The Application Of Novel Machine Learning Algorithms To Study Multi-Dimensional Fragmentation Functions Of Hadrons In Jets At Star,
2024
University of Kentucky
The Application Of Novel Machine Learning Algorithms To Study Multi-Dimensional Fragmentation Functions Of Hadrons In Jets At Star, Hannah A. Harrison-Smith
Theses and Dissertations--Physics and Astronomy
Hadronization, the process by which colored quarks and gluons shower from high energy collisions and recombine to form stable, experimentally-observable particles, is a fundamental aspect of Quantum Chromodynamics (QCD) that is not yet fully understood. Fragmentation functions, typically measured in electron-positron collisions, encapsulate this hadronization process well for quarks. Studying proton-proton collisions offers direct access to gluon fragmentation that other channels like electron-positron do not. Recent theoretical developments have proposed the study of hadronic showers in groupings called jets, introducing the concept of multi-dimensional jet fragmentation functions. This thesis presents the extraction of collinear and transverse momentum-dependent fragmentation functions for …
Speculative Anisotropic Mesh Adaptation On Shared Memory For Cfd Applications,
2024
Old Dominion University
Speculative Anisotropic Mesh Adaptation On Shared Memory For Cfd Applications, Christos Tsolakis, Nikos Chrisochoides
Computer Science Faculty Publications
Efficient and robust anisotropic mesh adaptation is crucial for Computational Fluid Dynamics (CFD) simulations. The CFD Vision 2030 Study highlights the pressing need for this technology, particularly for simulations targeting supercomputers. This work applies a fine-grained speculative approach to anisotropic mesh operations. Our implementation exhibits more than 90% parallel efficiency on a multi-core node. Additionally, we evaluate our method within an adaptive pipeline for a spectrum of publicly available test-cases that includes both analytically derived and error-based fields. For all test-cases, our results are in accordance with published results in the literature. Support for CAD-based data is introduced, and its …
Bayesian Neural Netwok Variational Autoencoder Inverse Mapper (Bnn-Vaim) And Its Application In Compton Form Factors Extraction,
2024
Old Dominion University
Bayesian Neural Netwok Variational Autoencoder Inverse Mapper (Bnn-Vaim) And Its Application In Compton Form Factors Extraction, Md Fayaz Bin Hossen, Tareq Alghamdi, Manal Almaeen, Yaohang Li
Computer Science Faculty Publications
We extend the Variational Autoencoder Inverse Mapper (VAIM) framework for the inverse problem of extracting Compton Form Factors (CFFs) from deeply virtual exclusive reactions, such as the unpolarized Deeply virtual exclusive scattering (DVCS) cross section. VAIM is an end-to-end deep learning framework to address the solution ambiguity issue in ill-posed inverse problems, which comprises of a forward mapper and a backward mapper to simulate the forward and inverse processes, respectively. In particular, we incorporate Bayesian Neural Network (BNN) into the VAIM architecture (BNN-VAIM) for uncertainty quantification. By sampling the weights and biases distributions of the BNN in the backward mapper …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques,
2024
Georgia Southern University
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
College of Graduate Studies: Theses & Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
Quantifying Potential Marine Debris Sources And Potential Threats To Penguins On The West Antarctic Peninsula,
2024
Stony Brook University
Quantifying Potential Marine Debris Sources And Potential Threats To Penguins On The West Antarctic Peninsula, Katherine L. Gallagher, Megan A. Cimino, Michael S. Dinniman, Heather J. Lynch
OES Faculty Publications
Marine pollution is becoming ubiquitous in the environment. Observations of pollution on beaches, in the coastal ocean, and in organisms in the Antarctic are becoming distressingly common. Increasing human activity, growing tourism, and an expanding krill fishing industry along the West Antarctic Peninsula all represent potential sources of plastic pollution and other debris (collectively referred to as debris) to the region. However, the sources of these pollutants from point (pollutants released from discrete sources) versus non-point (pollutants from a large area rather than a specific source) sources are poorly understood. We used buoyant simulated particles released in a high-resolution physical …
Quantitative Verification For Massive Linear Systems,
2024
University of Nebraska-Lincoln
Quantitative Verification For Massive Linear Systems, Qing Liu
School of Computing: Dissertations, Theses, and Student Research
The verification of linear systems has been an active area of research for decades. Reachability analysis is a key component in verification problems. It involves computing the system’s reachable set, the set of reachable states in the state space from a given set of initial states. Most verification methods primarily focus on qualitative verification, which answers whether or not a system may violate specified safety conditions. This paper extends this qualitative verification to quantitative verification by introducing a novel approach, employing probabilistic stars (Probstars) to compute reachable sets, which augment traditional star sets by integrating Gaussian-distributed random variables with …
Identifying And Predicting Patterns Of Snowpack Ripening With Machine Learning Methods,
2024
University of Montana, Missoula
Identifying And Predicting Patterns Of Snowpack Ripening With Machine Learning Methods, Clement Cherblanc
Graduate Student Theses, Dissertations, & Professional Papers
The timing of water release from the snowpack plays key roles in ecosystem services, groundwater recharge, and water resource management. However, two internal barriers in a standing snowpack must be overcome before runoff can outflow from the base: 1) the cold content must be exhausted, and 2) the interconnected network of snow grains must be filled with liquid water to residual saturation. Expressing the liquid water as latent heat allows the two barriers to be grouped as an energy (J/m²) to define a snowpack’s Runoff Energy Hurdle (REH). The growth and loss of REH is driven by evolution of pore …
Crop Yield Using Novel Parametric L-System Plant Modelling,
2024
Edith Cowan University
Crop Yield Using Novel Parametric L-System Plant Modelling, Christopher Cameron Napier
Theses: Doctorates and Masters
This research considers a system for the recognition of real plant parts through image analysis based upon synthetic plant modelling. It aims to use data pipelines and synthetic datasets to define recognizable features that assist in the efficient analysis of real plants and plant images. This research asks about the efficacy of L-systems in accurately simulating wheat crop characteristics. It specifically focusses on readable, understandable, accurate, and complex L-system algorithms. The research examines wheat crops in terms of phenotypes and examines the accuracy of a dataset in support of real image annotation. The methodology used was experimental in nature and …
Tracking People Across Ultra Populated Indoor Spaces By Matching Unreliable Wi-Fi Signals With Disconnected Video Feeds,
2024
Singapore Management University
Tracking People Across Ultra Populated Indoor Spaces By Matching Unreliable Wi-Fi Signals With Disconnected Video Feeds, Quang Hai Truong, Dheryta Jaisinghani, Shubham Jain, Arunesh Sinha, Jeong Gil Ko, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Tracking in dense indoor environments where several thousands of people move around is an extremely challenging problem. In this paper, we present a system — DenseTrack for tracking people in such environments. DenseTrack leverages data from the sensing modalities that are already present in these environments — Wi-Fi (from enterprise network deployments) and Video (from surveillance cameras). We combine Wi-Fi information with video data to overcome the individual errors induced by these modalities. More precisely, the locations derived from video are used to overcome the localization errors inherent in using Wi-Fi signals where precise Wi-Fi MAC IDs are used to …
Glance To Count: Learning To Rank With Anchors For Weakly-Supervised Crowd Counting,
2024
Singapore Management University
Glance To Count: Learning To Rank With Anchors For Weakly-Supervised Crowd Counting, Zheng Xiong, Liangyu Chai, Wenxi Liu, Yongtuo Liu, Sucheng Ren, Shengfeng He
Research Collection School Of Computing and Information Systems
Crowd image is arguably one of the most laborious data to annotate. In this paper, we devote to reduce the massive demand of densely labeled crowd data, and propose a novel weakly-supervised setting, in which we leverage the binary ranking of two images with highcontrast crowd counts as training guidance. To enable training under this new setting, we convert the crowd count regression problem to a ranking potential prediction problem. In particular, we tailor a Siamese Ranking Network that predicts the potential scores of two images indicating the ordering of the counts. Hence, the ultimate goal is to assign appropriate …
Cooperative Trucks And Drones For Rural Last-Mile Delivery With Steep Roads,
2024
Singapore Management University
Cooperative Trucks And Drones For Rural Last-Mile Delivery With Steep Roads, Jiuhong Xiao, Ying Li, Zhiguang Cao, Jianhua Xiao
Research Collection School Of Computing and Information Systems
The cooperative delivery of trucks and drones promises considerable advantages in delivery efficiency and environmental friendliness over pure fossil fuel fleets. As the prosperity of rural B2C e-commerce grows, this study intends to explore the prospect of this cooperation mode for rural last-mile delivery by developing a green vehicle routing problem with drones that considers the presence of steep roads (GVRPD-SR). Realistic energy consumption calculations for trucks and drones that both consider the impacts of general factors and steep roads are incorporated into the GVRPD-SR model, and the objective is to minimize the total energy consumption. To solve the proposed …
Comparison Of Convolutional Neural Network Architecture On Detection Of Helmet Use By Humans,
2023
Universitas Amikom Yogyakarta, Indonesia
Comparison Of Convolutional Neural Network Architecture On Detection Of Helmet Use By Humans, H. Hartatik, Muhammad Khoirul Anam
Elinvo (Electronics, Informatics, and Vocational Education)
The helmet is one of the protective equipment for the head when driving. Although it is a protector, some criminals misuse helmets to disguise their identities, such as robbery at ATMs. Some places have put a sticker not to wear a helmet in the ATM room. However, this advice is often violated. The research adopted the Convolutional Neural Network (CNN) algorithm to identify humans who use helmets and do not use helmets based on digital images. Several CNN models, such as MobileNet-V2, ResNet-50, and VGG-16, were compared in performance. The experiment was carried out using a dataset consisting of 3,207 …
Salt Sales Prediction Using The Moving Average Method (A Case Study Of Madura-Indonesia Salt),
2023
Departemen of Informatics, Faculty of Engineering, University of Trunojoyo, Madura, Bangkalan, Indonesia
Salt Sales Prediction Using The Moving Average Method (A Case Study Of Madura-Indonesia Salt), Muhammad Ali Syakur, Yudha Dwi Putra Negara, Aeri Rachmad, Eka Mala Sari Rochman
Elinvo (Electronics, Informatics, and Vocational Education)
Forecasting is a term used to forecast or predict the business that we run to see the direction in the future which uses historical data as the main reference. An appropriate strategy is needed to manage the production of salt raw materials properly, namely through sales forecasting. PT Budiono Madura Bangun Persada is a company engaged in salt processing with the brands "Anak pintar (AP)" and "Kapal Container (KC)" where the amount of production experiences uncertainty, namely an increase or decrease, this results in an uncertain amount of raw materials. This study aims to predict the exact amount of salt …
Classification Of Corn Seed Quality Using Residual Network With Transfer Learning Weight,
2023
University of Trunojoyo Madura, Indonesia
Classification Of Corn Seed Quality Using Residual Network With Transfer Learning Weight, Meidya Koeshardianto, Wahyudi Agustiono, Wahyudi Setiawan
Elinvo (Electronics, Informatics, and Vocational Education)
Corn is one of the main ingredients in farm animal feed. Currently, corn is preferable because widely available and cheaper in the market than others. However, it needs quality control on corn production. The company that manufactures animal feed has certain quality standards to receive corn material. On the other hand, the quality of corn produced varies greatly. Thus, quality control when receiving corn from suppliers greatly affects the quality of animal feed. The quality of feed ingredients is classified into physical properties and analytical values. Physical properties are determined so that the resulting corn can be accepted or rejected, …
Development Of Several Typical Virtual Reality Fusion Technologies,
2023
Army Academy of Armored Forces, Beijing 100072, China; PLA 32290 Troops, Jiʹnan 250002, China
Development Of Several Typical Virtual Reality Fusion Technologies, Qiqi Feng, Zhiming Dong, Wencheng Peng, Yi Dai, Bingshan Si
Journal of System Simulation
Abstract: Virtual reality fusion can realize the two-way interaction, mapping and linkage between virtual world and physical world, which attracts the attention of countries in the world. In order to sort out and make statistics on concept connotation, academic status and application of the related new technologies, digital twin, cyber-physical systems, metaverse and live-virtual-constructive simulation are taken as representatives. The comparison on the development process, functional characteristics, target trends, etc. is carried out.
Data Simulation Testing Framework For Complex Process Equipment Software,
2023
Institute of Computer Application, China Academy of Engineering Physics, Mianyang 621900, China
Data Simulation Testing Framework For Complex Process Equipment Software, Jinkun Zhang, Longfei Shi, Chi Hu, Hao Zhang, Yonghui Yang
Journal of System Simulation
Abstract: Due to the complex task, tight coupling, strict timing, and a large amount of interchange data, the technical threshold of automated testing of bus communication equipment software is high, and the implementation is difficult. The ideas of data-driven testing and keyword-driven testing are introduced, and a data simulation testing framework is proposed. Configuration rules are formulated and implemented in the framework. Testers can simulate peripheral data for complex process equipment software and implement automated testing by only focusing on the task analysis, and configuring interchange data and keywords. There is no need to develop test scripts, which reduces the …
Urban Uav Path Planning Based On Improved Beetle Search Algorithm,
2023
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Provincial Key Laboratory of Computer Science, Kunming University of Science and Technology, Kunming 650500, China
Urban Uav Path Planning Based On Improved Beetle Search Algorithm, Qingqing Yang, Minyi Deng, Yi Peng
Journal of System Simulation
Abstract: An improved SABAS is proposed to improve the safety and path smoothing of UAV missions in urban multi-obstacle environments and to obtain the shortest path. The algorithm no longer completely depends on the difference of odor concentration between the left and the right tentacles of beetle when exploring the path for position update. Instead, it makes full use of the strong searching ability of BAS algorithm, and introduces the annealing algorithm to add the neighborhood position solution of the next position, and finally selects the next best position from the neighborhood position solution. Metropolis criterion of annealing algorithm is …
Reliable Emergency Rescue Model Of Uavs Based On Blockchain,
2023
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Reliable Emergency Rescue Model Of Uavs Based On Blockchain, Mengyao Du, Kai Xu, Miao Zhang, Xiang Fu, Quanjun Yin
Journal of System Simulation
Abstract: Natural disasters may unpredictably disrupt ground communication infrastructure and transportation systems, and UAVs emergency response can deal with such uncertainties and highly dynamic scenarios. Aiming at the robustness requirements of decentralized rescue systems. UAV emergency rescue chain (UERChain) based on blockchain technology is proposed. By deploying UAV backbone nodes within a layered local network, the smart contracts for managing reputation considering UAV social relationships are designed. The blockchain is employed as a trust mechanism to realize the trustworthy interactions among distributed UAVs. Experimental results show that, UERChain has higher robustness, and within controllable resource constraints, the reputation management and …
Unrelated Parallel Machine Scheduling With Additional Resource And Learning Effect,
2023
Faculty of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China
Unrelated Parallel Machine Scheduling With Additional Resource And Learning Effect, Youlian Zheng, Deming Lei
Journal of System Simulation
Abstract: To solve unrelated parallel machine scheduling problem(UPMSP) with additional resource and learning effect, a dynamical artificial bee colony(DABC) algorithm is proposed to minimize the makespan. A new representation and decoding process is given and two initial bee swarms are constructed. A swarm evaluation method is applied to dynamically decide employed bee swarms and onlooker bee swarms. Employed bee phase and onlooker bee phase are implemented in different ways to increase exploration ability. The experimental results show that the new strategies of DABC are effective and reasonable, and can obtain results with better convergence, average value and stability, which d …
Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions,
2023
School of Economics and Management, Yanshan University, Qinhuangdao 066004, China; Center for Internet Plus and Industry Development, Yanshan University, Qinhuangdao 066004, China; Research Center of Regional Economic Development, Yanshan University, Qinhuangdao 066004, China
Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions, Yaming Zhang, Yanyuan Su, Guiru Zhao, Xiaoyu Guo
Journal of System Simulation
Abstract: Major epidemics provoke a variety of netizens' emotions. To some degree, the interaction of netizens' intense emotions determine the development direction of public opinion. Considering the complexity and dual emotional contagion, the impact of emotional factors in network public opinion is quantified to three dimensions indicators, emotional enhancement, differences and conversion rates. SIPINR public opinion propagation model is constructed. The equilibrium points and the transmission threshold are estimated and the stability is proved. The law of network public opinion propagation during major epidemics is revealed through numerical simulation. The results show that the dual emotional contagion would lead to …
