Automated Blind Control,
2021
The University of Akron
Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa
Williams Honors College, Honors Research Projects
The objective of this project would be to design and prototype an automated, light and temperature sensing window blinds system. The device would detect temperature, both inside and outside, and incoming sunlight to determine proper window blind position for maximum energy savings. The user would also have the ability to change the settings of the blind from a remote device to a setting that they desire at any given time
Soil Sensor Network,
2021
The University of Akron
Soil Sensor Network, Andrea Wyder, Ross Klonowski, Alexis Alves, Luke Farnsworth
Williams Honors College, Honors Research Projects
Water management during crop irrigation is a problem for the agricultural industry. To help farmers better maintain water usage, a wireless soil sensor network comprised of a sensor pod and wireless communication has been designed and implemented. It was proven that the sensor pod can be installed 6-8 inches below the ground and communicate up to at least a 6km distance back to the gateway. The senor pod shells have a 2 mm thick shell to prevent the pod from shattering when coming into contact with the ground after being released from the planter, as calculated through the force of …
Light Loaded Automated Guided Vehicle,
2021
The University of Akron
Light Loaded Automated Guided Vehicle, Marcus Radtka, Nazar Paramashchuk, Lawrence Shevock
Williams Honors College, Honors Research Projects
The objective of the locomotion system was to design and implement the mechanical, electrical, and software related functions to ensure the LLAGV had the capability of maneuvering its surroundings. The LLAGV’s motors were represented in an open loop transfer function to utilize RPM feedback and a compensator when needed. The modeled compensator helped control the LLAGV’s speed and acceleration, enabling further control of the LLAGV. The internal circuitry has the means to properly distributed power to all components and allowed the user to control the LLAGV to their desire. The application software within the LLAGV locomotion system (LLAGV-LS) had consideration …
The Youplanner,
2021
The University of Akron
The Youplanner, Taylor Burgess
Williams Honors College, Honors Research Projects
Staying organized can be difficult. A four tier web application was created to help in the endeavor. Utilizing software engineering practices, an online notepad was created where users can add, update, and delete notes. The application was a full stack application. For the backend, MySQL was the language and phpMyAdmin was the server. For the front end, PHP and Bootstrap 5.1 was used.
Schizophrenia Classification Using Resting State Eeg Functional Connectivity: Source Level Outperforms Sensor Level,
2021
Missouri University of Science and Technology
Schizophrenia Classification Using Resting State Eeg Functional Connectivity: Source Level Outperforms Sensor Level, Sima Azizi, Daniel B. Hier, Donald C. Wunsch
Chemistry Faculty Research & Creative Works
Disrupted Functional and Structural Connectivity Measures Have Been Used to Distinguish Schizophrenia Patients from Healthy Controls. Classification Methods based on Functional Connectivity Derived from EEG Signals Are Limited by the Volume Conduction Problem. Recorded Time Series at Scalp Electrodes Capture a Mixture of Common Sources Signals, Resulting in Spurious Connections. We Have Transformed Sensor Level Resting State EEG Times Series to Source Level EEG Signals Utilizing a Source Reconstruction Method. Functional Connectivity Networks Were Calculated by Computing Phase Lag Values between Brain Regions at Both the Sensor and Source Level. Brain Complex Network Analysis Was Used to Extract Features and …
Subsumption Reduces Dataset Dimensionality Without Decreasing Performance Of A Machine Learning Classifier,
2021
Missouri University of Science and Technology
Subsumption Reduces Dataset Dimensionality Without Decreasing Performance Of A Machine Learning Classifier, Donald C. Wunsch, Daniel B. Hier
Chemistry Faculty Research & Creative Works
When Features in a High Dimension Dataset Are Organized Hierarchically, There is an Inherent Opportunity to Reduce Dimensionality. Since More Specific Concepts Are Subsumed by More General Concepts, Subsumption Can Be Applied Successively to Reduce Dimensionality. We Tested Whether Sub-Sumption Could Reduce the Dimensionality of a Disease Dataset Without Impairing Classification Accuracy. We Started with a Dataset that Had 168 Neurological Patients, 14 Diagnoses, and 293 Unique Features. We Applied Subsumption Repeatedly to Create Eight Successively Smaller Datasets, Ranging from 293 Dimensions in the Largest Dataset to 11 Dimensions in the Smallest Dataset. We Tested a MLP Classifier on All …
Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems,
2021
University of Central Florida
Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems, Baogang Zhang
Electronic Theses and Dissertations, 2020-2023
With the accessible data reaching zettabyte level, CMOS technology is reaching its limit for the data hungry applications. Moore's law has been reaching its depletion in recent studies. On the other hand, von Neumann architecture is approaching the bottleneck due to the data movement between the computing and memory units. With data movement and power budgets becoming the limiting factors of today's computing systems, in-memory computing using emerging non-volatile resistive devices has attracted an increasing amount of attention. A non-volatile resistive device may be realized using memristor, resistive random access memory (ReRAM), phase change memory (PCM), or spin-transfer torque magnetic …
Effect Of Digital Advertising On Website Traffic At A Kentucky Comprehensive Regional University,
2021
Eastern Kentucky University
Effect Of Digital Advertising On Website Traffic At A Kentucky Comprehensive Regional University, Brandon Lee Moore
Online Theses and Dissertations
The purpose of this research is to quantify differences in key performance indicators between paid and organic (not paid) website traffic over a one year period of time at a regional comprehensive university in Kentucky, which is located in the southeastern United States. Two distinct sources of website traffic can be measured: paid traffic and organic traffic. Using data from website traffic analytics, this study employed multiple linear regression analysis and time series methods to understand the similarities and differences between key performance indicators of paid traffic and organic traffic as they relate to key performance indicators. Data from Google …
Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication,
2021
TÜBİTAK
Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh
Turkish Journal of Electrical Engineering and Computer Sciences
A point-to-point (P2P) communication system based on the CPM-DSSS scheme ensures reliability, security, and antijamming capabilities. However, for reliable detection of data carrier synchronization of CPM-DSSS based system is one of the requirements. This paper presents a joint algorithm for carrier frequency offset (CFO) and carrier phase offset (CPO) estimation for CPM-DSSS based P2P system. The results indicate that the proposed CFO estimator is unbiased and can accurately estimate a wide range of offsets. Moreover, the proposed algorithm is compared with another research work. The results show that the proposed CFO and CPO estimation algorithm outperforms its counterpart with a …
A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation,
2021
TÜBİTAK
A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün
Turkish Journal of Electrical Engineering and Computer Sciences
A hybrid numerical model is presented for solving long range electromagnetic wave propagation problems involving objects on or above the ground surface by hybridizing the two-way split-step parabolic equation (2W-SSPE) method with the method of moments (MoM). The advantages of the proposed model are twofold: (i) It reduces the staircasing error in irregular terrain modeling, which usually occurs when the standard SSPE method is used alone. This is achieved by employing the MoM to more accurately obtain the scattered fields from slanted/curved surfaces. (ii) It enables the SSPE method to handle the problems involving objects above the Earth's surface, which …
Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique,
2021
TÜBİTAK
Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the modification of the Deb feasibility method is considered to solve the constrained optimization problems. In the developed modified Deb feasibility constraint method, the third rule in its procedure was revised in order to increase the performance of the Deb feasibility constraint handling method. The innovation in the method is based on generating a new individual by using both possible solutions that violate the constraints in the method used for solving the problem. In detail, discussions were given about the application and usefulness of six constrained handling techniques. Furthermore, genetic algorithm, particle swarm optimization, Harris hawks optimization, …
Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain,
2021
TÜBİTAK
Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan
Turkish Journal of Electrical Engineering and Computer Sciences
Multimodal medical image fusion approaches have been commonly used to diagnose diseases and involve merging multiple images of different modes to achieve superior image quality and to reduce uncertainty and redundancy in order to increase the clinical applicability. In this paper, we proposed a new medical image fusion algorithm based on a convolutional neural network (CNN) to obtain a weight map for multiscale transform (curvelet/ non-subsampled shearlet transform) domains that enhance the textual and edge property. The aim of the method is achieving the best visualization and highest details in a single fused image without losing spectral and anatomical details. …
Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇
Turkish Journal of Electrical Engineering and Computer Sciences
Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common method used in brain imaging to study neurological disorders. Diagnosis of neurological disorders such as ALS, Parkinson's, attention deficit hyperactivity disorder is important in biomedical studies. In recent years, deep learning (DL) models have been started to be applied in the literature for the diagnosis of these diseases. In this study, event-related potentials (ERPs) were obtained from EEG signals obtained as a …
Crosswalk Sensor System,
2021
The University of Akron
Crosswalk Sensor System, Jacob Schandel, Mohammed Alsubhi, Aaron Gloeckler, Samuel Turner
Williams Honors College, Honors Research Projects
A number of safety concerns persist with modern crosswalks. People are distracted by things in their car, or their surroundings can make it hard to see oncoming pedestrians. With today’s self-sufficient power technologies, available sensors, and cheap low-power wireless communication protocols, it is possible to create digital signage to warn of oncoming pedestrians. By using distance sensors such as ultrasonic or infrared sensors, systems can detect where objects, or in this case people, are with respect to a sensor on a fixed pole. With low-powered illumination technologies like LEDs and low-powered IoT communication protocols like ZigBee, a system can communicate …
Smart Doggy Door,
2021
The University of Akron
Smart Doggy Door, Jaret Helminski, Brandon Caldwell, Jason Marcum, Nathaniel Hall
Williams Honors College, Honors Research Projects
The smart doggy door is an engineering senior design project which will be completed in the spring of 2021. The goal of this project is to design and implement a dog door that can detect when a dog is near. After that it will determine if the dog is allowed to use the door and it will then open if the dog is allowed to go through the door. This device will also send a notification to the dogs owner via an app on their phone. This device will allow dog owners to keep unwanted animals out as well as …
Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network,
2021
Wright State University
Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev
Browse all Theses and Dissertations
Scientific collaboration between researchers is very common and much influential and ground-breaking research is performed by teams comprised of scientist from different fields and organizations. In this thesis, we analyze and model a small scientific collaboration network limited to two organizations: Wright State University and the Air Force Research Laboratory. Research paper co-authorship is used for establishing the network structure. We analyze several network properties and compare them to past results from analysis of larger and more diverse collaboration networks. We show that the two-organization network we explored exhibits properties similar to those of larger networks. Guided by advances in …
Computational Simulation And Analysis Of Neuroplasticity,
2021
Wright State University
Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey
Browse all Theses and Dissertations
Homeostatic synaptic plasticity is the process by which neurons alter their activity in response to changes in network activity. Neuroscientists attempting to understand homeostatic synaptic plasticity have developed three different mathematical methods to analyze collections of event recordings from neurons acting as a proxy for neuronal activity. These collections of events are from control data and treatment data, referring to the treatment of neuron cultures with pharmacological agents that augment or inhibit network activity. If the distribution of control events can be functionally mapped to the distribution of treatment events, a better understanding of the biological processes underlying homeostatic synaptic …
Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy,
2021
Wright State University
Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey
Browse all Theses and Dissertations
We consider the problem of compressive synthetic aperture radar (SAR) imaging with the goal of reconstructing SAR imagery in the presence of under sampled phase history. While this problem is typically considered in compressive sensing (CS) literature, we consider a variety of deep learning approaches where a deep neural network (DNN) is trained to form SAR imagery from limited data. At the cost of computationally intensive offline training, on-line test-time DNN-SAR has demonstrated orders of magnitude faster reconstruction than standard CS algorithms. A limitation of the DNN approach is that any change to the operating conditions necessitates a costly retraining …
Content Adaption And Design In Mobile Learning Of Wind Instruments,
2021
Wright State University
Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani
Browse all Theses and Dissertations
People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …
Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents,
2021
Wright State University
Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia
Browse all Theses and Dissertations
A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …
