Engineering Commons^™

Analysis Of The Key Performance Indicators Between Lithologies On Mine To Crusher, Janine Figueiredo, Vidal Torres, Rodolfo Cruz, Douglas Moreira

Journal of Sustainable Mining

The evolution of the mineral economy requires greater technological developments to find a better use of resources and reserves through the relationships between the characteristics of the rocks and the need to enable the entire mining enterprise. This study focuses on the development of new rock blasting technologies that result in a more optimized fragmentation according to the lithology in the feed of the primary crusher. This methodology is known as Mine to Crusher, through which it becomes possible to minimize costs in the future prospecting of the mine and maximize productivity. For this methodology to be developed, it was …

What Effect Does Standards-Based Grading Versus Traditional Grading Have On Standardized Tests For Fifth-Grade Students In Mathematics In Arkansas?, Ruby Dean

ATU Theses and Dissertations 2021 - Present

WHAT EFFECT DOES STANDARDS-BASED GRADING VERSUS TRADITIONAL

GRADING HAVE ON STANDARDIZED TESTS FOR FIFTH GRADE STUDENTS IN MATHEMATICS IN ARKANSAS?

Ruby Earlene Dean

This study examined the effects of standards-based grading and traditional grading on standardized tests for fifth grade students in mathematics in Arkansas. The purpose of the study was to determine whether the type of grading system (traditional or standards-based) used to assess student progress makes a difference on the ACT Aspire results in fifth grade in mathematics. The information gleaned from this study will provide school leaders and teachers with information to make more informed decisions to …

Choosing Optimal Supply Radius Of Transformer Substations (Tss) In Iraq’S Cities Using Geometric Programming With Neutrosophic Coefficients, Ahmed K. Essa, Montifort Blessings Andrew Mitungwi, Tuweh Prince Gadama, Ahmed A. Salama

Neutrosophic Systems with Applications

Numerous uncertainties exist in various electricity power system problems due to the size, complexity, geographical distribution, and influence of unforeseen events in these systems, making it difficult for traditional mathematics tools based on crisp set theory to have an impact on and solve many power system problems. As a new branch of mathematical uncertainty techniques, the neutrosophic expert systems approach has therefore emerged with the development of electric power systems and has proven successful when correctly linked. The expert typically uses ambiguous or neutrosophic language to describe their empirical knowledge, such as "very likely," "quite likely," "if x is large, …

Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore

Honors College Theses

The shock absorber is an integral part of a vehicle suspension system and has a strong influence on its performance, especially in the case of motorsports. It is important to study the force versus velocity relationship, commonly known as the characteristic curve of the shock absorber both during compression and rebound. Vendor-supplied characteristics often reflect the behavior of the shock absorber in a particular setting. However, during the installation, the settings inside the shock absorber are adjusted to increase the human comfort level and performance of the vehicle. This may change the characteristic curve of the shock. The available data …

Thermal Frontal Polymerization – Applications In Coatings And Composites, Maria Martinez

LSU Doctoral Dissertations

Thermal frontal polymerization has long been used as a method to cure composites and coatings. However, this is the first time these applications have been used without the use of a catalyst, for the case of composites and coatings.

Chapter 2 discusses how to optimize cure-on-demand, thin layer coatings, using frontal polymerization. Previously, for the use of curing thin layer coating using thermal FP, it was known to just make the formulation viscous enough, as this would prevent premature quenching caused by heat loss. It was discovered that for a given layer thickness, a minimum viscosity and initiator concentration were …

Choosing Optimal Supply Radius Of Transformer Substations (Tss) In Iraq’S Cities Using Geometric Programming With Neutrosophic Coefficients, Ahmed K. Essa, Montifort Blessings Andrew Mitungwi, Tuweh Prince Gadama, Ahmed A. Salama

Neutrosophic Systems with Applications

Numerous uncertainties exist in various electricity power system problems due to the size, complexity, geographical distribution, and influence of unforeseen events in these systems, making it difficult for traditional mathematics tools based on crisp set theory to have an impact on and solve many power system problems. As a new branch of mathematical uncertainty techniques, the neutrosophic expert systems approach has therefore emerged with the development of electric power systems and has proven successful when correctly linked. The expert typically uses ambiguous or neutrosophic language to describe their empirical knowledge, such as "very likely," "quite likely," "if x is large, …

Localized Collocation Meshless Method For Modeling Transdermal Pharmacokinetics In Multiphase Skin Structures, Eduardo Divo

Math Department Colloquium Series

The human skin has a complicated structure with many multi-scale, biophysical effects impacting the propagation of skin-injected substances, such as partitioning, metabolic reactions, adsorption and elimination. An extended version of Fick’s second law governing the process of the compound diffusion in various skin layer is employed in the current work by considering the conservation of mass of the substance and the metabolic reaction of the substance in viable skin. Additionally, a model assuming linear coupling between the substance concentrations that are bound and unbound with blood was developed. Using such a model, a set of coupled partial differential equations are …

Modeling Metaverse Perceptions For Bolstering Traffic Safety Using Novel Trss-Based Owcm-Ram Mcdm Techniques: Purposes And Strategies, Mona Mohamed, Asmaa Elsayed, Marwa Sharawi

Neutrosophic Systems with Applications

The Metaverse has the potential to revolutionize various aspects of human life, including transportation systems. The integration of the Metaverse into intelligent transportation systems has the potential to significantly improve traffic safety in smart cities. By creating a virtual replica of the physical world, the Metaverse can provide a platform for testing new traffic management systems, road designs, and vehicle technologies in a controlled and safe environment before implementing them in the real world. One way to integrate the Metaverse into intelligent transportation systems (ITS) is by enhancing traffic safety. This can be achieved by developing an evaluation model that …

Uncertainty Analysis In Machine Learning Models, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

No abstract provided.

Modeling Metaverse Perceptions For Bolstering Traffic Safety Using Novel Trss-Based Owcm-Ram Mcdm Techniques: Purposes And Strategies, Mona Mohamed, Asmaa Elsayed, Marwa Sharawi

Neutrosophic Systems with Applications

The Metaverse has the potential to revolutionize various aspects of human life, including transportation systems. The integration of the Metaverse into intelligent transportation systems has the potential to significantly improve traffic safety in smart cities. By creating a virtual replica of the physical world, the Metaverse can provide a platform for testing new traffic management systems, road designs, and vehicle technologies in a controlled and safe environment before implementing them in the real world. One way to integrate the Metaverse into intelligent transportation systems (ITS) is by enhancing traffic safety. This can be achieved by developing an evaluation model that …

Nowcasting Solar Euv Irradiance With Photospheric Magnetic Fields And The Mg Ii Index, Kara L. Kniezewski, Samuel J. Schonfeld, Carl J. Henney

Student Publications

A new method to nowcast spectral irradiance in extreme ultraviolet (EUV) and far ultraviolet (FUV) bands is presented here, utilizing only solar photospheric magnetograms and the Mg II index (i.e., the core-to-wing ratio). The EUV and FUV modeling outlined here is a direct extension of the SIFT (Solar Indices Forecasting Tool) model, based on Henney et al. (2015, https://doi.org/10.1002/2014sw001118). SIFT estimates solar activity indices using the earth-side solar photospheric magnetic field sums from global magnetic maps generated by the ADAPT (Air Force Data Assimilative Photospheric Flux Transport) model. Utilizing strong and weak magnetic field sums from ADAPT maps, Henney …

Ct Image Segmentation Using Optimization Techniques Under Neutrosophic Domain, Doaa El-Shahat, Nourhan Talal, Jun Ye, Wen-Hua Cui

Neutrosophic Systems with Applications

In this paper, we introduce a hybrid technique between optimization algorithms and neutrosophic theory. This new hybridization can deal with uncertainties in brain computed tomography (CT) images in three different memberships very effectively. To prove the real-time application of this theory, a new segmentation method for brain CT medical images is presented. The grayscale medical image suffers from uncertainties and inconsistencies in the gray levels due to their bad luminance. The proposed technique addressed this problem by performing neutrosophic operations on gray levels based on the S membership function.

Enhancing Rotating Machinery Fault Diagnosis: A Dual-Head Attention Mechanism In Deep Learning Neural Networks, Qing Snyder

Dissertations

Rotating machinery is crucial to production efficiency and safety in manufacturing industries for an extended time. Ensuring machinery reliability necessitates effective diagnostic systems, particularly for rotating bearings, the key components of such equipment. Fault diagnosis in rotating machinery is essential to prevent failures and minimize downtime, thereby playing an important role in industrial operations. The application of advanced neural network techniques in industry has risen recently. Among these, attention-based neural networks, especially the Transformer models, are originally noteworthy for their sequential data handling capability. This research delves into attention-based algorithms for rotating machinery fault diagnosis, signifying a substantial advancement in …

Santa Clara Magazine, Volume 65 Number 1, Spring 2024, Santa Clara University

Santa Clara Magazine

14 - A CAMPUS ON THE RISE Six new buildings on campus aren’t the only changes brought by a successful $1 billion fundraising campaign. Lauren Loftus & Leslie Griffy

20 - HUMAN AT HEART How Santa Clara University is distinguishing itself as a leader in human-focused health care innovation. Lauren Loftus

26 - SHEPHERDING INNOVATION How wonder, and God, can make us better scientists. Brother Guy Consolmagno, S.J.

30 - THE CO-OP Santa Clara University has long been a bastion of interdisciplinary learning. A new fund is taking cross-collaboration to new heights. SCM Staff

34 - MAKE AI THE BEST …

2024- The Twenty-Eighth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the 28th Annual Symposium of Student Scholars, held on April 17-19, 2024. Includes abstracts from the presentations and posters.

Engr 691: Trustworthy Machine Learning, University Of Mississippi. School Of Engineering

GMAS Course Syllabi

No abstract provided.

Ct Image Segmentation Using Optimization Techniques Under Neutrosophic Domain, Doaa El-Shahat, Nourhan Talal, Jun Ye, Wen-Hua Cui

Neutrosophic Systems with Applications

In this paper, we introduce a hybrid technique between optimization algorithms and neutrosophic theory. This new hybridization can deal with uncertainties in brain computed tomography (CT) images in three different memberships very effectively. To prove the real-time application of this theory, a new segmentation method for brain CT medical images is presented. The grayscale medical image suffers from uncertainties and inconsistencies in the gray levels due to their bad luminance. The proposed technique addressed this problem by performing neutrosophic operations on gray levels based on the S membership function.

A Connected-Component Improvement Procedure For Relative Isolation Probability Calculation, Renzo Roel P. Tan, Kazushi Ikeda

Quantitative Methods and Information Technology Faculty Publications

Due to the prevalence of natural disasters, the resilience of networks that provide essential services to the population has been studied. A recent contribution is the probability of relative isolation, which measures the likelihood of a demand node to be unreachable by supply nodes. The existing procedure for calculation is an enumerative decision-diagram-based approach that may be resource-intensive especially on occasions when time and memory constraints are imposed. In response, the study reverse-engineers the current method towards increased efficiency. The proposed solution hinges on the breadth-first search, producing connected components based on the sources. The algorithm is then benchmarked on …

10 Meters To Disaster: The Challenges Of Premature Application Of Circular Economy Strategies In Jakarta’S Waste Management Structure, Almira Bowo

Independent Study Project (ISP) Collection

Jakarta's complex issue of waste management encompasses a multitude of challenges that include inefficiencies in infrastructure, a lack of public awareness of the consequences of an inadequate waste system, socioeconomic disparities, and a deficiency in intersectoral collaboration. The urgency for holistic and sustainable solutions that prioritize proactive waste collection is underscored by the complexities of these dynamics. This field study paper argues that the attention that is being drawn towards trending waste management innovations, which are reactive strategies, could bring the waste crisis in Jakarta to an even more critical state. The sections will critically examine current waste management efforts …

Transport Of Multi-Phase Multi-Component Fluids In The Shallow Subsurface Influenced By Soil And Surface Boundary Conditions: Experimental And Numerical Study With Application To Natural Gas Leakage, Navodi Jayarathne

Civil and Environmental Engineering Theses and Dissertations

With the increased use of Natural Gas (NG) as a source of fuel, underground leak-related events are increasingly reported, and some are fatal. Subsurface migration and development up to flammable limits are highly dependent on leak characteristics, soil, atmospheric variables, and other surface and subsurface structural complexities. Although few studies have characterized the transient behavior of leaked NG in the shallow subsurface, the underlying mechanisms and their interactions are not well understood, which prevents prediction of the impact of environmental and operating conditions on gas migration. The study conducted a series of field scale-controlled release experiments and numerical simulations to …

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy

Computer Science Faculty Research & Creative Works

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …

Diagnosing Discharge Events Within A Novel Miniature Simplified Coaxial Ion Trap Mass Analyzer, David Virgil Sirbescu-Stanley

Masters Theses

Mass spectrometry is a technique that organizes material samples by mass to reveal their chemical composition by forming a spectrum. Since their invention, ion trap mass spectrometers have undergone significant enhancements. This work, funded by the National Science Foundation and in collaboration with Brigham Young University, the Simplified Coaxial Ion Trap (SCIT), attempts to simplify ion trap geometry and combine three ion traps into one device. Successful demonstration of the SCIT functionality could reduce costs, reduce manufacturing complexity, and shrink total instrument volume. At the same time, trapping capacity and analytical efficiency will be increased. However, as discussed within, challenges …

Exploring Lstm-Based Attention Mechanisms With Pso And Grid Search Under Different Normalization Techniques For Energy Demands Time Series Forecasting, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao, Bambang Widi Pratolo, Aji Prasetya Wibawa, Agung Bella Putra Utama, Abdoul Fatakhou Ba, Abdullahi Uwaisu Muhammad

Knowledge Engineering and Data Science

Advanced analytical approaches are required to accurately forecast the energy sector's rising complexity and volume of time series data. This research aims to forecast the energy demand utilising sophisticated Long Short-Term Memory (LSTM) configurations with Attention mechanisms (Att), Grid search, and Particle Swarm Optimization (PSO). In addition, the study also examines the influence of Min-Max and Z-Score normalization approaches in the preprocessing stage on the accuracy performances of the baselines and the proposed models. PSO and Grid Search techniques are used to select the best hyperparameters for LSTM models, while the attention mechanism selects the important input for the LSTM. …

Hybrid Method For User Review Sentiment Categorization In Chatgpt Application Using N-Gram And Word2vec Features, Husna Luthfiatun Nisa, Atina Ahdika

Knowledge Engineering and Data Science

The rapid development of Artificial Intelligence (AI) has significantly influenced nearly all aspects of life. One AI product widely used by people worldwide is the Chat Generative Pre-Training Transformer (ChatGPT), which can respond to questions conversationally. Although data indicates that the use of ChatGPT in Indonesia is less widespread than in other countries, a Populix survey reveals that half of the respondents have utilized ChatGPT, using AI more than once a month. This indicates its crucial role among the Indonesian population. ChatGPT is not limited to browsers; it is also available as a downloadable application on the Google Play Store. …

Convolutional Neural Network In Motion Detection For Physiotherapy Exercise Movement, Dika Fikri Laistulloh, Anik Nur Handayani, Rosa Andrie Asmara, Phillip Taw

Knowledge Engineering and Data Science

Physiotherapy focuses on movement and optimal utilization of the patient's potential. Exercise Therapy is a physiotherapy procedure that specifically focuses exercises on active and passive movements. Cerebral Palsy (CP) patients are one of the sufferers of motor disorders of the upper extremities. Cerebral Palsy (CP) patients suffer from disorders in motor functions of the upper extremities. Physiotherapy Exercise Movement has 4 categories of movement exercises for the therapy of people with upper extremity body disorders: Elbow flexor strengthening in sitting using free weights, lifting an object up, reaching diagonally in sitting, and reaching from a low surface to a high …

Optimizing Malaria Control: Granular And Cost-Effective Mosquito Habitat Index In Endemic Areas Through Satellite Imagery, Nur Ainun Daulay, Salwa Rizqina Putri, Arie Wahyu Wijayanto, Ika Yuni Wulansari

Knowledge Engineering and Data Science

Malaria, classified as a tropical disease under the Sustainable Development Goals (SDGs) indicator 3.3, remains a significant global health challenge. In this study, by taking advantage of multiple spectral composite indexes of multisource satellite imagery to capture various geospatial features relevant to the suitability of marsh mosquito habitat, we introduced the Mosquito Habitat Suitability Index (MHSI) to assess potential Anopheles mosquito breeding sites in terms of the vegetation density, water bodies, environment temperature, and humidity in any particular areas. The MHSI integrates the publicly accessible granular level of the normalized difference vegetation index, water index, land surface temperature, and moisture …

Docker Optimization Of An Automotive Sector Virtual Server Infrastructure, Leonel Hernandez, Carlos Eduardo Uc Rios

Knowledge Engineering and Data Science

Server virtualization is a powerful strategy for optimizing network infrastructure. It allows multiple virtual servers to run on a single physical server, maximizing resource utilization and improving efficiency. Deploying server virtualization using Docker technology offers a lightweight and flexible approach to optimizing network infrastructure. Docker contains package applications and their dependencies, enabling consistent and efficient deployment across various environments. Specifically, optimizing virtual server infrastructure using Docker Technology in the automotive sector focuses on improving the efficiency and management of the company's virtual server resources. By implementing Docker technology, a container platform that allows the packaging and running of applications in …

Timbre Style Transfer For Musical Instruments Acoustic Guitar And Piano Using The Generator-Discriminator Model, Widean Nagari, Joan Santoso, Esther Irawati Setiawan

Knowledge Engineering and Data Science

Music style transfer is a technique for creating new music by combining the input song's content and the target song's style to have a sound that humans can enjoy. This research is related to timbre style transfer, a branch of music style transfer that focuses on using the generator-discriminator model. This exciting method has been used in various studies in the music style transfer domain to train a machine learning model to change the sound of instruments in a song with the sound of instruments from other songs. This work focuses on finding the best layer configuration in the generator- …

Low Cost Magnetometer Calibration And Distributed Simultaneous Multipoint Ionospheric Measurements From A Sounding Rocket Platform, Joshua W. Milford

Doctoral Dissertations and Master's Theses

Low-cost and low-size-weight-and-power (SWaP) magnetometers can provide greater accessibility for distributed simultaneous measurements in the ionosphere, either onboard sounding rockets or on CubeSats. The Space and Atmospheric Instrumentation Laboratory (SAIL) at Embry-Riddle Aeronautical University has launched a multitude of sounding rockets in recent history: one night-time mid-latitude rocket from Wallops Flight Facility in August 2022 and three mid-latitude rockets from White Sands Missile Range during the October 2023 annular solar eclipse. All rockets had a comprehensive suite of instruments for electrodynamics and neutral dynamics measurements. Among this suite was one science-grade three-axis fluxgate magnetometer (Billingsley TFM65VQS / TFM100G2) and up …

Development Of On-The-Fly Quasi-Steady State Approximation For Chemical Kinetics In Cfd, Abhinav Balamurugan

Doctoral Dissertations and Master's Theses

This study analyzes the feasibility of On-The-Fly Quasi-Steady-State Approximation (OTF-QSSA) application for solving chemical kinetics within Computational Fluid Dynamics (CFD) simulations, aiming to reduce the computational demand of detailed mechanisms. An algorithm that dynamically identifies and designates Quasi-Steady-State (QSS) species at specific grid locations and instances during the simulation was developed. With this information, our method pseudo-delays the advancement of concentrations for these QSS species—effectively setting their rate of concentration change to zero for a set number iteration before updating using the detailed mechanism and thereby omitting the computationally intensive processes typically required for their calculation during those skipped iteration. …