Artificial Neural Network Modeling Applied For Predicting Reformate Yield And Research Octane Number In The Reforming Process, 2024 Department of Chemical Engineering, Faculty of Engineering and Petroleum, Hadhramout University, Mukalla, Hadhramout, Yemen
Artificial Neural Network Modeling Applied For Predicting Reformate Yield And Research Octane Number In The Reforming Process, Badiea S. Babaqi, Abdelrigeeb Ali Al-Gathe, Mohd S. Takriff, Hassimi Abu Hasan, Mohammed H. Al-Douh
Hadhramout University Journal of Natural & Applied Sciences
The prediction model of the continuous catalytic regeneration reforming process was developed for expecting the reformate yield and research octane number using an Artificial Neural Network technique (ANN) to improve the process performance. The proposed model includes temperatures, pressures, and hydrogen to hydrocarbon molar ratio as input parameters while the output of the process represents reformate yield and research octane number. The ANN model was carried out to estimate the process behavior based on the Levenberg-Marquardt Algorithm, which included the nine input parameters, two hidden layers (10-5 neurons), and two parameters as network outputs. The results obtained were that the …
Iequity: An Augmented Reality Theatre Production, 2024 Western Kentucky University
Iequity: An Augmented Reality Theatre Production, Amy Pan, Kristina Arnold Dr, Alan White, Truth Tran
Posters-at-the-Capitol
Augmented reality is commonly seen being used in game development and design, typically seen through a mobile device such as a phone. However, it has rarely been tested and pushed to its limits in other settings. The main focus of this project was trying to deploy augmented reality in settings that are seen as more traditional. This will be done by taking a play, pre-written and performed by a professor at Western Kentucky University, and building an augmented reality set for the play in the background. The main software that will be used is Unity and Blender. Unity will be …
Immersive Framework For Designing Trajectories Using Augmented Reality, 2024 Embry-Riddle Aeronautical University
Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro
Publications
The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.
Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, 2023 Faculty of Science, Beirut Arab University, Debbieh, Lebanon
Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud
BAU Journal - Science and Technology
With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …
Smart System For Wheat Diseases Early Detection, 2023 Tashkent Institute of Irrigation and Agricultural Mechanization Engineers. National Research University. Address: Kary Niyaziy Str., 39, 100000, Tashkent, Uzbekistan. E-mail: rbaratov@mail.ru;
Smart System For Wheat Diseases Early Detection, Rustam Baratov, Himola Sunnatillayeva, Almardon Mamatovich Mustafoqulov
Chemical Technology, Control and Management
This paper presents a smart system for early detection of wheat plant diseases in the vegetation period. The proposed smart system allows detecting three types of wheat diseases, particularly yellow rust, powdery mildew and septoria at early stage and significantly improves the soil and ecology by locally spraying harmful chemicals just to sickness plants. The proposed diagnostic program is created in the C++ programming language. The basic structure of the smart system consists of Raspberry PI 4 MODULE, Logitech HD Pro Webcam C920, buzzer, HC-SR04 distance sensor, DC motor driver, AC motor, power supply, relay and some digital devices.
Combined Risk Based Inspection And Fault Tree Analysis For Repetitive 3-Phase Line Piping Leakage At West Java Offshore Topside Facility, 2023 Universitas Indonesia
Combined Risk Based Inspection And Fault Tree Analysis For Repetitive 3-Phase Line Piping Leakage At West Java Offshore Topside Facility, Dona Yuliati, Akhmad Herman Yuwono, Datu Rizal Asral, Donanta Dhaneswara
Journal of Materials Exploration and Findings (JMEF)
Hydrocarbon releases might result in serious consequences in various aspects. In addition to the contribution to environmental pollution, repetitive leakages need high repair costs. This study aim is to minimize potential repetitive leakage for other typical 3-phase piping systems. We conducted the risk assessment by adopting Risk Based Inspection (RBI) API 581 to identify risk level, calculating piping lifetime, recommended inspection plan and mitigations. The most relevant root causes can be obtained through quantitative Fault Tree Analysis (FTA). Observation and investigation was taken from eight 3-phase piping systems that experienced repetitive leakages. It has been found that the risk level …
Nitrogen Gas Quenching Pressure Effect On Bs S155 Alloy Steel In Vacuum Furnace, 2023 University of Indonesia, Depok
Nitrogen Gas Quenching Pressure Effect On Bs S155 Alloy Steel In Vacuum Furnace, Agus Mulyadi Hasanudin, Eddy Sumarno Siradj
Journal of Materials Exploration and Findings (JMEF)
The production of metal and alloy products requires the use of heat treatment, when during the heat treatment process, quenching is a crucial step. The quenching medium can be anything from water, a salt bath, oil, air and gas. In a vacuum furnace, pressurized gas, most frequently nitrogen (N2) gas, serves as one of the quenching mediums. One of the drawbacks of the quenching process is the distortion and dimensional change of the parts. This paper aims to investigate the influence of nitrogen gas quenching pressure on the distortion and dimensional change of aerospace actuator gear planet parts …
Pipeline Risk Analysis Optimization With Monte Carlo Method Using Gamma Distribution, 2023 University of Indonesia
Pipeline Risk Analysis Optimization With Monte Carlo Method Using Gamma Distribution, Farhan Rama Digita, Jaka Fajar Fatriansyah, Abdul Rahim Ridzuan, Hanna Ovelia, Imam Abdillah Mas'ud, Irma Hartia Tihara, Baiq Diffa Pakarti Linuwih
Journal of Materials Exploration and Findings (JMEF)
The inspection process of piping components in the oil and gas industry is one of the most crucial things, given the high risk posed by pipeline system failures, which have a huge impact on losses, both from environmental and financial aspects. Risk-based inspection with the Monte Carlo method is one of the efforts that can be made to minimize failures in piping systems, by involving data distribution to calculate the probability of component failure. Although the normal distribution is commonly used for generating random variables, its use in corrosion rate calculation can lead to overestimation due to negative corrosion rate …
Early-Age Strength And Failure Characteristics Of 3d Printable Polymer Concrete: Numerical Modelling And Experimental Testing, 2023 University of New Mexico - Main Campus
Early-Age Strength And Failure Characteristics Of 3d Printable Polymer Concrete: Numerical Modelling And Experimental Testing, Mohammad Amin Dehghani Najvani
Civil Engineering ETDs
The time-dependent rheological and early-age strength parameters of Polymer concrete (PC) were investigated. PC flow decreased, and the static yield stress and thixotropy increased as the specimen aged, while the dynamic yield stress remained unchanged. The study found that the Herschel-Bulkley model can accurately describe the PC’s rheological behavior over time. The change in cohesion strength and internal friction angle over time was observed using uniaxial unconfined compression and direct shear tests of fresh PC. A time-dependent MohrCoulomb failure criterion was established. Temperature analysis was used to determine the gel time and explain the evolution of the time-dependent early-age strength …
Numerical Investigation Of Subglottal Stenosis Effects On Human Voice Production, 2023 University of Maine
Numerical Investigation Of Subglottal Stenosis Effects On Human Voice Production, Dariush Bodaghi
Electronic Theses and Dissertations
This dissertation aimed to advance knowledge of how subglottal stenosis impacts voice production physiology. An in-house fluid-structure-acoustic interaction approach based on the hydrodynamic/acoustic splitting technique was employed. This technique was rigorously verified for simulating phonation by matching the acoustic behavior to a compressible flow solver for phonation-relevant geometries. Simulations of an idealized 2D vocal tract model demonstrated the effects of supraglottal acoustic resonance on vocal fold kinematics and glottal flow waveform. Results showed that the acoustic coupling between higher harmonics and formats generated pressure oscillations, modifying vocal fold dynamics and glottal flow rate.
A major novelty was the incorporation and …
An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, 2023 Mississippi State University
An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey
Theses and Dissertations
Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …
Convolution And Autoencoders Applied To Nonlinear Differential Equations, 2023 East Tennessee State University
Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye
Electronic Theses and Dissertations
Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …
Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., 2023 University of Louisville
Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei
Electronic Theses and Dissertations
Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …
Machine Learning For Kalman Filter Tuning Prediction In Gps/Ins Trajectory Estimation, 2023 California State University, San Bernardino
Machine Learning For Kalman Filter Tuning Prediction In Gps/Ins Trajectory Estimation, Peter Wright
Electronic Theses, Projects, and Dissertations
This project is an exploration and implementation of an application using Machine Learning (ML) and Artificial Intelligence (AI) techniques which would be capable of automatically tuning Kalman-Filter parameters used in post-flight trajectory estimation software at Edwards Air Force Base (EAFB), CA. The scope of the work in this paper is to design and develop a skeleton application with modular design, where various AI/ML modules could be developed to plug-in to the application for tuning-switch prediction.
Multicellular And Multiscale Models Of Microbes And Host Systems, 2023 Illinois State University
Multicellular And Multiscale Models Of Microbes And Host Systems, Elebeoba May
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Digital Twins Of The Living Knee: From Measurements To Model, 2023 University of Denver
Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen
Electronic Theses and Dissertations
Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …
I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, 2023 Purdue University
I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, Iman Haqiqi, Wei Hu, Ramya Kumaran, Pin-Ching Li, Nicholas Manning, Alex Michels, Ayman Nassar, Jinwoo Park, Jimeng Shi, Adam Tonks, Zhaonan Wang
I-GUIDE Forum
In this paper, we propose a new form of multidisciplinary academic collaboration that goes beyond the traditional modes of knowledge exchange. We argue that most research collaboration today is based on interactions between closely related disciplines, in which researchers share data, methods, and insights within a common framework or problem. However, such collaboration may not foster the development of the communication and management skills essential to a multi-disciplinary research career. Therefore, we suggest establishing a network of researchers from divergent, yet complementary, disciplines who are interested in improving these skills through regular interactions and feedback. The main goal of this …
Deep Semantic Hashing For Aerial Livestock Detection, 2023 California Polytechnic State University, San Luis Obispo
Deep Semantic Hashing For Aerial Livestock Detection, Shosei Anegawa, Franz Kurfess, Sumona Mukhopadhyay
College of Engineering Summer Undergraduate Research Program
The goal of this project is to be able to accurately detect and count livestock in footage captured by a drone in real time. The main problems with this arise from the fact that a drone can only carry limited computing resources, and hashing is conventionally thought of as a great method of doing image classification very quickly and thus even on low-power devices. In this project, we use both a Faster-RCNN, which is a state-of-the art object detection model as a benchmark to develop a hashing model that can perform a similar task much more quickly. These two models …
Predictive Maintenance Of Base Transceiver Station Power System Using Xgboost Algorithm: A Case Study Of Econet Wireless, Zimbabwe, 2023 Chinhoyi University of Technology
Predictive Maintenance Of Base Transceiver Station Power System Using Xgboost Algorithm: A Case Study Of Econet Wireless, Zimbabwe, Tavengwa Masamha
African Conference on Information Systems and Technology
Faults incurred by Base Transceiver Stations pose challenges to telecommunication organisations. Mostly the faults are due to BTS failures. BTS power system failures can have a significant impact on organizational performance in the telecommunications industry. These failures can cause disruptions in mobile network coverage, leading to dropped calls, slow data speeds, and difficulty connecting to the network. ECONET Zimbabwe has been experiencing unprecedented BTS power system failures for the past five years. Team Data Science Process was the pillar of the study methodology. The XGBoost algorithm was employed to develop a predictive model for the maintenance of Base Transceiver Station …
Automatic Cardiac Mri Image Segmentation And Mesh Generation, 2023 Washington University in St. Louis
Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li
McKelvey School of Engineering Theses & Dissertations
Segmenting and reconstructing cardiac anatomical structures from magnetic resonance (MR) images is essential for the quantitative measurement and automatic diagnosis of cardiovascular diseases [1]. However, manual evaluation of the time-series cardiac MRI (CMRI) obtained during routine clinical care are laborious, inefficient, and tends to produce biased and non-reproducible results [2]. This thesis proposes an end-to-end pipeline for automatically segmenting short-axis (SAX) CMRI images and generating high-quality 2D and 3D meshes suitable for finite element analysis. The main advantage of our approach is that it can not only work as a stand-alone pipeline for the automatic CMR image segmentation and mesh …