Open Access. Powered by Scholars. Published by Universities.®

Mechanical Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1 - 30 of 350

Full-Text Articles in Mechanical Engineering

Challenges And Opportunities In Machine-Augmented Plant Stress Phenotyping, Arti Singh, Sarah Jones, Baskar Ganapathysubramanian, Soumik Sarkar, Daren S. Mueller, Kulbir Sandhu, Koushik Nagasubramanian Aug 2020

Challenges And Opportunities In Machine-Augmented Plant Stress Phenotyping, Arti Singh, Sarah Jones, Baskar Ganapathysubramanian, Soumik Sarkar, Daren S. Mueller, Kulbir Sandhu, Koushik Nagasubramanian

Mechanical Engineering Publications

Plant stress phenotyping is essential to select stress-resistant varieties and develop better stress-management strategies. Standardization of visual assessments and deployment of imaging techniques have improved the accuracy and reliability of stress assessment in comparison with unaided visual measurement. The growing capabilities of machine learning (ML) methods in conjunction with image-based phenotyping can extract new insights from curated, annotated, and high-dimensional datasets across varied crops and stresses. We propose an overarching strategy for utilizing ML techniques that methodically enables the application of plant stress phenotyping at multiple scales across different types of stresses, program goals, and environments.


Leaf Angle Extractor: A High‐Throughput Image Processing Framework For Leaf Angle Measurements In Maize And Sorghum, Sunil K. Kenchanmane Raju, Miles Adkins, Alex Enersen, Daniel Santana De Carvalho, Anthony J. Studer, Baskar Ganapathysubramanian, Patrick S. Schnable, James C. Schnable Aug 2020

Leaf Angle Extractor: A High‐Throughput Image Processing Framework For Leaf Angle Measurements In Maize And Sorghum, Sunil K. Kenchanmane Raju, Miles Adkins, Alex Enersen, Daniel Santana De Carvalho, Anthony J. Studer, Baskar Ganapathysubramanian, Patrick S. Schnable, James C. Schnable

Mechanical Engineering Publications

PREMISE: Maize yields have significantly increased over the past half-century owing to advances in breeding and agronomic practices. Plants have been grown in increasingly higher densities due to changes in plant architecture resulting in plants with more upright leaves, which allows more efficient light interception for photosynthesis. Natural variation for leaf angle has been identified in maize and sorghum using multiple mapping populations. However, conventional phenotyping techniques for leaf angle are low throughput and labor intensive, and therefore hinder a mechanistic understanding of how the leaf angle of individual leaves changes over time in response to the environment.

METHODS: High-throughput ...


Automated Trichome Counting In Soybean Using Advanced Image‐Processing Techniques, Seyed Vahid Mirnezami, Therin Young, Teshale Assefa, Shelby Prichard, Koushik Nagasubramanian, Kulbir Sandhu, Soumik Sarkar, Sriram Sundararajan, Matthew E. O'Neal, Baskar Ganapathysubramanian, Arti Singh Jul 2020

Automated Trichome Counting In Soybean Using Advanced Image‐Processing Techniques, Seyed Vahid Mirnezami, Therin Young, Teshale Assefa, Shelby Prichard, Koushik Nagasubramanian, Kulbir Sandhu, Soumik Sarkar, Sriram Sundararajan, Matthew E. O'Neal, Baskar Ganapathysubramanian, Arti Singh

Mechanical Engineering Publications

Premise Trichomes are hair‐like appendages extending from the plant epidermis. They serve many important biotic roles, including interference with herbivore movement. Characterizing the number, density, and distribution of trichomes can provide valuable insights on plant response to insect infestation and define the extent of plant defense capability. Automated trichome counting would speed up this research but poses several challenges, primarily because of the variability in coloration and the high occlusion of the trichomes.

Methods and Results We developed a simplified method for image processing for automated and semi‐automated trichome counting. We illustrate this process using 30 leaves from ...


Towards A Cyber-Physical Manufacturing Cloud Through Operable Digital Twins And Virtual Production Lines, Md Rakib Shahriar Jul 2020

Towards A Cyber-Physical Manufacturing Cloud Through Operable Digital Twins And Virtual Production Lines, Md Rakib Shahriar

Theses and Dissertations

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services ...


Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, Nicholas Deily May 2020

Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, Nicholas Deily

Engineering and Applied Science Theses & Dissertations

Many industries are rapidly adopting additive manufacturing (AM) because of the added versatility this technology offers over traditional manufacturing techniques. But with AM, there comes a unique set of security challenges that must be addressed. In particular, the issue of part verification is critically important given the growing reliance of safety-critical systems on 3D printed parts. In this thesis, the current state of part verification technologies will be examined in the con- text of AM-specific geometric-modification attacks, and an automated tool for 3D printed part verification will be presented. This work will cover: 1) the impacts of malicious attacks on ...


College Of Engineering Senior Design Competition Spring 2020, University Of Nevada, Las Vegas May 2020

College Of Engineering Senior Design Competition Spring 2020, University Of Nevada, Las Vegas

Senior Projects (COE)

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the ...


Investigating The Feasibility And Stability For Modeling Acoustic Wave Scattering Using A Time-Domain Boundary Integral Equation With Impedance Boundary Condition, Michelle E. Rodio Apr 2020

Investigating The Feasibility And Stability For Modeling Acoustic Wave Scattering Using A Time-Domain Boundary Integral Equation With Impedance Boundary Condition, Michelle E. Rodio

Mathematics & Statistics Theses & Dissertations

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners

This work considers using either an impedance or an admittance (inverse ...


Observer-Based Event-Triggered And Set-Theoretic Neuro-Adaptive Controls For Constrained Uncertain Systems, Abdul Ghafoor Jan 2020

Observer-Based Event-Triggered And Set-Theoretic Neuro-Adaptive Controls For Constrained Uncertain Systems, Abdul Ghafoor

Doctoral Dissertations

"In this study, several new observer-based event-triggered and set-theoretic control schemes are presented to advance the state of the art in neuro-adaptive controls. In the first part, six new event-triggered neuro-adaptive control (ETNAC) schemes are presented for uncertain linear systems. These comprehensive designs offer flexibility to choose a design depending upon system performance requirements. Stability proofs for each scheme are presented and their performance is analyzed using benchmark examples. In the second part, the scope of the ETNAC is extended to uncertain nonlinear systems. It is applied to a case of precision formation flight of the microsatellites at the Sun-Earth ...


Usefulness Of Interpretability Methods To Explain Deep Learning Based Plant Stress Phenotyping, Koushik Nagasubramanian, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian Jan 2020

Usefulness Of Interpretability Methods To Explain Deep Learning Based Plant Stress Phenotyping, Koushik Nagasubramanian, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian

Mechanical Engineering Publications

Deep learning techniques have been successfully deployed for automating plant stress identification and quantification. In recent years, there is a growing push towards training models that are interpretable -i.e. that justify their classification decisions by visually highlighting image features that were crucial for classification decisions. The expectation is that trained network models utilize image features that mimic visual cues used by plant pathologists. In this work, we compare some of the most popular interpretability methods: Saliency Maps, SmoothGrad, Guided Backpropogation, Deep Taylor Decomposition, Integrated Gradients, Layer-wise Relevance Propagation and Gradient times Input, for interpreting the deep learning model. We ...


Industrial Scale Large Eddy Simulations (Les) With Adaptive Octree Meshes Using Immersogeometric Analysis, Kumar Saurabh, Boshun Gao, Milinda Fernando, Songzhe Xu, Biswajit Khara, Makrand A. Khanwale, Ming-Chen Hsu, Adarsh Krishnamurthy, Hari Sundar, Baskar Ganapathysubramanian Jan 2020

Industrial Scale Large Eddy Simulations (Les) With Adaptive Octree Meshes Using Immersogeometric Analysis, Kumar Saurabh, Boshun Gao, Milinda Fernando, Songzhe Xu, Biswajit Khara, Makrand A. Khanwale, Ming-Chen Hsu, Adarsh Krishnamurthy, Hari Sundar, Baskar Ganapathysubramanian

Mechanical Engineering Publications

We present a variant of the immersed boundary method integrated with octree meshes for highly efficient and accurate Large-Eddy Simulations (LES) of flows around complex geometries. We demonstrate the scalability of the proposed method up to O(32K) processors. This is achieved by (a) rapid in-out tests; (b) adaptive quadrature for an accurate evaluation of forces; (c) tensorized evaluation during matrix assembly. We showcase this method on two non-trivial applications: accurately computing the drag coefficient of a sphere across Reynolds numbers 1−106 encompassing the drag crisis regime; simulating flow features across a semi-truck for investigating the effect of platooning ...


Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak Jan 2020

Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports

Practical decision makers are inherently limited by computational and memory resources as well as the time available in which to make decisions. To cope with these limitations, humans actively seek methods which limit their resource demands by exploiting structure within the environment and exploiting a coupling between their sensing and actuation to form heuristics for fast decision-making. To date, such behavior has not been replicated in artificial agents. This research explores how heuristics may be incorporated into the decision-making process to quickly make high-quality decisions through the analysis of a prominent case study: the outfielder problem. In the outfielder problem ...


How Useful Is Active Learning For Image-Based Plant Phenotyping?, Koushik Nagasubramanian, Talukder Z. Jubery, Fateme Fotouhi Ardakani, Seyed Vahid Mirnezami, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian Jan 2020

How Useful Is Active Learning For Image-Based Plant Phenotyping?, Koushik Nagasubramanian, Talukder Z. Jubery, Fateme Fotouhi Ardakani, Seyed Vahid Mirnezami, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian

Mechanical Engineering Publications

Deep learning models have been successfully deployed for a diverse array of image-based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requires large amount of labeled data, which is a significant challenge in plant science (and most biological) domains due to the inherent complexity. Specifically, data annotation is costly, laborious, time consuming and needs domain expertise for phenotyping tasks, especially for diseases. To overcome this challenge, active learning algorithms have been proposed that reduce the amount of labeling needed by deep learning models to achieve good predictive performance. Active learning methods adaptively ...


Smart Factories, Dumb Policy? Managing Cybersecurity And Data Privacy Risks In The Industrial Internet Of Things, Scott J. Shackelford Dec 2019

Smart Factories, Dumb Policy? Managing Cybersecurity And Data Privacy Risks In The Industrial Internet Of Things, Scott J. Shackelford

Minnesota Journal of Law, Science & Technology

No abstract provided.


College Of Engineering Senior Design Competition Fall 2019, University Of Nevada, Las Vegas Dec 2019

College Of Engineering Senior Design Competition Fall 2019, University Of Nevada, Las Vegas

Senior Projects (COE)

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the ...


Design And Modeling Of A New Biomimetic Soft Robotic Jellyfish Using Ipmc-Based Electroactive Polymers, Zakai J. Olsen, Kwang J. Kim Nov 2019

Design And Modeling Of A New Biomimetic Soft Robotic Jellyfish Using Ipmc-Based Electroactive Polymers, Zakai J. Olsen, Kwang J. Kim

Mechanical Engineering Faculty Publications

Smart materials and soft robotics have been seen to be particularly well-suited for developing biomimetic devices and are active fields of research. In this study, the design and modeling of a new biomimetic soft robot is described. Initial work was made in the modeling of a biomimetic robot based on the locomotion and kinematics of jellyfish. Modifications were made to the governing equations for jellyfish locomotion that accounted for geometric differences between biology and the robotic design. In particular, the capability of the model to account for the mass and geometry of the robot design has been added for better ...


Interpretable Deep Learning For Guided Microstructure-Property Explorations In Photovoltaics, Balaji Sesha Sarath Pokuri, Sambuddha Ghosal, Apurva Kokate, Soumik Sarkar, Baskar Ganapathysubramanian Oct 2019

Interpretable Deep Learning For Guided Microstructure-Property Explorations In Photovoltaics, Balaji Sesha Sarath Pokuri, Sambuddha Ghosal, Apurva Kokate, Soumik Sarkar, Baskar Ganapathysubramanian

Mechanical Engineering Publications

The microstructure determines the photovoltaic performance of a thin film organic semiconductor film. The relationship between microstructure and performance is usually highly non-linear and expensive to evaluate, thus making microstructure optimization challenging. Here, we show a data-driven approach for mapping the microstructure to photovoltaic performance using deep convolutional neural networks. We characterize this approach in terms of two critical metrics, its generalizability (has it learnt a reasonable map?), and its intepretability (can it produce meaningful microstructure characteristics that influence its prediction?). A surrogate model that exhibits these two features of generalizability and intepretability is particularly useful for subsequent design exploration ...


Analytical Approach To Investigation Of Free Vibration Of Thin Rectangular Plate Immersed In Fluid, Resting On Winkler And Pasternak Foundations, Obanishola Sadiq, Gbeminiyi Sobamowo, Saheed Salawu Sep 2019

Analytical Approach To Investigation Of Free Vibration Of Thin Rectangular Plate Immersed In Fluid, Resting On Winkler And Pasternak Foundations, Obanishola Sadiq, Gbeminiyi Sobamowo, Saheed Salawu

Karbala International Journal of Modern Science

Dynamic behaviour of free vibration of rectangular plate is investigated. This study considered an analytical approach to investigation of free vibration of thin rectangular plate immersed in fluid, resting on Winkler and Pasternak foundations.The governing nonlinear partial differential equation is analyzed using two-dimensional differential transform method. The accuracy of the analytical solutions obtained is verified with existing results in literature and confirmed in excellent agreement. Thereafter, the analytical solutions are used for investigation of effect of elastic foundation, fluid and aspect ratio on vibrating plate.From the result, it is observed that, increase elastic foundation parameters increases natural frequency ...


Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin Aug 2019

Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin

Computer Science Faculty Research & Creative Works

Production innovations are occurring faster than ever. Manufacturing workers thus need to frequently learn new methods and skills. In fast changing, largely uncertain production systems, manufacturers with the ability to comprehend workers' behavior and assess their operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize ...


Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde Jun 2019

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

Mechanical Engineering Publications

Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, training samples obey invariances that are \textit{a priori} known; for example, in complex physics simulations, the training data obey universal laws encoded as well-defined mathematical equations. In this paper, we propose a new generative modeling approach, InvNet, that can efficiently model data spaces with known invariances. We devise an adversarial training algorithm to encode them into data distribution. We validate our framework in three experimental settings: generating images with fixed motifs; solving nonlinear partial differential equations (PDEs); and ...


College Of Engineering Senior Design Competition Spring 2019, University Of Nevada, Las Vegas May 2019

College Of Engineering Senior Design Competition Spring 2019, University Of Nevada, Las Vegas

Senior Projects (COE)

Part of every UNLV engineering student’s academic experience, the senior design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs, and prototypes a product in this required element of the curriculum. A capstone to the student’s educational career, the senior design project encourages the student to use everything learned in the engineering program to create a practical, real world solution to an engineering challenge. The senior design competition helps focus the senior students in increasing the quality and potential for commercial application for their design projects. Judges from local industry evaluate the ...


Motor Control Systems Analysis, Design, And Optimization Strategies For A Lightweight Excavation Robot, Austin Jerold Crawford May 2019

Motor Control Systems Analysis, Design, And Optimization Strategies For A Lightweight Excavation Robot, Austin Jerold Crawford

Theses and Dissertations

This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective ...


Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano May 2019

Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano

Theses and Dissertations

This research proposes novel fault adaptive workload allocation (FAWA) strategies for the health management of complex manufacturing systems. The primary goal of these strategies is to minimize maintenance costs and maximize production by strategically controlling when and where failures occur through condition-based workload allocation.

For complex systems that are capable of performing tasks a variety of different ways, such as an industrial robot arm that can move between locations using different joint angle configurations and path trajectories, each option, i.e. mission plan, will result in different degradation rates and life-expectancies. Consequently, this can make it difficult to predict when ...


The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup May 2019

The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup

UNLV Theses, Dissertations, Professional Papers, and Capstones

Methods for prolonged compassionate care for persons with Profound Intellectual and Multiple Disabilities (PIMD) require a rotating cast of import people in the subjects life in order to facilitate interaction with the external environment. As subjects continue to age, dependency on these people increases with complexity of communications while the quality of communication decreases. It is theorized that a machine learning (ML) system could replicate the attuning process and replace these people to promote independence. This thesis extends this idea to develop a conceptual and formal model and system prototype.

The main contributions of this thesis are: (1) proposal of ...


Numerical Investigation Of Inclination On The Thermal Performance Of Porous Fin Heatsink Using Pseudospectral Collocation Method, George Oguntala, Gbeminiyi Sobamowo, Raed Abd-Alhameed, James Noras Mar 2019

Numerical Investigation Of Inclination On The Thermal Performance Of Porous Fin Heatsink Using Pseudospectral Collocation Method, George Oguntala, Gbeminiyi Sobamowo, Raed Abd-Alhameed, James Noras

Karbala International Journal of Modern Science

Numerical investigation of inclination effect on the thermal performance of a porous fin heat sink is presented. The developed thermal model is solved using pseudo-spectral collocation method (PSCM). Parametric studies are carried out using PSCM, and the thermal characterization of heat sink with the inclined porous fin of rectangular geometry is presented. Results show that heat sink of inclined porous fin exhibits higher thermal performance than heat sink of vertical porous fin operating under the same thermal conditions with the same geometrical configurations. Performance of inclined or tilted fin increases with decrease in length-thickness aspect ratio. However, increase in the ...


Deep Learning For Monitoring Cyber-Physical Systems, Tryambak Gangopadhyay Jan 2019

Deep Learning For Monitoring Cyber-Physical Systems, Tryambak Gangopadhyay

Graduate Theses and Dissertations

Different cyber-physical systems involving sequential data require accurate frameworks for predicting the state of the system leading to effective monitoring. If the framework is explanatory, the insights provided by the explanations can improve scientific understanding of the system. Detecting the transition to an impending instability is important to initiate effective control in a combustion system. Building robust frameworks is important in this context.

As one of the early applications of characterizing instability in a combustion system using Deep Neural Networks, we train our proposed deep convolutional neural network (CNN) model on sequential image frames extracted from hi-speed flame videos by ...


Applying Computer Vision For Detection Of Diseases In Plants, Xuan Truong Tran Jan 2019

Applying Computer Vision For Detection Of Diseases In Plants, Xuan Truong Tran

Graduate Theses and Dissertations

Early detection and quantification of diseases in food plants are critical to agriculture industry and national food security. However, limitation in technology and cost has limited the success of applying Computer Vision in Plant Science. This research builds on the recent advance of Machine Learning, GPU and smartphones to tackle the problem of fast and low cost diagnosis of plant disease. In particular, we choose soybean as the subject for applying automatic disease detection. The reason is because soybean is an important crop for the state of Iowa and an important source of food for America. The plant is however ...


The Borrowbike, Martin Woodby, Grayson Taylor, Jesse Rubenstein, Aaron Leung, Jack Padon, Ryan Dehart Jan 2019

The Borrowbike, Martin Woodby, Grayson Taylor, Jesse Rubenstein, Aaron Leung, Jack Padon, Ryan Dehart

Engineering E-Portfolios and Projects

The BorrowBike is turning UP's bike rental system from an inconvenient process to a hassle-free swipe of a card. BorrowBike's smart lock and online web application streamlines the check-out process and allows bikes to be rented at any time of the day.


Ir Motion Tracking Robotic Arm, Gavin Low, Andrew Doan, Avery Guillermo, Dayna Yoshimura Jan 2019

Ir Motion Tracking Robotic Arm, Gavin Low, Andrew Doan, Avery Guillermo, Dayna Yoshimura

Engineering E-Portfolios and Projects

The Motion Tracking Robot Arm is a senior Electrical Engineering Capstone project designed by Andrew Doan, Avery Guillermo, Gavin Low, and Dayna Yoshimura. The project serves as an exploration of alternative control methods for robotic arms. While standard robotic arms are often controlled with physical controllers or computer programs, this robotic arm will be controlled with a LEAP motion controller. The user will be able to control the robotic arm using his or her own arm; no extra control inputs will be necessary.


Good Similar Patches For Image Denoising (Poster), Si Lu Jan 2019

Good Similar Patches For Image Denoising (Poster), Si Lu

Computer Science Faculty Publications and Presentations

Patch-based denoising algorithms like BM3D have achieved outstanding performance. An important idea for the success of these methods is to exploit the recurrence of similar patches in an input image to estimate the underlying image structures....


Development Of A Sensing System For Underground Optic Fiber Cable Conduit Mapping, Sherif Bakr Jan 2019

Development Of A Sensing System For Underground Optic Fiber Cable Conduit Mapping, Sherif Bakr

All Graduate Theses, Dissertations, and Other Capstone Projects

The motivation of this research is to obtain an accurate three-dimensional (3D) layout of an underground conduit, which may be beneficial to optic fiber cable installers and engineers. A newly designed algorithm for 3D position tracking with the help of an inertial sensor and an encoder has been developed. Two types of representations (Euler angle and Quaternion) for orientation and rotation are also introduced, followed by several data pre-processing procedures. A sensing fusion method is utilized to overcome the accumulated errors introduced by the sensor drifting. Considering the application of 3D underground duct mapping in this research, a sensing system ...