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Articles 1 - 30 of 346
Full-Text Articles in Engineering
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Dissertations, Master's Theses and Master's Reports
Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …
Monitoring Time Domain Characteristics Of Parkinson's Disease Using 3d Memristive Neuromorphic System, Md Abu Bakr Siddique, Yan Zhang, Hongyu An
Monitoring Time Domain Characteristics Of Parkinson's Disease Using 3d Memristive Neuromorphic System, Md Abu Bakr Siddique, Yan Zhang, Hongyu An
Michigan Tech Publications, Part 2
INTRODUCTION: Parkinson's disease (PD) is a neurodegenerative disorder affecting millions of patients. Closed-Loop Deep Brain Stimulation (CL-DBS) is a therapy that can alleviate the symptoms of PD. The CL-DBS system consists of an electrode sending electrical stimulation signals to a specific region of the brain and a battery-powered stimulator implanted in the chest. The electrical stimuli in CL-DBS systems need to be adjusted in real-time in accordance with the state of PD symptoms. Therefore, fast and precise monitoring of PD symptoms is a critical function for CL-DBS systems. However, the current CL-DBS techniques suffer from high computational demands for real-time …
Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce
Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce
Michigan Tech Publications, Part 2
As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used …
Modular Open-Source Design Of Pyrolysis Reactor Monitoring And Control Electronics, Finn K. Hafting, Daniel G. Kulas, Etienne Michels, Sarvada Chipkar, Stefan Wisniewski, David Shonnard, Joshua M. Pearce
Modular Open-Source Design Of Pyrolysis Reactor Monitoring And Control Electronics, Finn K. Hafting, Daniel G. Kulas, Etienne Michels, Sarvada Chipkar, Stefan Wisniewski, David Shonnard, Joshua M. Pearce
Michigan Tech Publications, Part 2
Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis …
Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce
Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce
Michigan Tech Publications, Part 2
As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used …
Nr Sidelink Performance Evaluation For Enhanced 5g-V2x Services, Mehnaz Tabassum, Felipe Henrique Bastos, Aurenice M. Oliveira, Aldebaro Klautau
Nr Sidelink Performance Evaluation For Enhanced 5g-V2x Services, Mehnaz Tabassum, Felipe Henrique Bastos, Aurenice M. Oliveira, Aldebaro Klautau
Michigan Tech Publications, Part 2
The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous …
Synthetic Aperture Scatter Imaging, Qian Huang, Zhipeng Dong, Gregory Nero, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
Synthetic Aperture Scatter Imaging, Qian Huang, Zhipeng Dong, Gregory Nero, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
Michigan Tech Publications, Part 2
Diffraction limits the minimum resolvable feature on remotely observed targets to $\lambda R_{c}/A_{c}$, where $\lambda$ is the operating wavelength, $R_{c}$ is the range to the target and $A_{c}$ is the diameter of the observing aperture. Resolution is often further reduced by scatter or turbulence. Here we show that analysis of scattered coherent illumination can be used to achieve resolution proportional to $\lambda R_{s}/A_{s}$, where $R_{s}$ is the range between the scatterer and the target and $A_{s}$ is the diameter of the observed scatter. Theoretical analysis suggests that this approach can yield resolution up to 1000× better than the diffraction limit. …
Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa
Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa
Michigan Tech Publications, Part 2
This paper proposes an algorithm for the optimal installation of inverter-based resources (IBR) composed of wind energy conversion systems, photovoltaic systems, and battery energy storage systems in distribution systems using genetic algorithm (GA) and the cuckoo search (CS) as optimization techniques. The OpenDSS software is used to calculate the power flow in the distribution system with different penetration levels of IBRs. It is used a standard load shape of the IEEE 123 bus system programmed in OpenDSS and irradiance, temperature, and wind speed curves from Brazil. The proposed algorithm, using a genetic algorithm and cuckoo search, was able to define …
Open Source Framework For A Broadly Expandable And Reconfigurable Data Acquisition And Automation Device (Bread), Shane Oberloier, Nicholas G. Whisman, Finn Hafting, Joshua M. Pearce
Open Source Framework For A Broadly Expandable And Reconfigurable Data Acquisition And Automation Device (Bread), Shane Oberloier, Nicholas G. Whisman, Finn Hafting, Joshua M. Pearce
Michigan Tech Publications, Part 2
Though open source data acquisition (DAQ) systems have been published, closed source proprietary systems are the standard despite often being prohibitively expensive. High costs, however, limit access to high-quality DAQ in low-resource settings. In many cases the functions executed by the closed source and proprietary DAQ cards could be carried out by an open source alternative; however, as desired function count increases, the simplicity of integrating the designs decreases substantially. Although the global library of open source electronic designs is expanding rapidly, and there is clear evidence they can reduce costs for scientists one device at a time, they are …
Hypergraph-Based Multi-Robot Task And Motion Planning, James Motes, Tan Chen, Timothy Bretl, Marco Morales Aguirre, Nancy M. Amato
Hypergraph-Based Multi-Robot Task And Motion Planning, James Motes, Tan Chen, Timothy Bretl, Marco Morales Aguirre, Nancy M. Amato
Michigan Tech Publications, Part 2
In this article, we present a multi-robot task and motion planning method that, when applied to the rearrangement of objects by manipulators, results in solution times up to three orders of magnitude faster than the existing methods and successfully plans for problems with up to 20 objects, more than three times as many objects as comparable methods. We achieve this improvement by decomposing the planning space to consider manipulators alone, objects, and manipulators holding objects. We represent this decomposition with a hypergraph where vertices are decomposed elements of the planning spaces and hyperarcs are transitions between elements. The existing methods …
Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette
Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette
Michigan Tech Publications, Part 2
Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …
Real-Time Suitable Predictive Control Using Spat Information From Automated Traffic Lights, Pradeep Bhat, Bo Chen
Real-Time Suitable Predictive Control Using Spat Information From Automated Traffic Lights, Pradeep Bhat, Bo Chen
Michigan Tech Publications, Part 2
Traffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. Intelligent transportation systems deployed in traffic infrastructure can communicate Signal and Phase Timing messages (SPaT) to vehicles approaching intersections. In the connected and automated vehicle ecosystem, the fuel savings potential has been explored. Prior studies have predominantly focused on fixed time control for the driver. However, in the case of actuated signals, there is a different and significant challenge due to …
Optimal Configuration Of Extreme Fast Charging Stations Integrated With Energy Storage System And Photovoltaic Panels In Distribution Networks, Zhouquan Wu, Pradeep Bhat, Bo Chen
Optimal Configuration Of Extreme Fast Charging Stations Integrated With Energy Storage System And Photovoltaic Panels In Distribution Networks, Zhouquan Wu, Pradeep Bhat, Bo Chen
Michigan Tech Publications
Extreme fast charging (XFC) for electric vehicles (EVs) has emerged recently because of the short charging period. However, the extreme high charging power of EVs at XFC stations may severely impact distribution networks. This paper addresses the estimation of the charging power demand of XFC stations and the design of multiple XFC stations with renewable energy resources in current distribution networks. First, a Monte Carlo (MC) simulation tool was created utilizing the EV arrival time and state-of-charge (SOC) distributions obtained from the dataset of vehicle travel surveys. Various impact factors are considered to obtain a realistic estimation of the charging …
A Simple Micromilled Microfluidic Impedance Cytometer With Vertical Parallel Electrodes For Cell Viability Analysis, Jason Eades, Julianne F. Audiffred, Micah Fincher, Jin Woo Choi, Steven A. Soper, William Todd Monroe
A Simple Micromilled Microfluidic Impedance Cytometer With Vertical Parallel Electrodes For Cell Viability Analysis, Jason Eades, Julianne F. Audiffred, Micah Fincher, Jin Woo Choi, Steven A. Soper, William Todd Monroe
Michigan Tech Publications
Microfluidic impedance cytometry has been demonstrated as an effective platform for single cell analysis, taking advantage of microfabricated features and dielectric cell sensing methods. In this study, we present a simple microfluidic device to improve the sensitivity, accuracy, and throughput of single suspension cell viability analysis using vertical sidewall electrodes fabricated by a widely accessible negative manufacturing method. A microchannel milled through a 75 µm platinum wire, which was embedded into poly-methyl-methacrylate (PMMA), created a pair of parallel vertical sidewall platinum electrodes. Jurkat cells were interrogated in a custom low-conductivity buffer (1.2 ± 0.04 mS/cm) to reduce current leakage and …
Noise2clean: Cross-Device Side-Channel Traces Denoising With Unsupervised Deep Learning, Honggang Yu, Mei Wang, Xiyu Song, Haoqi Shan, Hongbing Qiu, Junyi Wang, Kaichen Yang
Noise2clean: Cross-Device Side-Channel Traces Denoising With Unsupervised Deep Learning, Honggang Yu, Mei Wang, Xiyu Song, Haoqi Shan, Hongbing Qiu, Junyi Wang, Kaichen Yang
Michigan Tech Publications
Deep learning (DL)-based side-channel analysis (SCA) has posed a severe challenge to the security and privacy of embedded devices. During its execution, an attacker exploits physical SCA leakages collected from profiling devices to create a DL model for recovering secret information from victim devices. Despite this success, recent works have demonstrated that certain countermeasures, such as random delay interrupts or clock jitters, would make these attacks more complex and less practical in real-world scenarios. To address this challenge, we present a novel denoising scheme that exploits the U-Net model to pre-process SCA traces for “noises” (i.e., countermeasures) removal. Specifically, we …
Wavelet-Based Harmonic Magnitude Measurement In The Presence Of Interharmonics, Flavio Costa, Stefan Häselbarth, Sergey Yanchenko, Kai Strunz, Aurenice M. Oliveira
Wavelet-Based Harmonic Magnitude Measurement In The Presence Of Interharmonics, Flavio Costa, Stefan Häselbarth, Sergey Yanchenko, Kai Strunz, Aurenice M. Oliveira
Michigan Tech Publications
The increasing proliferation of power electronic converters, nonlinear loads, and distributed generation are leading to increased levels of harmonic and interharmonics in power networks. As a consequence, power quality (PQ) has become a critical performance indicator for power utilities and end-users. This study proposes a novel harmonic estimation method based on the real-time stationary discrete wavelet packet transform (RT-SDWPT). The proposed technique decomposes an input signal into frequency bands with harmonic information at cutoff frequencies and uses a compensation strategy to estimate root mean square (RMS) values of harmonics at every sampling period. The performance and effectiveness of the proposed …
Neuromorphic Computing Applications In Robotics, Noah Zins
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, …
Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries
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
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 …
Development And Verification Of Automated Fixtures For Functional Testing Of Space Grade Printed Circuit Board Assemblies, Nicholas A. Wylie
Development And Verification Of Automated Fixtures For Functional Testing Of Space Grade Printed Circuit Board Assemblies, Nicholas A. Wylie
Dissertations, Master's Theses and Master's Reports
Orbion Space Technology is a developer and manufacturer of electric propulsion systems for military and commercial spacecraft. Orbion’s products include a Power Processing Unit (PPU) which is utilized for power and control of the satellite propulsion system. These PPUs are complex electro-mechanical assemblies that include multiple Printed Circuit Board Assemblies (PCBA) and are built to IPC standards. To ensure smooth fabrication and to reduce the risk of complications from in-process rework of PCBAs, comprehensive electrical functional testing at the board-level is required before higher- level assembly. Electrical functional testing provides verification of quality, workmanship, and manufacturing defects of the PCBAs. …
Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance, Madelyn G. Veurink
Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance, Madelyn G. Veurink
Dissertations, Master's Theses and Master's Reports
Many governments around the world are pledging to reduce their consumption of fossil fuels as they look to curb the amount of green house gasses they release into the atmosphere. These green house gasses are what scientists blame for global warming and the recent increase in extreme weather events. Producing electricity is one of the largest producers of these gasses but utilizing renewable sources can greatly decrease the amount of green house gasses produced. Common forms of renewable energies are wind and solar and both of these green energies have reached a state of maturation where they are economically viable …
Towards Scalable Spectral Clustering Via Spectrum-Preserving Sparsification, Yongyu Wang, Zhuo Feng
Towards Scalable Spectral Clustering Via Spectrum-Preserving Sparsification, Yongyu Wang, Zhuo Feng
Michigan Tech Publications
Eigenvalue decomposition of Laplacian matrices for large nearest-neighbor (NN)graphs is the major computational bottleneck in spectral clustering (SC). To fundamentally address this computational challenge in SC, we propose a scalable spectral sparsification framework that enables to construct nearly-linear-sized ultra-sparse NN graphs with guaranteed preservation of key eigenvalues and eigenvectors of the original Laplacian. The proposed method is based on the latest theoretical results in spectral graph theory and thus can be applied to robustly handle general undirected graphs. By leveraging a nearly-linear time spectral graph topology sparsification phase and a subgraph scaling phase via stochastic gradient descent (SGD) iterations, our …
A Smart Parallel Gripper Industrial Automation System For Measurement Of Gripped Work Piece Thickness, Erik Kocher, Chukwuemeka George Ochieze, Ahmat Oumar, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
A Smart Parallel Gripper Industrial Automation System For Measurement Of Gripped Work Piece Thickness, Erik Kocher, Chukwuemeka George Ochieze, Ahmat Oumar, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
Michigan Tech Publications
As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of the smart parallel gripper system to measure the width of components grasped with the gripper. In addition, details of the system’s components, operation, more advanced uses are discussed. On the automation line, this smart gripper can be used to measure the thickness of work pieces while handling them and classifying these as either acceptable, too large …
Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding
Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding
Michigan Tech Publications
In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the …
Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
Michigan Tech Publications
As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project was performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and application of a force-programmable and sensing pneumatic parallel gripper system. Force sensing is a critical part of many systems in modern automation systems. Applications such as prosthetics, robotic surgery, or basic manufacturing systems may rely on the ability to properly read and control forces applied to an object. This work evaluates the basic operation of the pneumatic force-sensing gripper …
An Industrial Pneumatic And Servo Four-Axis Robotic Gripper System: Description And Unitronics Ladder Logic Programming, Zongguang Liu, Chrispin Johnston, Aleksi Leino, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
An Industrial Pneumatic And Servo Four-Axis Robotic Gripper System: Description And Unitronics Ladder Logic Programming, Zongguang Liu, Chrispin Johnston, Aleksi Leino, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh
Michigan Tech Publications
As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of a four-axis robot enclosed in a cage with one side guarded by an optical fence. The robot has pneumatically actuated X-Y linear motion and a pneumatic gripper. Furthermore, the Z-axis motion and gripper wrist rotation are controlled by servo motors. A human machine interface (HMI) is also present, and it allows for easy manipulation and programming …
Mechatronics Bachelor Curriculum Development In Light Of Industry 4.0 Technology Needs: Contrasting Us And German University Curricula, Paniz Hazaveh, Aleksandr Sergeyev, Nathir Rawashdeh
Mechatronics Bachelor Curriculum Development In Light Of Industry 4.0 Technology Needs: Contrasting Us And German University Curricula, Paniz Hazaveh, Aleksandr Sergeyev, Nathir Rawashdeh
Michigan Tech Publications
This study compares Mechatronics bachelor curricula at universities in the United States of America and German universities. Mechatronics education is relatively new in the United States, but has been common in Germany for over a decade. With the multidisciplinary nature of technologies required by the 4’th industrial revolution, a.k.a. Industry 4.0, composing an appropriate Mechatronics curriculum becomes a challenge and an opportunity. This paper studies how Mechatronics education can address the future needs of industry, while building on a specific university’s strengths and industry links. We have also analyzed the new undergraduate Mechatronics program at Michigan Technological University (MTU) and …
The Missing Link Between Standing-And Traveling-Wave Resonators, Qi Zhong, Haoqi Zhao, Liang Feng, Kurt Busch, Sahin K. Özdemir, Ramy El-Ganainy
The Missing Link Between Standing-And Traveling-Wave Resonators, Qi Zhong, Haoqi Zhao, Liang Feng, Kurt Busch, Sahin K. Özdemir, Ramy El-Ganainy
Michigan Tech Publications
Optical resonators are structures that utilize wave interference and feedback to confine light in all three dimensions. Depending on the feedback mechanism, resonators can support either standing-or traveling-wave modes. Over the years, the distinction between these two different types of modes has become so prevalent that nowadays it is one of the main characteristics for classifying optical resonators. Here, we show that an intermediate link between these two rather different groups exists. In particular, we introduce a new class of photonic resonators that supports a hybrid optical mode, i.e. at one location along the resonator the electromagnetic fields associated with …
Through-Ice Acoustic Source Tracking Using Vision Transformers With Ordinal Classification, Steven Whitaker, Andrew Barnard, George D. Anderson, Timothy C. Havens
Through-Ice Acoustic Source Tracking Using Vision Transformers With Ordinal Classification, Steven Whitaker, Andrew Barnard, George D. Anderson, Timothy C. Havens
Michigan Tech Publications
Ice environments pose challenges for conventional underwater acoustic localization techniques due to theirmultipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Vision Transformers (ViTs), for passive localization and tracking of single moving, on-ice acoustic sources using two underwater acoustic vector sensors. We incorporate ordinal classification as a localization approach and compare the results with other standard methods. We conduct experiments passively recording the acoustic signature of an anthropogenic source on the ice and analyze these data. The results demonstrate that Vision Transformers are …
Mobile-Polypnet: Lightweight Colon Polyp Segmentation Network For Low-Resource Settings, Ranit Karmakar, Saeid Nooshabadi
Mobile-Polypnet: Lightweight Colon Polyp Segmentation Network For Low-Resource Settings, Ranit Karmakar, Saeid Nooshabadi
Michigan Tech Publications
Colon polyps, small clump of cells on the lining of the colon, can lead to colorectal cancer (CRC), one of the leading types of cancer globally. Hence, early detection of these polyps automatically is crucial in the prevention of CRC. The deep learning models proposed for the detection and segmentation of colorectal polyps are resource-consuming. This paper proposes a lightweight deep learning model for colorectal polyp segmentation that achieved state-of-the-art accuracy while significantly reducing the model size and complexity. The proposed deep learning autoencoder model employs a set of state-of-the-art architectural blocks and optimization objective functions to achieve the desired …