Engineering Commons^™

Design And Fabrication Of A Force-Displacement Control Mechanism For Bone-Surgical Tool Testing, Kenneth Nwagu

College of Graduate Studies: Theses & Dissertations

This project focuses on the design and fabrication of an experimental setup for orthopedic-tool testing, tailored for a surgical instrumentation company. The multifaceted project encompasses a literature review, conceptual design, prototyping, and rigorous testing, resulting in a versatile control system capable of assessing various orthopedic tools, including bone drills, saws, burrs, and power handpieces.

Orthopedic surgical procedures (which include cutting and/or drilling into bone) often need to be performed on bones for faster recovery. The drilling and cutting process can cause an increase in temperature at the cutting site which can cause bone necrosis. The tools also need to be …

Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer

Honors Theses and Capstones

Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) …

Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio

Articles

Deep Learning models based on convolutional neural networks are known to be uncalibrated, that is, they are either overconfident or underconfident in their predictions. Safety-critical applications of neural networks, however, require models to be well-calibrated, and there are various methods in the literature to increase model performance and calibration. Subnetwork ensembling is based on the over-parametrization of modern neural networks by fitting several subnetworks into a single network to take advantage of ensembling them without additional computational costs. Data augmentation methods have also been shown to enhance model performance in terms of accuracy and calibration. However, ensembling and data augmentation …

Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …

Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

Articles

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …

Detection And Localization Of Data Forgery Attacks In Automatic Generation Control, Fengli Zhang, Yatish R. Dubasi, Wei Bao, Qinghua Li

Electrical Engineering Faculty Publications and Presentations

Automatic Generation Control (AGC) is a key control system to maintain the power system’s balance between load and supply by maintaining its frequency in a specific range. It collects the tie-line power flow and frequency measurements of each control area to calculate the Area Control Error (ACE) and then adjusts power generation based on the calculated ACE. However, malicious frequency or tie-line power flow measurements can be injected and then AGC is misled to make false power generation adjustments which will harm power system operations. Such attacks can be carefully designed to pass the power system’s existing bad data detection …

Effects Of Electrodes Layout On Performance Of Millimeter-Wave Transistors, Soheil Nouri, Samir M. El-Ghazaly

Electrical Engineering Faculty Publications and Presentations

This work presents a systematic parameter extraction methodology for modeling of millimeter-wave transistors. The physics-based parameter extraction approach in this study is included in the wave-electron-transport model to improve the accuracy of the simulation results. The effects of extrinsic parameters on the performance of the device are also analyzed in detail. Skin effects and sharp metallization edge effects as the two physical phenomena that impact the current distribution and the resistance of millimeter-wave transistors are studied thoroughly. Two common electrode layout variations, the T configuration and the fork configuration, are compared. The comparison mainly targeted their performance on upper millimeter …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya

Dissertations, Master's Theses and Master's Reports

Increased Printed Circuit Board (PCB) route complexity and density combined with the growing demand for low-scale rapid prototyping has increased the desire for Automated Optical Inspection (AOI) that reduces prototyping time and production costs by detecting defects early in the production process. Traditional defect detection method of human visual inspection is not only error prone but is also time-consuming given the growing complex and dense circuitry of modern-day electronics. Electric contact-based testing, either in the form of a bed of nails testing fixture or a flying probe system, is costly for low-rate rapid prototyping. An AOI is a non-contact test …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Study Of Eco-Driving And Charging Planning In Connected And Automated Vehicles Environment, Pradeep Bhat

Dissertations, Master's Theses and Master's Reports

In this dissertation, the development of eco-driving and charging planning algorithms in the connected and automated vehicle environment (CAV) are presented. CAV technologies provide opportunities for potential energy savings and efficiency improvement of transportation networks, which are explored through multiple research tasks in this study.

The objective of the first study presented in Chapter 2 is to reduce vehicle dynamic losses and required tractive force while completing trip distance within a given travel time. Sequential Quadratic Programming method is employed for this nonlinearly constrained optimization problem. The validation result illustrates the benefits of optimal velocity trajectories. The objective of the …

Dynamic Modeling Of Commercial-Off-The-Shelf Smart Inverters Using Power-Hardware-In-The-Loop, Bidur Poudel

Electronic Theses and Dissertations

Inverter-based generation is replacing synchronous-based generation in the power grid. In the past, due to the dominance of synchronous-based generation, inverter-based generation dynamics were typically under-modeled as they made little contribution to voltage and frequency control. Looking at the present context, several disturbances, like the Blue Cut Fire (CA), on August 16, 2016, the South Australian Blackout on September 28, 2016, and the Canyon Two Fire Disturbance (CA) on October 9, 2017, etc., are caused by the influence of converter-based resources. So, for converter-dominated power system stability analysis and control, the dynamics of an inverter-based system cannot be under-modeled. In …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

Underwater Communication Acoustic Transducers: A Technology Review, Laila Shams, Tian-Bing Xu, Zhongqing Su (Ed.), Branko Glisic (Ed.), Maria Pina Limongelli (Ed.)

Mechanical & Aerospace Engineering Faculty Publications

This paper provides a comprehensive review on transducer technologies for underwater communications. The popularly used communication transducers, such as piezoelectric acoustic transducers, electromagnetic acoustic transducers, and acousto-optic devices are reviewed in detail. The reasons that common air communication technologies are invalid die to the differences between the media of air and water are addresses. Because of the abilities to overcome challenges the complexity of marine environments, piezoelectric acoustic transducers are playing the major underwater communication roles for science, surveillance, and Naval missions. The configuration and material properties of piezoelectric transducers effects on signal output power, beamwidth, amplitude, and other properties …

Perceptual Anthropomorphic Walking Robot Platform For Navigation In Unstructured And Undifferentiated Environments, Luige Vladareanu, Mihai Rădulescu, Marius Pandelea, Hongbo Wang, Florentin Smarandache, Yongfei Feng, Ionel-Alexandru Gal, Alexandra C. Ciocîrlan

Branch Mathematics and Statistics Faculty and Staff Publications

This scientific presentation studies the VIPRO Platform for control of Anthropomorphic Walking Robots (AWR), the architecture control system of the SiMeLA MP robot motion, and shows several experimental results.

High Energy Blue Light Induces Oxidative Stress And Retinal Cell Apoptosis, Jessica Malinsky

Capstone Showcase

Blue light (BL) is a high energy, short wavelength spanning 400 to 500 nm. Found in technological and environmental forms, BL has been shown to induce photochemical damage of the retina by reactive oxygen species (ROS) production. Excess ROS leads to oxidative stress, which disrupts retinal mitochondrial structure and function. As mitochondria amply occupy photoreceptors, they also contribute to oxidative stress due to their selectively significant absorption of BL at 400 to 500 nm. ROS generation that induces oxidative stress subsequently promotes retinal mitochondrial apoptosis. BL filtering and preventative mechanisms have been suggested to improve or repair BL-induced retinal damage, …

Pneumatic Latched Demultiplexer Circuit For Controlling Multi-Actuator Soft Robots, Arsh Noor Amin

Master’s Theses

This thesis presents a novel method for controlling multi-actuator soft robots using pneumatic latched demultiplexer circuits implemented with monolithic membrane valves. The pneumatic circuits are designed to address the problems of heavy dependence on hard electrical components and lack of feasible multi-actuator soft robotic systems that limit the potential applications of soft robotics. The proposed pneumatic demultiplexers reduce the number of solenoid valves and electrical components required to drive soft robotic systems, making soft robot control mechanisms more compliant, scalable, and versatile. The thesis demonstrates the design, fabrication, and testing of 4-bit and n-bit pneumatic demultiplexer circuits that can control …

Exploration Of Robotics Need In The Medical Field And Robotic Arm Operation Via Glove Control, Aditi Vijayvergia

Master’s Theses

This thesis project is an exercise in getting hands-on experience in redesigning and modifying a robotic system. It also involves understanding the current need for robotic applications in hospital settings. To achieve the above, a thorough literature review of the current state of robotics in a hospital setting was conducted. Moreover, a number of interviews with medical care professionals were completed. Three main themes were obtained from the literature review and five main themes were obtained from the interviews which will be presented in this thesis report. The next phase of the project involved redesigning a system that is composed …

Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando

Browse all Theses and Dissertations

Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …

Furniture Mover, Zachariah Burkhardt, Gary Mucciarone, Gino Mucciarone, Juan Soto, David Kotyk

Williams Honors College, Honors Research Projects

The movement of furniture is an often overlooked pain point for physically-challenged individuals, especially when rearranging furniture in a room. These individuals may try to minimize the risk of tip-over or strain-related injuries by seeking assistance from others. Still, some individuals are limited in finding volunteers forthcoming and capable of helping. This can lead to a dilemma of either being able to find individuals willing to assist in the process or risking one’s own personal safety when moving furniture. The proposed design project implements the use of multiple, independent platforms with mecanum wheels placed underneath each corner of a piece …

Botsitter, Maria Hatzis, Gregory Blondheim Jr., Marian Bonto, Brett Jacobsen

Williams Honors College, Honors Research Projects

As society progresses into an era where both parents work, whether it is online or in person, children in the home may be put in dangerous situations if they are not given the attention they need. The BotSitter is an automated system that follows the child around and makes an audio alarm to alert both the child and the nearby guardian. Using RSSI trilateration, predetermined danger areas, and embedded controls, the BotSitter will be able to follow the child. The device can manage to keep track of the child for the guardian while being almost completely automated outside of setup.

Motion Sensors And Instrumentation Based On Electrochemical Redox Reaction, Xiaoce Feng

Wayne State University Dissertations

To detect human body vital physiological signals, an electrochemical wearable sensor and a single-mode artificial mechanoreceptor have been developed and their capabilities to detect cardiorespiratory signals, as well as to detect rapid adaptive and slow adaptive responses have been preliminarily demonstrated. The electrochemical method based on I-/I3- redox couple proves to be a sensitive transduction mechanism. Furthermore, a common gate transimpedance amplifier based on gallium nitride high electron mobility transistor for the mechano-acoustic sensor and the wearable mechanoreceptor was developed. The transistor’s performance at high temperatures has been investigated, and its failure mode at high temperature has been discussed.

Gas Sensor Development For Environmental And Soil Monitoring, Xiaoyu Chen

Wayne State University Dissertations

This dissertation introduces the development of 3 type of gas sensors for different applications.Chapter 2 reports a simple but effective methane sensor based on off-the-shelf quartz tuning forks (QTFs). It has been experimentally demonstrated that the presence of methane increases the resonant frequency of a single QTF with a sensitivity of 0.0063 Hz/1% or 0.19 ppm/1% and a detection limit of 0.025% at 0.5 Hz sampling rate. For the differential device with 2 QTFs, the values reach to 0.0050 Hz/1% and <0.0386% at 0.25 Hz sampling rate. An excellent selectivity to carbon dioxide, which causes a decrease of the resonant frequency, has been illustrated. Temperature, pressure and humidity responses have been characterized. This new methane sensor is expected to meet the requirements of cost, power, size, reliability and explosion permissibility for coal mine safety applications. Chapter 3 illustrates an in-situ soil probe prototype development for Arctic area underground greenhouse monitoring utilizing commercially available CO2 sensors. Several single and double measurement site prototypes indoor and outdoor test results show the reliability and robustness. These prototypes are ready for real field test to provide long-term Arctic soil information in harsh environments. Chapter 4 uses a simple, surfactant-free solvothermal method to synthesize spherical Pt−Ni NPs which was coated onto a planar electrochemical sensor device as the electrode material. With BmpyNTf2 as the electrolyte, O2 and H2 sensing reaction were investigated. The sensor exhibited a high sensitivity to O2 ((3.04 ± 0.18) × 10−5 mA cm−2 ppm−1) compared to commercial Pt/C-based sensor ((2.57 ± 0.22) × 10−5 mA cm−2 ppm−1), and H2 sensitivity for (0.331 ± 0.014) × 10−4 mA cm−2 ppm−1. Other feature such as rapid gas response, high selectivity and superior reproducibility were also demonstrated.

High-Power, High-Efficiency, High-Power-Density, Non-Isolated Dc-Dc Converter For Fuel Cell Vehicles, Nima Abdolmaleki

Wayne State University Dissertations

This work proposes various solutions for performance, efficiency, and power density improvements of high-power interleaved boost converters (IBCs) in electrified powertrains, namely, use of SiC, LCIs, improved controller, and soft-switching. A relationship was developed for the output current calculation of an n-phase interleaved boost converter (IBC) and output DC link capacitance sizing. The semiconductor losses and efficiency in an n-phase SiC-based IBC were calculated and analyzed. The trade-off in design of an n-phase SIBC with regards to passive components requirements and sizing, passive components volume, losses, and efficiency were analytically investigated from different aspects. An n-phase SIBC was simulated at …

Efficient Design And Implementation Of Miniaturized Microstrip Diplexer Using Dual Open Stub Loaded Resonator For 5g Applications, Islam F. Abu Elkhair, Hamdi A. Elmikati, Mohamed M. Ashour, Amr H. Hussein

Mansoura Engineering Journal

The design and implementation of a compact size diplexer with high isolation, low insertion loss, and small fractional bandwidths is a promising issue in recent wireless communication systems. In this paper, a novel microstrip diplexer has been introduced based on the utilization of the dual open stub loaded resonator technique. The proposed design has a very compact size of with a high operating power efficiency. The diplexer is designed to operate at two resonance frequencies of and with very low insertion losses of and , respectively. Moreover, it provides high isolation values of and for and , respectively. The diplexer …

An Optimized Deep Learning-Based Framework For Predicting Diabetes Mellitus Using Ffnn, Norhan S. Elmongy, Sally M. Elghamrawy, Amr M. T. Ali-Eldin, Ali I. Eldesouky

Mansoura Engineering Journal

Diabetes mellitus (DM) is a major public health problem in Egypt, and the illness is regarded as a contemporary epidemic across the world. Diabetes is becoming more common, which is a cause for serious concern. As a result, precise and timely identification of the illness is critical. Health and research institutions have also recently expressed a serious interest in developing and implementing cutting-edge healthcare systems. Therefore, it is necessary to accurately and quickly identify the condition. To solve this issue, scientific research has been carried out, but the outcomes have fallen short. Four layers make up the proposed Diabetes mellitus …

Microstrip Antenna Design Using Cst Optimized By Neural Network Algorithm, Hadeer. A Shoeab, Mohamed A.Mohamed, Marzouk El Said A, Ahmed. A. Kabeel

Mansoura Engineering Journal

In this paper, a general design procedure is suggested for the microstrip antennas using artificial neural networks and this is demonstrated using the rectangular patch geometry. The model was analyzed for 1733 data sets of input output parameters. 1300 samples for training and 433 samples for testing and 1500 epoch, learning rate from (0.003 to 0.005). Python was used to create and implement the ANN algorithm model. The mean error in detection of resonance frequencies (return loss peaks) was 0.144GHz on train set, and 0.116GHz on test set. The outputs of the radial basis function are optimized by varying the …

Community And Key Player Detection For Disrupting Illicit Drug Supply Networks In Social Media Platforms – Especially On Instagram, Akassi Rachel Niamke Aman

Graduate Theses, Dissertations, and Problem Reports (ETD)

This thesis focuses on the pressing issue of illicit drug trafficking and its impact on public health and safety at a global level. With the advent of digital technologies and social media platforms, combating drug trafficking has become increasingly challenging for law enforcement and researchers alike. Among these platforms, Instagram, a popular photo and video-sharing social networking platform, has emerged as a prominent hub for drug trafficking activities.

In this study, we delve into the effectiveness of community and key player detection algorithms in identifying and disrupting illicit drug supply networks on Instagram. To conduct our research, we collected real …

Method Of Validating Satellite Surface Reflectance Product Using Empirical Line Method, Meghraj Kc

Electronic Theses and Dissertations

Atmospherically corrected surface reflectance (SR) products are used for reliable monitoring of land surfaces and are the standard products of Landsat sensors. Due to increased demand for SR products, a need exists to verify that the L2C2 (Level-2 Collection-2) SR products are precise and accurate. The Level-2 Collection 2 (L2C2) SR Product is processed satellite imagery data that corrects for atmospheric effects such as absorption and scattering, providing a more accurate representation of Earth's surface. The validation of SR products using ground truth measurement is essential. This study aims to develop and evaluate a validation methodology for satellite SR products. …

Validation Of Expanded Trend-To-Trend Cross-Calibration Technique And Its Application To Global Scale, Ramita Shah

Electronic Theses and Dissertations

The expanded Trend-to-Trend (T2T) cross-calibration technique has the potential to calibrate two sensors in much less time and provides trends on daily assessment basis. The trend obtained from the expanded technique aids in evaluating the differences between satellite sensors. Therefore, this technique was validated with several trusted cross-calibration techniques to evaluate its accuracy. Initially, the expanded T2T technique was validated with three independent RadcaTS RRV, DIMITRI-PICS, and APICS models, and results show a 1% average difference with other models over all bands. Further, this technique was validated with other SDSU techniques to calibrate the newly launched satellite Landsat 9 with …