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Extracting Permittivity And Permeability Using The Position-Insensitive And Calibration-Independent Method On A Rectangular Waveguide, James Conrad Denemark

Theses and Dissertations

Classic methods for extracting material characteristics require known measurements to accurately calibrate the network analyzer. Previous work demonstrated a position-insensitive and calibration-independent (PiCi) transmission/reflection method to extract a material’s permittivity. This thesis proposes a method with the same function, manipulated to use one empty measurement and then two samples of different thicknesses. The PiCi method is first adopted for rectangular waveguide which resulted in inaccurate permittivity data when compared to the calibrated solution. Once detector mismatch corrections were applied, the PiCi method produced accurate results. Using a 2-D numerical root search, permittivity and permeability material characteristics are now successfully extracted …

Optimization Of The Number Of Cylinder Blades In Coffee Pulper Machine: Finite Element Analysis And Simple Additive Weighting Methods, Mochamad Rifki Syahriza, Dwi Djumhariyanto, Nasrul Ilminnafik, Mahros Darsin, Danang Yudistiro, Hari Arbiantara Basuki, Robertoes Koekoeh Koentjoro Wibowo, Ahmad Syuhri, Sumarji Sumarji

Journal of Mechanical Engineering Science and Technology (JMEST)

The increasing interest in coffee in all circles means that coffee production and quality must always increase due to consumer demands. One way to maintain the quality of coffee beans is by breaking them down using a huller machine. This research aims to improve the optimization of coffee machines by modifying the cylinder blades of huller machines with variations of 3, 4, 5, and 7 cylinder blades in terms of static loading design and quality and production capacity of coffee bean breaking. The experiment was carried out using 400 rpm and breaking 10kg of dry coffee cherries every time the …

Synthesis And In Vitro Testing Of Mg-6zn-Xhap Biocomposites From Beef Bone As Biodegradable Bone Implant Material, Jojor Lamsihar Manalu, Francisca Tjhay, Theodora Kristoforus, Sovian Aritonang

Journal of Mechanical Engineering Science and Technology (JMEST)

This study aimed to develop biodegradable Mg-6Zn hydroxyapatite (Mg-6Zn HAp) biocomposites for potential use in bone replacement applications. The hydroxyapatite (HAp) powders, sourced from cow bone, were synthesized through an eco-friendly and cost-effective process, leveraging bioresources for material sustainability. The Mg-6Zn and HAp powders were mechanically mixed through ball milling for six hours to ensure homogeneity. The resultant powder mixture was then subjected to isostatic pressing at a high pressure of 570 MPa, forming a dense coin-shaped composite with a 1.5 cm diameter. This coin was consolidated in a capsule furnace at elevated temperatures for one hour to enhance material …

The Role Of Banana Peel Surface Pores Through Increasing Temperature For Efficient Hydrogen Production, Abid Fahreza Alphanoda, Erlanda Augupta Pane, Agus Riyanto, Avita Ayu Permanasari

Journal of Mechanical Engineering Science and Technology (JMEST)

Porous carbon derived from banana peel has been synthesized by increasing the temperature range variation from 180 oC - 270 oC. The prepared carbon was tested in an experiment using double-chamber photoelectrochemistry to see the results of hydrogen production. SEM-EDX, FTIR, and TGA analyses identified all banana peel carbons. Optical and electrochemical properties were analyzed and measured by UV-Vis, Tauc Relationship, and Pearson Absolute Electronegativity. The amount of hydrogen gas produced from the simulation of UV-A visible light irradiation on variations of BP-240, BP-210, BP-180, and BPNatural. The surface of BP-270 has more pores and can produce the most significant …

E-Learning Management Technology Integration For Laboratory Usage, Mohammed Khaleel Hussein, Mohammed Ahmed Subhi, Saleh Mahdi Mohammed, Mayasah Al-Khateeb

Iraqi Journal for Computer Science and Mathematics

E-learning systems have transformed educational sectors and more interestingly, the use of these educational platforms for laboratory-based practices has been trending in the last couple of years. Laboratory-usage e-learning system has various tremendous benefits such as the skill of accessibility utilization and practical experimentation simulation. Several intelligent tasks still need to be tackled to make the most of it. One of the biggest problems is how to recreate hands-on experience in a virtual or remote environment. Some e-learning systems offer simulations and virtual experiments but may also require additional tactile feedback through interaction with physical equipment for this challenge, it …

Single-Entity Collisional Electrochemistry At The Micro- And/Or Nano-Interface Between Two Immiscible Electrolyte Solutions, Li-Fang Yang, Jun-Jie Chen, Ling-Yu Chen, Si-Qi Jin, Tao-Xiong Fang, Si-Jia He, Liang-Jun Shen, Xin-Jian Huang, Xiao-Hang Sun, Hai-Qiang Deng

Journal of Electrochemistry

Single-entity collisional electrochemistry (SECE) is a branch of single-entity electrochemistry. It can directly characterize entities/particles with single particle resolution through random collisions between particles and electrodes in a solution, and obtain rich physicochemical information, thus becoming one of the frontiers of electroanalytical chemistry in the past two decades. Interestingly, the (micro/nanoscale) sensing electrodes have evolved from a polarizable liquid/ liquid (mercury/liquid) interface to a solid/liquid interface and then to a liquid/liquid interface (i.e., an interface between two immiscible electrolyte solutions, ITIES), as if they have completed a cycle (but in fact they have not). ITIES has become the latest sensing …

Benchmarking Pretrained Models For Speech Emotion Recognition: A Focus On Xception, Ahmed Hassan, Tehroom Masood, Hassan A. Ahmed, H. M. Shahzad, Hafiz Muhammad T. Khushi

Business Faculty Publications

Speech emotion recognition (SER) is an emerging technology that utilizes speech sounds to identify a speaker’s emotional state. Computational intelligence is receiving increasing attention from academics, health, and social media applications. This research was conducted to identify emotional states in verbal communication. We applied a publicly available dataset called RAVDEES. The data augmentation process involved adding noise, applying time stretching, shifting, and pitch, and extracting the features zero cross rate (ZCR), chroma shift, Mel-Frequency Cepstral Coefficients (MFCC), and a spectrogram. In addition, we used many pretrained deep learning models, such as VGG16, ResNet50, Xception, InceptionV3, and DenseNet121. Out of all …

Effect Of Roadway Lighting On Safety In Utah, Samuel Lewis Runyan

Theses and Dissertations

A significant portion of severe crashes and severe crashes involving vulnerable road users, 29 percent and 39 percent respectively, occur at night in Utah, despite roughly only 25 percent of traffic occurring at night. Nighttime crash causes are less understood than daytime crashes as there are fewer nighttime crashes, but it is generally assumed that increasing street lighting can help mitigate these crashes. To test this assumption, the Utah Department of Transportation was interested in developing Crash Modification Factors (CMFs) specific to the state of Utah which correlate the quantity and quality of light to crash outcomes, to observe how …

Evaluating The Multi-Valued Bartlett Processor, Daniel Robert Frister

Dissertations and Theses

A variety of approaches exist to track targets in the ocean using acoustic sensors, and the complex mix of source characteristics, environmental effects, and sensor array limitations can make the selection of an appropriate algorithm challenging. This thesis models in simulation a recently proposed signal processing method that is intended for use with a large rectangular sensor array to track the bearings of multiple sources. The method, referred to as the Multi-Valued Bartlett (MVB) processor, is an eigenvector beamformer that leverages the capabilities of large arrays to locate in bearing multiple sources simultaneously. The analysis of this thesis details the …

Aircraft Control, Collision Avoidance, And Remote Autonomy In Scenarios With Ground Radar Information, Jaron Charles Ellingson

Theses and Dissertations

Unmanned aircraft systems (UAS) have become integral to various modern applications, including package delivery, security, medicine, and recreation. The autonomous operation of UAS significantly enhances their utility by improving performance and reducing operator workload, enabling collaborative missions such as boundary detection, border protection, and target tracking. To ensure safe integration of UAS, more work needs to be done in the areas of control, estimation, collision avoidance, path planning, hardware implementation, and autonomous practices in general. For this dissertation we chose to focus on the critical areas of control, collision avoidance, and remote autonomy. Our research is motivated by the need …

Data Security In The Apple Ecosystem: An Evaluation, Kayrene Woods

Cybersecurity Undergraduate Research Showcase

This study provides a comprehensive evaluation of data security within the Apple ecosystem, focusing on the company’s privacy policies, user perceptions, and the effectiveness of its App Store review processes. Employing an interdisciplinary methodology, the research examines Apple’s commitment to data protection, emphasizing transparency and user trust. A survey of user experiences revealed varying levels of engagement and understanding of Apple’s privacy practices, with only 32.8% of respondents having read the Privacy Policy and mixed opinions on its clarity. Additionally, concerns persist about third-party app security, with 39.7% of users expressing apprehension and skepticism about Apple’s App Store review process. …

Intelligent Transportation System With 5g Vehicle-To-Everything (V2x): Architectures, Vehicular Use Cases, Emergency Vehicles, Current Challenges, And Future Directions, Vaishali Pawar, Nilima Zade, Deepali Vora, Vaishali Khairnar, Aurenice M. Oliveira, Ketan Kotecha, Ambarish Kulkarni

Michigan Tech Publications

In recent years, connected vehicle technologies emerged to provide a safer and more connected environment for transportation systems, which has further evolved into cellular vehicle-to-everything (C-V2X) technology. The current study contributes in the direction of future research of smart India @2047 in connected vehicles. The study presents the diverse aspects of 5G V2X as a comprehensive overview of Vehicle-to-Everything (V2X) technology that covers the significant scope of V2X technology, including its development, components, functionality, use cases, and future potential. It is observed that few surveys are available that cover limited aspects of 5G V2X communication technologies, with one or two …

Explainable Machine Learning Approach Enables Computer-Aided Identification System For Children Autism Spectrum Disorder (C-Asd), Karrar Hameed Abdulkareem, Zainab Hussein Arif, Mazin Abed Mohammed

Iraqi Journal for Computer Science and Mathematics

Neurodevelopmental disorders like autism spectrum disorder (ASD) cause significant cognitive, linguistic, object identification, communication, and social skills deficits. Although there is currently no cure for autism spectrum disorder (ASD), early detection can aid in diagnosis and implementing effective preventative measures. Artificial intelligence (AI) tools allow for an earlier diagnosis of ASD than was previously possible. Furthermore, many clinical and not clinical attributes can be used for identification of ASD but select the most proper ones still challenge. Therefore, in this study we propose a Computer-Aided Identification System based on machine learning concept and feature selection methods to diagnosis Children Autism …

Stable Heterogeneous Traffic Flow With Effective Localization And Path Planning In Wireless Network Connected And Automated Vehicles In~Internet Of Vehicular Things (Iovt), Ahmed N. Rashid, Ahmed Mahdi Jubair

Iraqi Journal for Computer Science and Mathematics

The increasing complexity of networks comprising both Connected Autonomous Vehicles (CAVs) and Human-Driven Vehicles (HDVs) presents substantial challenges in achieving accurate positioning, efficient communication, and optimal route planning. Current methodologies fall short in enhancing vehicular network efficiency and reliability due to noise interference, inefficient data transmission, and unstable data transfer. This study aims to improve localization accuracy, reduce communication noise, and enhance path planning efficiency in mixed CAV and HDV environments through the Stable Heterogeneous Traffic Flow using Deep Reinforcement Learning and Effective Path Planning (SHTDR-EPP) approach. The primary goals are to ensure dependable localization, efficient communication, and reliable route …

Modelling Security Factors Influencing E-Wallet Adoption In Malaysia, Adi Badiozaman Ruhani, Nur Suhaili Mansor, Hapini Awang, Mohamad Fadli Zolkipli, Khuzairi Mohd Zaini, Abderrahmane Benlahcene

Iraqi Journal for Computer Science and Mathematics

This study aims to develop an effective framework that addresses the security concerns and user behavior related to e-wallet adoption. The research methodology entails quantitative data collection through a literature review and surveys of e-wallet users using convenience sampling, and the proposed model is tested using the Partial Least Squares Structural Equation Modelling (PLS-SEM). The proposed security factors in this study include phone stolen protection, app security performance, secure authentication, data privacy protection, secure online transaction and banking info security. The online survey form was disseminated to Malaysian citizens, and 186 respondents participated in the survey. Using a two-step approach, …

Automated Fake News Detection System, Saja A. Al-Obaidi, Tuba Çağlıkantar

Iraqi Journal for Computer Science and Mathematics

Online news has been the majority of people’s information source in recent decades. However, a lot of the information that is accessible online is fake and sometimes even designed to mislead. It might be difficult for individuals to distinguish between certain false newspaper items and the real ones since they are so similar. Deep learning (DL) and machine learning (ML) models, among other automated false news detection (FND) techniques, are quickly becoming essential. A comparative study was conducted to analyze the performance of five prominent deep learning models across four distinct datasets, namely ISOT, FakeNewsNet, Dataset1, and Dataset2. Results indicated …

Posinormality Of Operators Treated By Weyl's Theorem On Unbounded Hilbert Space, Abbas G. Rajij, Dalia S. Ali, Huseyin Cakalli, Nadia M. G. Al-Saidi

Iraqi Journal for Computer Science and Mathematics

Hamiltonians, momentum operators, and other quantum-mechanical perceptible take the form of self-adjoint operators when understood in quantized physical schemes. Unbounded and self-adjoint recognition are required in the situation of positive measurements. The selection of the proper Hilbert space(s) and the selection of the self-adjoint extension must be made in order for this to operate. In this effort, we define a new extension positive measure depending on the measurable field of nonzero positive self-adjoint operator in unbounded Hilbert space of analytic functions of complex variables. Consequently, we define an extension norm in the same space. We show several new properties of …

Developing Linguistic Patterns To Mitigate Inherent Human Bias In Offensive Language Detection, Toygar Tanyel, Besher Alkurdi, Serkan Ayvaz

Turkish Journal of Electrical Engineering and Computer Sciences

With the proliferation of social media, there has been a sharp increase in offensive content, particularly targeting vulnerable groups, exacerbating social problems such as hatred, racism, and sexism. Detecting offensive language use is crucial to prevent offensive language from being widely shared on social media. However, the accurate detection of irony, implication, and various forms of hate speech on social media remains a challenge. Natural language-based deep learning models require extensive training with large, comprehensive, and labeled datasets. Unfortunately, manually creating such datasets is both costly and error-prone. Additionally, the presence of human-bias in offensive language datasets is a major …

A Surface-Based Approach For 3d Approximate Convex Decomposition, Onat Zeybek Kuşkonmaz, Yusuf Sahi̇lli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Approximate convex decomposition enables the simplification of complex shapes into manageable convex components. In this work, we propose a novel surface-based method to achieve this which leads to efficient computation times and sufficiently convex results while avoiding over-approximating the input model. We start approximation using mesh simplification. Then we iterate over the surface polygons of the mesh and divide them into convex groups. We utilize planar and angular equations to determine suitable neighboring polygons for inclusion in forming convex groups. To ensure our method outputs a sufficient result for a wide range of input shapes, we run multiple iterations of …

State Of The Art And Future Directions In Groundwater Contamination Risk Assessment, Xu Beiyi, Wang Ce, Zhou Guangyang, Zhou Pengpeng

Coal Geology & Exploration

Background Rapid global socio-economic development has intensified the resource crisis and contamination of groundwater, rendering groundwater contamination risk assessments critical to contamination prevention, control, and remediation. Advances Through a systematic summary of domestic and international studies, this study reviews the development of theories on groundwater contamination risk assessments and the formation of the theoretical system. Based on the source-pathway-receptor assessment system, this study presents a summary of the research methods for the assessments of contamination source load risks, groundwater vulnerability, and contamination hazards. Groundwater contamination risk assessments have evolved from unidimensional qualitative assessments to quantitative process models highlighting contamination mechanisms …

Acoustic Velocity Inversion Based On Convolutional Autoencoder Embedded With Fourier Neural Operator, Li Chen, Zhao Haixia, Bai Zhaowei, Hao Yufan

Coal Geology & Exploration

Background Seismic wave inversion serves as an effective method for obtaining the characteristics of structures, lithology, and physical properties of subsurface media using the arrival times, amplitude, and waveforms of seismic waves. Seismic inversion methods based on wave equations iteratively update model parameters using forward modeling. This generally involves extensive numerical simulations and optimization calculations, requiring large quantities of computational resources and time. In recent years, neural operators for deep learning, represented by the Fourier neural operator (FNO), have gained widespread attention. However, the original FNO structure fails to effectively learn the wavefield information with sharp changes in geological structures …

Sdf-1Α Mediates Primary Tumor Escape In Glioblastoma Through Activation Of Mesenchymal Transitions, Charles T. Froman-Glover

The Cardinal Edge

Glioblastoma (GBM), a highly aggressive primary brain tumor originating in glial cells, poses a significant challenge due to its rapid growth and invasive nature within healthy brain tissue.

Current treatments involve surgical resection, chemotherapy, and radiation. These treatments alone are not enough to cure this disease, and a better understanding of the mechanics of the tumor's micro-environment is imperative to furthering the field of cancer research. This research focuses on understanding the tumor microenvironment's impact, specifically investigating the role of stromal cell-derived factor 1 (SDF-1) mechanics on GBM aggressiveness. SDF-1 is known to facilitate disease progression by facilitating chemotaxis toward …

Implementing The Safe System Approach At Intersections In Utah, Ian Patrick Macgregor

Theses and Dissertations

This thesis investigates the principles and elements of the Safe System Approach, a new paradigm in roadway safety. A compendium of practice was created to determine recommendations on how to implement the Safe System Approach at intersections and observe how other jurisdictions are implementing it. Several strategies identified include the Safe Systems at Intersections (SSI) methodology, Safe System Alignment Frameworks, Vision Zero communities, incorporating the Safe System Approach into the Strategic Highway Safety Plan (SHSP) or Highway Safety Improvement Program (HSIP), mandating the Safe System Approach be considered in all projects, and the Organizational Safety Culture Self-Assessment. These policies do …

Computational Study Of The Evolution Of The Grain Boundary Network During Anisotropic Grain Growth, Jose Nino

Theses and Dissertations

The grain boundary network (GBN) of polycrystalline materials changes during grain growth, affecting the material's properties. This research presents the results of fully anisotropic grain growth simulations. We perform simulations using three GB energy functions: an energy function that considers a GB's 5 degrees of freedom, the Read-Shockley model, and isotropic. We analyze the impact of these energy functions on the morphological evolution and various microstructural statistics, such as crystallographic texture and triple junction distribution. The results demonstrate that while individual grain evolution varies with GB energy function, certain microstructural statistics reach similar steady states across different models. In addition, …

Phagolysosomes Break Down The Membrane Of A Non-Apoptotic Corpse Independent Of Macroautophagy, Shruti Kolli, Cassidy J. Kline, Kimya M. Rad, Ann M. Wehman

Biological Sciences: Faculty Scholarship

Cell corpses must be cleared in an efficient manner to maintain tissue homeostasis and regulate immune responses. Ubiquitin-like Atg8/LC3 family proteins promote the degradation of membranes and internal cargo during both macroautophagy and corpse clearance, raising the question how macroautophagy contributes to corpse clearance. Studying the clearance of non-apoptotic dying polar bodies in Caenorhabditis elegans embryos, we show that the LC3 ortholog LGG-2 is enriched inside the polar body phagolysosome independent of autophagosome formation. We demonstrate that ATG-16.1 and ATG-16.2, which promote membrane association of lipidated Atg8/LC3 proteins, redundantly promote polar body membrane breakdown in phagolysosomes independent of their role …

Analysis Of Status, Challenges, And Optimization Recommendations For China’S Commercial Space Policy Support System, Liming Ge, Zixuan Liu, Mingda Yang, Wenbin Ma

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a strategic pillar in building a space power, commercial space has become a new frontier for global technological competition. The Chinese government and relevant regulatory authorities have introduced a series of multi-level policy documents, propelling the commercial space sector into a phase of vigorous development. This study systematically reviews the background, evolution, and implementation outcomes of China’s policy support system for commercial space. It is indicates that, in light of the goal of becoming a “space power” and the future industrial competition, China’s policy support system for commercial space still faces challenges such as ineffective policy implementation mechanisms, lack …

Compliant Structures Facilitate Less Invasive And Biomechanically Improved Lumbar Spinal Implants, Daniel J. Orr

Theses and Dissertations

Implants used in lumbar spinal fusion and lumbar total disc replacement procedures have improved substantially over the years, however, the opportunity remains to improve either the adjustability, durability, motion, or minimally invasive characteristics which could aid in achieving optimal surgical outcomes. It is hypothesized that the inherent advantages of compliant mechanisms specifically Deployable Euler Spiral Connectors (DESCs) and a new mechanism known as the interior contact aided rolling element (I-CORE) are well suited for each of these applications and will be explored and utilized as the basis of these proposed designs. By addressing these challenges, the research endeavors to improve …

Understanding Contributing Factors To Injury Severity And Improper Driver Actions In Work Zone Crashes And Evaluating Smart Work Zone Applications For Safety Improvement, Rakesh Rangaswamy

USF Tampa Graduate Theses and Dissertations

A work zone can be described as a roadway designated for construction, maintenance, or other activities that temporarily disrupt the normal traffic flow. Due to this disrupts in traffic conditions, work zones may bring sudden shifts in driving experience, depending on the sort of work zone present, creating unpredictable maneuvers, and putting both motorists and workers at risk. To understand these issues, this study uses work zone accident data obtained from Florida and uses several methodological techniques, including the mixed logit model with variance and mean heterogeneity, temporal instability test, log-likelihood test, out-of-sample analysis, and ANOVA test.

Firstly, this study …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

Sound Innovations For Biofabrication And Tissue Engineering, Mengxi Wu, Zhiteng Ma, Zhenhua Tian, Joseph Rich, Xin He, Jianping Xia, Ye He, Kaichun Yang, Shujie Yang, Kam W. Leong, Luke P. Lee, Tony Jun Huang

Faculty Publications

Advanced biofabrication techniques can create tissue-like constructs that can be applied for reconstructive surgery or as in vitro three-dimensional (3D) models for disease modeling and drug screening. While various biofabrication techniques have recently been widely reviewed in the literature, acoustics-based technologies still need to be explored. The rapidly increasing number of publications in the past two decades exploring the application of acoustic technologies highlights the tremendous potential of these technologies. In this review, we contend that acoustics-based methods can address many limitations inherent in other biofabrication techniques due to their unique advantages: noncontact manipulation, biocompatibility, deep tissue penetrability, versatility, precision …