematics Commons^™

Takeout Distribution Routes Optimization Considering Order Clustering Under Dynamic Demand, Houming Fan, Fushan Xian, Huaiqi Wang

Journal of System Simulation

Abstract: Takeout distribution optimization includes order allocation and route planning. Aiming at dynamic order and rider position change, with the goal of minimizing the overtime order proportion, average delivery time and average travel distance,a two-stage mathematical model is established based on the idea of pre-optimization and dynamic adjustment. In the pre-optimization stage, an improved variable neighborhood search algorithm is designed to obtain the initial distribution scheme. In the dynamic adjustment stage, a periodic optimization strategy is adopted to transform the problem into a virtual distribution center vehicle problem for solution. In each stage,different clustering methods are used to optimize the …

Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao

Journal of System Simulation

Abstract: The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation …

How Noise Thresholds Affect The Information Content Of Stellar Flare Sequences, Elmer C. Rivera, Jay R. Johnson, Jonathan Homan, Simon Wing

Faculty Publications

Systems that exhibit discrete dynamics can be well described and reconstructed by considering the set of time intervals between the discrete events of the system. The Kepler satellite has cataloged light curves for many Sun-like stars, and these light curves show strong bursts in intensity that are associated with stellar flares. The waiting time between these flares describes the fundamental dynamics of the stars and is driven by physical processes, such as flux emergence. While it is rather straightforward to identify large flares, the identification of weaker flares can be challenging because of the presence of noise. A common practice …

Quadcopter Control Using Single Network Adaptive Critics, Alberto Velazquez, Lei Xu, Tohid Sardarmehni

Mechanical Engineering Faculty Publications and Presentations

In this paper, optimal tracking control is found for an inputaffine nonlinear quadcopter using Single Network Adaptive Critics (SNAC). The quadcopter dynamics consists of twelve states and four controls. The states are defined using two related reference frames: the earth frame, which describes the position and angles, and the body frame, which describes the linear and angular velocities. The quadcopter has six outputs and four controls, so it is an underactuated nonlinear system. The optimal control for the system is derived by solving a discrete-time recursive Hamilton-Jacobi-Bellman equation using a linear in-parameter neural network. The neural network is trained to …

Session 12: Analysis Of State And Parameter Estimation Techniques Using Dynamic Perturbation Signals, Timothy M. Hansen

SDSU Data Science Symposium

The trend in electric power systems is the displacement of traditional synchronous generation (e.g., coal, natural gas) with renewable energy resources (e.g., wind, solar photovoltaic) and battery energy storage. These energy resources require power electronic converters (PECs) to interconnect to the grid and have different response characteristics and dynamic stability issues compared to conventional synchronous generators. As a result, there is a need for validated models to study and mitigate PEC-based stability issues, especially for converter dominated power systems (e.g., island power systems, remote microgrids).

This presentation will introduce methods related to dynamic state and parameter estimation via the design …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Application Of Gaussian Mixture Models To Simulated Additive Manufacturing, Jason Hasse, Semhar Michael, Anamika Prasad

SDSU Data Science Symposium

Additive manufacturing (AM) is the process of building components through an iterative process of adding material in specific designs. AM has a wide range of process parameters that influence the quality of the component. This work applies Gaussian mixture models to detect clusters of similar stress values within and across components manufactured with varying process parameters. Further, a mixture of regression models is considered to simultaneously find groups and also fit regression within each group. The results are compared with a previous naive approach.

Session 2: The Effect Of Boom Leveling On Spray Dispersion, Travis A. Burgers, Miguel Bustamante, Juan F. Vivanco

SDSU Data Science Symposium

Self-propelled sprayers are commonly used in agriculture to disperse agrichemicals. These sprayers commonly have two boom wings with dozens of nozzles that disperse the chemicals. Automatic boom height systems reduce the variability of agricultural sprayer boom height, which is important to reduce uneven spray dispersion if the boom is not at the target height.

A computational model was created to simulate the spray dispersion under the following conditions: a) one stationary nozzle based on the measured spray pattern from one nozzle, b) one stationary model due to an angled boom, c) superposition of multiple stationary nozzles due an angled boom, …

Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Uncertainties are difficult if not impossible to avoid. Capturing data from the analog world almost always results in some form of uncertainty. The amount of uncertainty depends on the method of measurement and its accuracy. When visualizing data that has some associated uncertainty, it is essential to properly process and convey such uncertainty and especially the amount of uncertainty keeping in mind that additional processing steps can amplify the uncertainty. There are various sources of uncertainty, such as numerical limitations or limitations of the capture device. However, there are other sources of uncertainty. Some of these uncertainties stem from model …

Fair4pghd: A Framework For Fair Implementation Over Pghd, Abdullahi Abubakar Kawu, Dympna O'Sullivan, Lucy Hederman, Mirjam Van Reisen

Articles

Patient Generated Health Data (PGHD) are being considered for integration with health facilities, however little is known about how such data can be made machine-actionable in a way that meets FAIR guidelines. This article proposes a 5-stage framework that can be used to achieve this.

Current Scenario Of Solar Energy Applications In Bangladesh: Techno-Economic Perspective, Policy Implementation, And Possibility Of The Integration Of Artificial Intelligence, Monirul Islam Miskat, Protap Sarker, Hemal Chowdhury, Tamal Chowdhury, Md Salman Rahman, Nazia Hossain, Piyal Chowdhury, Sadiq M. Sait

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Bangladesh is blessed with abundant solar resources. Solar power is considered the most desirable energy source to mitigate the high energy demand of this densely populated country. Although various articles deal with solar energy applications in Bangladesh, no detailed review can be found in the literature. Therefore, in this study, we report on the current scenario of renewable energy in Bangladesh and the most significant potential of solar energy’s contribution among multiple renewable energy resources in mitigating energy demand. One main objective of this analysis was to outline the overall view of solar energy applications in Bangladesh to date, as …

Systems Thinking Activities Used In K-12 For Up To Two Decades, Diana Fisher, Systems Thinking Association

Systems Science Faculty Publications and Presentations

Infusing systems thinking activities in pre-college education (grades K-12) means updating precollege education so it includes a study of many systemic behavior patterns that are ubiquitous in the real world. Systems thinking tools include those using both paper and pencil and the computer and enhance learning in the classroom making it more student-centered, more active, and allowing students to analyze problems that have been heretofore beyond the scope of K-12 classrooms. Students in primary school have used behavior over time graphs to demonstrate dynamics described in story books, like the Lorax, and created stock-flow diagrams to describe what was needed …

Drone Detection Using Yolov5, Burchan Aydin, Subroto Singha

Faculty Publications

The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). …

Seismic Azimuthal Anisotropy Beneath A Fast Moving Ancient Continent: Constraints From Shear Wave Splitting Analysis In Australia, Kailun Ba, Stephen S. Gao, Jianguo Song, Kelly H. Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Seismic Azimuthal Anisotropy Beneath Australia is Investigated using Splitting of the Teleseismic PKS, SKKS, and SKS Phases to Delineate Asthenospheric Flow and Lithospheric Deformation Beneath One of the Oldest and Fast-Moving Continents on Earth. in Total 511 Pairs of High-Quality Splitting Parameters Were Observed at 116 Seismic Stations. Unlike Other Stable Continental Areas in Africa, East Asia, and North America, Where Spatially Consistent Splitting Parameters Dominate, the Fast Orientations and Splitting Times Observed in Australia Show a Complex Pattern, with a Slightly Smaller Than Normal Average Splitting Time of 0.85 ± 0.33 S. on the North Australian Craton, the Fast …

Learning Relation Prototype From Unlabeled Texts For Long-Tail Relation Extraction, Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting entity relations from texts. However, it usually suffers from the long-tail issue. The training data mainly concentrates on a few types of relations, leading to the lack of sufficient annotations for the remaining types of relations. In this paper, we propose a general approach to learn relation prototypes from unlabeled texts, to facilitate the long-tail relation extraction by transferring knowledge from the relation types with sufficient training data. We learn relation prototypes as an implicit factor between entities, which reflects the meanings of relations as well …

Water Resources Planning Under Deep Uncertainty For Physically, Socially, And Politically Complex Systems, Sarah St. George Freeman

Doctoral Dissertations

Water supply systems, particularly those of large cities, are complex systems linking supply, regulatory and distribution infrastructure, and points of use. Despite their physical complexities, it is infrequent that full supply, distribution, end use, and feedbacks therein are considered in an integrated manner. These complex systems-of-systems face large uncertainties related to physical aspects such as degradation of infrastructure, changing demand, and climate variability and change. Though great, such physical uncertainties often pale in comparison to the those related to the human systems in place to manage them and yet uncertainty in the decision-making landscape is often grossly simplified in our …

Towards Machine Learning-Based Fpga Backend Flow: Challenges And Opportunities, Imran Taj, Umer Farooq

All Works

Field-Programmable Gate Array (FPGA) is at the core of System on Chip (SoC) design across various Industry 5.0 digital systems—healthcare devices, farming equipment, autonomous vehicles and aerospace gear to name a few. Given that pre-silicon verification using Computer Aided Design (CAD) accounts for about 70% of the time and money spent on the design of modern digital systems, this paper summarizes the machine learning (ML)-oriented efforts in different FPGA CAD design steps. With the recent breakthrough of machine learning, FPGA CAD tasks—high-level synthesis (HLS), logic synthesis, placement and routing—are seeing a renewed interest in their respective decision-making steps. We focus …

Coreflooding Evaluation Of Fiber-Assisted Recrosslinkable Preformed Particle Gel Using An Open Fracture Model, Shuda Zhao, Ali Al Brahim, Junchen Liu, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Recrosslinkable Preformed Particle Gels (RPPGs) Have Been Used to Treat the Problem of Void Space Conduits (VSC) and repair the "Short-Circuited" Waterflood in Alaska's West Sak Field. Field Results Showed a 23% Increase in Success Rates over Typical Preformed Particle Gel (PPG) Treatments. in This Paper, We Evaluated Whether Adding Fiber into RPPGs Can Increase the RPPG Plugging Efficiency and Thus Further Improve the Success Rate. We Designed Open Fracture Models to Represent vs.C and Investigated the Effect of Swelling Ratio (SR), Fracture Size, and Fiber Concentration on Gel Injection Pressure, Water Breakthrough Pressure, and Permeability Reduction. Results Show that …

Polyethersulfone Thin-Film Nanocomposite Membrane Embedded With Amine-Functionalized Graphene Oxide For Desalination Applications, Ahmed Bahaeldin

Theses and Dissertations

Thin-film nanocomposite (TFN) desalination membranes were prepared based on a polyethersulfone (PES) support, where the polyamide (PA) layer was embedded with amine-functionalized graphene oxide (GO). The effect of adding various concentrations of functionalized and un-functionalized GO on the desalination performance, hydrophilicity, and morphology of the membranes was additionally assessed throughout this work. Scanning electron microscopy (SEM) measurements were used to assess the morphology of the membranes in combination with Brunauer-Emmett-Teller (BET) analysis. Contact angle measurements were used to gauge the hydrophilicity of the synthesized membranes. The membrane with the best desalination performance contained 1x10^-3 wt/vol% of functionalized GO in …

Electromagnetic Theory And Applications, Nicholas Madamopoulos, George Kliros

Open Educational Resources

This book intends to provide both the fundamentals of Electromagnetics but also some practical applications of the concepts covered. Having taught electromagnetics for several years, the authors feel that many times the field of electromagnetics comes as “old” and often times students do not appreciate the concepts and their importance in everyday applications. The authors intend to accompany the EM concepts with life applications. Hence, students may see the direct impact of the knowledge they acquire through the study of the field of electromagnetics and better appreciate the field.

Recent Advances In Exploring Highly Active & Durable Pgm-Free Oxygen Reduction Catalysts, Yuan Li, Miao-Ying Chen, Bang-An Lu, Jia-Nan Zhang

Journal of Electrochemistry

In order to reduce the considerable usage of expensive but scarce platinum at the cathode in proton exchange membrane fuel cells (PEMFCs), it is necessary to pursue alternatives to platinum. The most promising platinum group metal (PGM)-free catalysts for oxygen reduction reaction (ORR) are atomically dispersed, and nitrogen-coordinated metal site catalysts denoted as M-N-C (M = Fe, Co, or Mn, etc.). Over the last few decades, there have been great advances in these catalysts with high ORR activity and promising initial fuel cell performance approaching traditional Pt/C catalysts. However, the stability of these highly active Fe-N-C catalysts under practical fuel …

Preface To Special Issue: Electrocatalysis And Electrosynthesis (Ⅰ), Fang-Yi Cheng, Shuang-Yin Wang, Tian-Hua Zhou

Journal of Electrochemistry

No abstract provided.

Research Progress In Cucurbit[N]Uril-Based Metal Nanomaterials For Electrocatalytic Applications, Zong-Nan Wei, Min-Na Cao, Rong Cao

Journal of Electrochemistry

Metal nanomaterials have exhibited excellent performance in electrocatalytic applications, but they still face the problems of poor stability and limited regulation strategies. It is an efficient strategy for greatly enhanced catalytic activity and stability by introducing a second component. In this review, we provide the sketch for the combination of metal nanomaterials and cucurbit[n]urils (CB[n]s) in electrocatalytic applications. CB[n]s are a series of macrocycles with rigid structure, high stability, and function groups for coordinating with metal sites, which make them promising to stabilize and modulate the metal nanomaterials for ideal performance. The discussion classifies the roles of CB[n]s, involving CB[n]s …

Electrochemical Oxidation Of Ethylene On Palladium Electrode, Wei-Xing Wu, Ying Wang

Journal of Electrochemistry

The electrochemical oxidation of C₂H₄ is attracting increasing attention due to its vast potential market. The current electrochemical methods rely on the use of redox mediators, which may produce corrosive intermediates, while direct oxidation is still limited by its low activity and selectivity. Herein, we conducted electrochemical studies to obtain mechanistic insights into the benchmark Pd catalyst. The generated Pd(II) could be the active site for C₂H₄ oxidation. By designing the pulse sequence, we found the ratio of strongly and weakly adsorbed C₂H₄ on Pd to be 0.3:1. The result we …

Supperlattice-Like Structure: Ordered Mass Transfer Endowing High Quality Output Of Fuel Cell, Jian Wang, Wen-Hui Xuan, Qian He, Jing-Xia Jiang, Yuan-Yuan Zhou, Yao Nie, Qiang Liao, Min-Hua Shao, Wei Ding, Zi-Dong Wei

Journal of Electrochemistry

The current or voltage fluctuation in fuel cell operation is harmful to the fuel cell system and power application equipment. Here, we report a technique to eliminate such a fluctuation by the aid of new type of catalysts, superlattice-like mesoporous PtCo catalysts. The current fluctuation in fuel cells catalyzed by two invented catalysts are fixed at as low as 25 mA·cm⁻² with a power of 0.75 W·cm⁻² or 120 mA·cm⁻² with a power of 1.01 W·cm⁻², and no noticeable current decay was detected over 100 h. By contrast, a …

Completeness Of Nominal Props, Samuel Balco, Alexander Kurz

Engineering Faculty Articles and Research

We introduce nominal string diagrams as string diagrams internal in the category of nominal sets. This leads us to define nominal PROPs and nominal monoidal theories. We show that the categories of ordinary PROPs and nominal PROPs are equivalent. This equivalence is then extended to symmetric monoidal theories and nominal monoidal theories, which allows us to transfer completeness results between ordinary and nominal calculi for string diagrams.

Time Domain Reflectometry Waveform Interpretation With Convolutional Neural Networks, Zhuangji Wang, Shan Hua, Dennis Timlin, Yuki Kojima, Songtao Lu, Wenguang Sun, David Fleisher, Robert Horton, Vangimalla R. Reddy, Katherine Tully

Nebraska Water Center: Faculty Publications

Interpreting time domain reflectometry (TDR) waveforms obtained in soils with non-uniform water content is an open question. We design a new TDR waveform interpretation model based on convolutional neural networks (CNNs) that can reveal the spatial variations of soil relative permittivity and water content along a TDR sensor. The proposed model, namely TDR-CNN, is constructed with three modules. First, the geometrical features of the TDR waveforms are extracted with a simplified version of VGG16 network. Second, the reflection positions in a TDR waveform are traced using a 1D version of the region proposal network. Finally, the soil relative permittivity values …

Lysine Crosslinked Polyacrylamide─A Novel Green Polymer Gel For Preferential Flow Control, Tao Song, Baojun Bai, Yugandhara Eriyagama, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Acrylamide-based polymer gels have been applied to control the preferential flow in the subsurface for decades. However, some commonly used crosslinkers, such as Cr (III) and phenol-formaldehyde, are highly toxic and are being phased out because of stringent environmental regulations. This work uses l-lysine as the green crosslinker to produce acrylamide-based polymer gels. This article systematically studied the effect of lysine and polymer concentration, salinity, pH, and temperature on gelation behavior and thermal stability. Besides, the gelation mechanism and crosslinking density were elucidated in this work. A high-permeability sandstone core was used to test the plugging efficiency of this novel …

Development Opportunities And Technical Challenges Of Industrialization For Hydrogen Production From Bio-Ethanol Reforming, Xue Han, Hong He, Guojun Yue, Hailong Lin, Jinsong Liu, Bin Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Bio-ethanol reforming for hydrogen production, using renewable raw materials and adopting mature and efficient chemical processes, is an important source of green hydrogen supply to achieve the goals of carbon peaking and carbon neutrality. Bio-ethanol is a widely used substitute for fossil fuels. With the continuous progress of cellulosic ethanol technology in recent years, bio-ethanol will gradually break through the constraints of starch-based raw material supply. Based on the industrialization achievements of hydrogen production and bio-ethanol, bio-ethanol reforming can realize a rapid linkage with the existing hydrogen energy industry. However, the existence of a carbon-carbon signal bond in ethanol poses …

Workforce Of The Future Begins With Aviation Stem, Lyndsay Digneo

National Training Aircraft Symposium (NTAS)

The United States has always been a world leader in aviation. This leadership position relies on the strength of the American STEM workforce and the quality of the nation’s educational, industrial, and government institutions. Therefore, it is imperative to nurture today’s students to become a well-trained STEM workforce in the future.

The Federal Aviation Administration (FAA) William J. Hughes Technical Center (WJHTC) recognizes that in pursuing its mission of aviation research, engineering, development, and test and evaluation, it is in a unique position to support aviation STEM activities for schools (K-12), post-secondary institutions, and community organizations. In 2016, the Technical …