Physical Sciences and Mathematics Commons^™

Learning-Based Ant Colony Optimization Algorithm For Solving A Kind Of Complex 2-Echelon Vehicle Routing Problem, Xue Chen, Rong Hu, Hui Wang, Zuocheng Li, Bin Qian, Yixu Li

Journal of System Simulation

Abstract: Aiming at green 2-echelon vehicle routing problem with simultaneous pick-up and delivery, a learning-based ant colony optimization algorithm combined with clustering decomposition is proposed. The objective function to be minimized is total transportation cost wherein carbon emission cost is specially considered. Associated with the mutual coupling features of the 2-echelon vehicle routing problem, we propose a distance-based clustering method to decompose the original problem into a set of sub-problems. Then, a learning-based ant colony optimization algorithm is presented to find the solutions of the sub-problems based on which the solution of the original problem can be obtained. In the …

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …

Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao

Journal of System Simulation

Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.

Performative Mixing For Immersive Audio, Brian A. Elizondo

LSU Doctoral Dissertations

Immersive multichannel audio can be produced with specialized setups of loudspeakers, often surrounding the audience. These setups can feature as few as four loudspeakers or more than 300. Performative mixing in these environments requires a bespoke solution offering intuitive gestural control. Beyond the usual faders for gain control, advancements in multichannel sound demand interfaces capable of quickly positioning sounds between channels. The Quad Cartesian Positioner is such a solution in the form of a Eurorack module for surround mixing for use in live or studio performances.

Diffusion/mixing methods for live multichannel immersive music often rely on the repurposing of hardware …

Composite Index Of Anthropometric Failure And Early Childhood Cognitive Development Based On The 2018 Indonesian Basic Health Research Data, Safira Zamrudiani, Abdul Wahab, Rosalia Kurniawati Harisaputra

Kesmas

Delays in early childhood cognitive development may have profound long-term implications on health and life expectancy. Optimal nutrition supports early life development, including a child's cognitive development. This study aimed to determine the association between the Composite Index of Anthropometric Failure and early childhood cognitive development among children aged 36-59 months in Indonesia. This cross-sectional study utilized data from the 2018 Indonesian Basic Health Research that involved 18,027 participants aged 36-59 months. This study outcome demonstrated that children who were stunted-underweight were potentially susceptible to delayed cognitive development compared to those with normal nutritional status (aOR = 1.30; 95% CI …

A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty

Turkish Journal of Electrical Engineering and Computer Sciences

Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …

Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol

Turkish Journal of Electrical Engineering and Computer Sciences

Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches' results not only …

Development Of Combat Concept Of Intelligent Land Assault System Based On Dodaf, Can Wang, Haoran Ji, Qisheng Guo, Zhiming Dong, Yaxin Tan, Ge Mu

Journal of System Simulation

Abstract: In view of military demand traction in the development of land assault equipment, a combat concept of land assault systems for future intelligent combat is developed. Basedon the definition of relevant concepts and research boundaries, the combat concept model framework and modeling steps are proposed based on DoDAF, and the combat effect, combat process, combat nodes, resource interaction, system composition, and capability characteristics are analyzed in combination with the model description. The combat concept verification is carried out from the aspects of system combat efficiency and communication load by simulation experiments. The results show that the intelligent assault system …

Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances, Xiaohu Yan, Yuwu Yao, Yuhua Wu, Jiangxin Xu

Journal of System Simulation

Abstract: A stochastic control scheme of adaptive robust trajectory tracking is proposed for near space vehicle (NSV) with stochastic noise input disturbances, Poisson random fluctuation disturbances, and control input saturation. The effective tracking of the height and speed reference signals is realized. For the outer loop trajectory control, the robust stochastic controller is designed for the height subsystem and the speed subsystem respectively. Additionally, the required attitude angle reference signals for the inner loop attitude control are obtained by converting the equivalent control input via numerical calculation. For the inner loop attitude control problems, an adaptive robust stochastic control scheme …

A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections, Yulong Sun, Jianfeng Zheng, Jiaxuan Han, Chao Li

Journal of System Simulation

Abstract: For improving the traffic efficiency of wide and narrow alternating waterways, considering Kiel Canal as an example, according to the structural characteristics of Kiel Canal with alternating width and narrow sections, a two-way ship traffic flow cellular automata model is established, and the simulation of ships passing through Kiel Canal is studied. Cellular space is set up according to the actual structure of Kiel Canal, and the evolution rules are set up based on the fixed block theory and moving block theory. In particular, due to the structure of Kiel Canal, large ships cannot pass simultaneously in the narrow …

Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu

Journal of System Simulation

Abstract: A rolling bearing fault diagnosis method based on a weighted domain adaptive convolutional neural network (WDACNN) is proposed to solve the problem that the data distribution of vibration signals of rolling bearings changes due to workload changes, which leads to poor generalization of fault diagnosis algorithm. In this method, the domain adaptation algorithm is embedded in the convolutional neural network to make the classifier based on the source domain achieve excellent generalization in the target domain, and the weight coefficient is introduced to weight the samples in the source domain to reduce the influence of the class weight deviation. …

Medical Monitoring Working Group Meeting Minutes, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Editorial: The Public Health Scholars As The Health Leaders, Al Asyary, Meita Veruswati, Putri Bungsu Machmud, Indri Hapsari Susilowati

Kesmas

1. Achmadi UF. Kesehatan Masyarakat: Teori dan Aplikasi. Jakarta: Rajawali Pers; 2014.

2. Asyary A. Editorial. Kesmas. 2023; 18 (Special Issue 1): 1-3. DOI: 10.21109/kesmas.v18isp1.7201

3. Badan Kebijakan Pembangunan Kesehatan. Pembangunan Kesehatan di Indonesia melalui Kesinambungan Finansial Jaminan Kesehatan serta Meningkatkan Kualitas Layanan dengan Integrasi Data. Jakarta: Kementerian Kesehatan Republik Indonesia; 2023.

Microscale To Mesoscale Modeling Of The Ocean Under Tropical Cyclones: Effects Of Sea Spray And Surfactants On Tropical Cyclone Intensity And Air-Sea Gas Exchange, Breanna Lynn Cain Vanderplow

All HCAS Student Capstones, Theses, and Dissertations

Tropical cyclone intensity prediction remains a challenge despite computational and observational developments because successful intensity forecasting requires implementing a multitude of atmospheric and oceanic processes. Hurricane Maria 2017 and Hurricane Dorian 2019 serve as prime examples of rapidly intensifying storms that devastated communities in the Caribbean. A lack of understanding and parameterization of crucial physics involved in tropical cyclone intensity in existing forecast models may have led to these and other forecasting errors.

Microscale physical processes at the air-sea interface are a major factor in intensification of tropical cyclones that are often unaccounted for in forecasting models since they are …

2023 November 30 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Data From: Climate Change-Driven Cumulative Mountain Pine Beetle-Caused Whitebark Pine Mortality In The Greater Yellowstone Ecosystem, William W. Macfarlane

Browse all Datasets

In 2018-2019 the Landscape Assessment System (LAS), an aerial survey method was used to assess mountain pine beetle (Dendroctonus ponderosae; MPB) - caused mortality of whitebark pine (Pinus albicaulis) across the Greater Yellowstone Ecosystem (59000 km2; GYE). This consisted of 11,942 km of flightlines, along which 4,434 geo-tagged, oblique aerial photos were captured and processed. A mortality rating of none to severe (0 to 4 nt attack or 5.0 5.4 old attack) was assigned to each photo based on the amount of red (recent attack) and gray (old attack) trees visible. The method produced a photo inventory of 74 percent …

An Empirical Study On The Use Of Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi

Thesis/ Dissertation Defenses

Trade contributes to the United Arab Emirates' economic growth. This thesis focuses on trade dynamics in the UAE using Long Short-Term Memory (LSTM) neural networks. The study focuses on both import and export activities, providing understandings into the complex patterns and impacts of international trade on the UAE's economic growth. The research begins by constructing an LSTM model to forecast the UAE's Gross Domestic Product (GDP) through the utilization of historical trade data. We use time series data for imports and exports as key input features. This innovative approach highlights the relevance of trade statistics as a leading indicator of …

Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed

Thesis/ Dissertation Defenses

The widespread applications of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has given rise to significant national security threats due to their illicit activities. Consequently, the domain of UAV forensics is rapidly evolving, presenting a substantial knowledge deficit among forensic experts. Open-source tools provide accessible and affordable resources, making it easier for investigators to bridge this gap by gaining expertise in the use of these tools. This helps ensure that forensic professionals can keep up with the ever-changing UAV technology landscape. This thesis undertakes the mission of navigate the complex field of drone forensics and conducting a comprehensive …

Lie Algebras And Lie Groups, Nhi Nguyen

Algebra Seminar

No abstract provided.

The Heisenberg Lie Algebra And Its Role In The Quantum Mechanical Harmonic Oscillator, Angelina Georg

Algebra Seminar

No abstract provided.

Irreducible Representations Of Sl(2,C), Della Medovoy

Algebra Seminar

No abstract provided.

Understanding Collective Performance: Human Factors And Team Science, Joseph Keebler

Math Department Colloquium Series

This talk will focus on modern issues with team science. Joe will discuss a variety of projects he's been involved with aimed at improving teamwork in complex sociotechnical systems including military, aviation, and healthcare. He will discuss major theoretical facets of teamwork and provide evidence-based best practices that were utilized to improve teams in applied settings.

Irreducible Representations Of Sl(2,C), Della Medovoy

Mathematics Colloquium Series

No abstract provided.

Lie Algebras And Lie Groups, Nhi Nguyen

Mathematics Colloquium Series

No abstract provided.

The Heisenberg Lie Algebra And Its Role In The Quantum Mechanical Harmonic Oscillator, Angelina Georg

Mathematics Colloquium Series

No abstract provided.

Painting Our Treescapes: A Visual, Gretel Olson, Ingrid Olson, Stephanie Schuurman-Olson

Occasional Paper Series

Two children (ages 6 and 9) represent an afternoon spent in their urban, wintery treescape through visual art, photo documentation, and written narrative. The first piece, "My Imaginary Forest", considers the seasons, animals, and issues of artistic representation of nature. The second piece describes the relationship between a favourite tree and a child, and considers others -- both present and future -- who also occupy "Our Knotty Tree". All of the words, visual art, and photo selection are those of the children.

Data Quality Checks: Implementation With Popular Data Collection Crowdsourcing Platforms, James Down, Gregory Balkcom, Kristine Duncan, Ngan (An) Truong, Andrew Lewis

Symposium of Student Scholars

The utilization of online crowdsourcing platforms for data collection has increased over the past two decades in the field of public health due to the ease of use, the cost-saving benefits, the speed of the data collection process, and the accessibility of a potentially true representative population. Although these platforms offer many advantages to researchers, significant drawbacks exist, such as poor data quality, that threaten the reliability and validity of the study. Previous studies have examined data quality concerns, but differences in results arise due to variations in study designs, disciplinary contexts, and the platforms being investigated. Therefore, this study …

Machine Learning In Minecraft: Proof Of Concept For Object Detection Oriented Autonomous Bots In Minecraft, John Merkin

Symposium of Student Scholars

Machine learning provides new methods of problem solving through applied pattern recognition. An interesting challenge is to utilize machine learning in the automation of tasks and behaviors in virtual environments. Minecraft is an open-world, sandbox style game giving players nearly limitless freedom to alter a procedurally generated world. In the survival game mode, the player must collect resources to craft tools and build structures. The collection of resources can be tedious, so this project seeks to automate the standard initial task of collecting wood. By combining a convolutional neural network with API, a bot can collect resources while remaining scalable …

Toxic Comment Classification Project, Brandon Solon

Symposium of Student Scholars

The digital landscape has blossomed thanks to the surge of online platforms, boosting the variety and volume of user-created content. But it's not without its shadows; cyberbullying and hate speech have also proliferated, making web spaces less safe. At our project centerstage, we work on creating a machine learning model skilled at spotting toxic comments with precision - this way contributing towards an internet society free from fear or discomfort. We put well-documented datasets to good use along with careful preprocessing maneuvers while trialing diverse machina-learning protocols as part of constructing solid classification architecture for usages beyond current limitations within …