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

Digital Commons Network™

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

Electrical and Computer Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 2311 - 2340 of 14409

Full-Text Articles in Entire DC Network

A High Performance Software Intensive Testbed For Rapid Prototyping And Controlled Testing Of Lte And Wi-Fi Radio Frequency Signals, Mirza Mohammad Maqbule Elahi Aug 2022

A High Performance Software Intensive Testbed For Rapid Prototyping And Controlled Testing Of Lte And Wi-Fi Radio Frequency Signals, Mirza Mohammad Maqbule Elahi

Open Access Theses & Dissertations

Long Term Evolution or LTE has gained interest for new applications that can benefit society including mobile broadband services like 802.11 or Wi-Fi. Both LTE and Wi-Fi uses similar modulation technique Orthogonal Frequency Division Multiplexing or OFDM. 6GHz sub carrier bands are crowded with LTE users. As wireless communications technology continues to develop, LTE technology in unlicensed bands (LTE-U) is a viable solution to the lack of spectrum resources. The competition between LTE-U and Wi-Fi will seriously impair their communication quality, so the friendly coexistence of both become an important research topic. This paper discusses the use of a software-defined …


Algorithms For Exploration Of Advanced Electromagnetic Concepts, Asad Ullah Hil Gulib Aug 2022

Algorithms For Exploration Of Advanced Electromagnetic Concepts, Asad Ullah Hil Gulib

Open Access Theses & Dissertations

3D printing is revolutionizing the manufacturing industry and is now being considered in the electronics industry. The creation of the worldâ??s first 3D volumetric circuit has made a way to make circuits smaller, lighter, into unconventional form factors and exploit physics like anisotropy more effectively than planar geometries can. While this is exciting, many problems must be solved to make 3D volumetric circuits more efficient. One of these problems is electromagnetic interference and mutual coupling between the circuit components that are expected to increase in high-frequency 3D circuits. Spatially variant anisotropic metamaterials (SVAMs) could be a solution to overcome this …


Development Of A Custom, 3d-Printed, Multi-Microphone, Noise-Cancelling, Hearing Protection Device With A Magnetically Attached Printed Ear Canal For Sound Localization Preservation, Brenda Leticia Valadez Mesta Aug 2022

Development Of A Custom, 3d-Printed, Multi-Microphone, Noise-Cancelling, Hearing Protection Device With A Magnetically Attached Printed Ear Canal For Sound Localization Preservation, Brenda Leticia Valadez Mesta

Open Access Theses & Dissertations

Hearing loss is a prominent health issue that affects a significant fraction of the global population. One of the main causes behind hearing loss is exposure to harmful noise levels in the workplace. There have been multiple efforts to prevent hearing loss from excessive noise in occupational settings, such as hearing conservation programs and use of hearing protection devices (HPDs), however, these are often ineffective. Although HPDs are frequently available in the workspace, they are not used as intended since they usually generate discomfort and hindered sound localization. The loss of sound localization can be hazardous in occupational settings, since …


Lifetime Maximization In Underwater Wireless Communication Networks, Kazi Yasin Islam, Iftekhar Ahmad, Daryoush Habibi, Jiong Jin, Muhammad Waqas Aug 2022

Lifetime Maximization In Underwater Wireless Communication Networks, Kazi Yasin Islam, Iftekhar Ahmad, Daryoush Habibi, Jiong Jin, Muhammad Waqas

Research outputs 2022 to 2026

The rise in demand for underwater wireless communication networks (UWCN) has been driven by the emergence of new applications including unmanned underwater vehicles, deep-sea exploration, maritime and underwater archaeology research, and diver communications. For various applications, underwater network lifetime must be long, since unlike terrestrial sensor networks, it is a major job to change/recharge node batteries in underwater environments. In this paper, we introduce a solution where critical nodes in a UWCN are periodically recharged by small renewable energy sources. Further, a caching mechanism is introduced to relieve critical nodes of heavy workload when their residual energies run low. By …


A Computational Approach To Evaluating Curricular Alignment To The United Nations Sustainable Development Goals, Philippe Lemarchand, Mick Mckeever, Cormac Macmahon, Philip Owende Aug 2022

A Computational Approach To Evaluating Curricular Alignment To The United Nations Sustainable Development Goals, Philippe Lemarchand, Mick Mckeever, Cormac Macmahon, Philip Owende

Articles

The United Nations (UN) considers universities to be key actors in the pursuit of the Sustainable Development Goals (SDGs). Yet, efforts to evaluate the embeddedness of the SDGs in university curricula tend to rely on manual analyses of curriculum documents for keywords contained in sustainability lexica, with little consideration for the diverse contexts of such keywords. The efficacy of these efforts, relying on expert co-elicitation in both subject-matter contexts and sustainability, suffers from drawbacks associated with keyword searches, such as limited coverage of key concepts, difficulty in extracting intended meaning and potential for greenwashing through “keyword stuffing.” This paper presents …


Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque Aug 2022

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque

Electrical & Computer Engineering Theses & Dissertations

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …


Feature Analysis Of Indus Valley And Dravidian Language Scripts With Similarity Matrices, Sarat Sasank Barla, Sai Surya Sanjay Alamuru, Peter Revesz Aug 2022

Feature Analysis Of Indus Valley And Dravidian Language Scripts With Similarity Matrices, Sarat Sasank Barla, Sai Surya Sanjay Alamuru, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper investigates the similarity between the Indus Valley script and the Kannada, Malayalam, Tamil, and Telugu scripts that are used to write Dravidian languages. The closeness of these scripts is determined by applying a feature analysis of each sign of these scripts and creating similarity matrices that describe the similarity of any pair of signs from two different scripts. The feature list that we use for the analysis of these Dravidian language-related scripts includes six new features beyond the thirteen features that were used for the study of Minoan Linear A and related scripts by Revesz. These new features …


Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche Aug 2022

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …


Evaluation Of Single Phase Smart Pv Inverter Functions In Unbalanced Residential Distribution Systems, Darren Symonette Aug 2022

Evaluation Of Single Phase Smart Pv Inverter Functions In Unbalanced Residential Distribution Systems, Darren Symonette

Graduate Theses and Dissertations

In the United States, smart PV inverters integrated with residential distribution systems are becoming a more common occurrence. With integration of smart PV inverters, power utilities are experiencing an increase of number of operations with regards to switched capacitor banks, voltage regulators and on load tap changers. These increases can lead to excess wear and tear on the devices causing power utilities to perform unwanted replacement and maintenance. However, smart PV inverters when controlled under specific functions can enable these inverters to provide reactive power and voltage control which in turn lowers the number of operations for switched capacitor banks, …


Materials Design For Energy Applications Using Ab- Initio Calculations, Hind Hemaidee Alqurashi Aug 2022

Materials Design For Energy Applications Using Ab- Initio Calculations, Hind Hemaidee Alqurashi

Graduate Theses and Dissertations

The structural, dynamical, electronic, and thermoelectric properties of rock-salt and wurtzite Cd1-xZnxO alloys, VTiRhZ (Al, Ga, In, Si, Ge, Sn) and ZrTiRhZ (Ge, Sn) quaternary Heusler alloys (QHAs) were investigated using density functional theory (DFT) and semi-classical Boltzmann transport theory. From these calculations, the alloys were identified as potential materials for future thermoelectric applications. Furthermore, the magnetic and spin-polarization properties of these QHAs were investigated. The total magnetic moments were found to be integer values for all QHAs. In addition, all studied QHAs except VTiRhAl possess a half-metallic behavior with a 100% spin-polarization. The half-metallic ferromagnetic behavior makes them promising …


A Physical Layer Security (Pls) Approach Through Address Fed Mapping Crest Factor Reduction Applicable For 5g/6g Signals, Somayeh Mohammady, David Malone Prof. Aug 2022

A Physical Layer Security (Pls) Approach Through Address Fed Mapping Crest Factor Reduction Applicable For 5g/6g Signals, Somayeh Mohammady, David Malone Prof.

Articles

The privacy and security of 5G/6G infrastructures are receiving great attention together with power consumption and efficiency. Here, Physical Layer Security (PLS) is considered and a technique named Address Fed Mapping (AFM) is proposed which not only enhances the physical layer security, but also reduces the effect of high Peak to Average Power Ratio (PAPR), which results in efficiency improvement in OFDM based signals used in beyond 5G and 6G. The AFM is designed based on the idea of randomly generated signals, modifying the original signal to reduce PAPR. Instead of a typical randomization algorithm, a unique key is generated …


A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations, Matthew Boeding Aug 2022

A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations, Matthew Boeding

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Operational Technology (OT) and Infrastructure Technology (IT) systems are converging with the rapid addition of centralized remote management in OT systems. Previously air-gapped systems are now interconnected through the internet with application-specific protocols. This has led to systems that had limited access points being remotely accessible. In different OT sectors, legacy protocols previously transmitted over serial communication were updated to allow internet communication with legacy devices. New protocols such as IEC-61850 were also introduced for monitoring of different OT resources. The IEC-61850 standard’s Generic Object Oriented Substation Event (GOOSE) protocol outlines the representation and communication of a variety of different …


Development Of High Quantum Efficiency Strained Superlattice Spin Polarized Photocathodes Via Metal Organic Chemical Vapor Deposition, Benjamin Belfore Aug 2022

Development Of High Quantum Efficiency Strained Superlattice Spin Polarized Photocathodes Via Metal Organic Chemical Vapor Deposition, Benjamin Belfore

Electrical & Computer Engineering Theses & Dissertations

Spin polarized photocathodes are necessary to examine parity violations and other fundamental phenomena in the field of high energy physics. To create these devices, expensive and complicated growth processes are necessary. While integral to accelerator physics, spin polarized electrons could have other exciting applications in materials science and other fields of physics. In order to explore these other applications feasibly, the relative supply of spin polarized photocathodes with a high rate of both polarization and photoemission needs to be increased. One such way to increase this supply is to develop the means to grow them faster and at a larger …


Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler Aug 2022

Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler

All Theses

As the field of Internet of Things (IoT) continues to grow, a variety of wireless signals fill the ambient wireless environment. These signals are used for communication, however, recently wireless sensing has been studied, in which these signals can be used to gather information about the surrounding space. With the development of 802.11n, a newer standard of WiFi, more complex information is available about the environment a signal propagates through. This information called Channel State Information (CSI) can be used in wireless sensing. With the help of Deep Learning, this work attempts to generate a fingerprinting technique for localizing a …


Miniaturized Battery Powered Air Quality Monitoring System, Bryan Chacon Aug 2022

Miniaturized Battery Powered Air Quality Monitoring System, Bryan Chacon

All Theses

In this work, an air quality monitoring system was developed using various sensors that measure specific air quality parameters, including Volatile Organic Compounds, Carbon Dioxide, particulate matter of varying sizes, ambient pressure, humidity, and temperature. This system is based off a Particle micro-controller, Boron LTE CAT-M1 which allows for cellular connectivity for real-time data transmission. It is powered by a 3.7 Volt Li-Po battery and has a miniaturized design which allows for portability. This data is processed through an Internet of Things software provider that allows for the device to be connected and accessed to and from anywhere in the …


Fetal Electrocardiogram Detection And Analysis From Maternal Abdominal Ecg For Diagnosis Of Fetal Heart Rhythm Abnormalities, Claudia L. Angel Aug 2022

Fetal Electrocardiogram Detection And Analysis From Maternal Abdominal Ecg For Diagnosis Of Fetal Heart Rhythm Abnormalities, Claudia L. Angel

Open Access Theses & Dissertations

Fetal cardiac arrhythmias are present in about 1–3% of pregnancies and account for about 10–20% of the referrals to fetal cardiology around the world. Most fetal arrhythmias are benign; however, some can cause fetal hydrops, preterm delivery, and higher perinatal morbidity and mortality. The evolution and treatment of fetal arrhythmia depend on a timely and complete diagnosis. However, conventional methods used in clinical practice for fetal arrhythmia diagnosis are limited since they do not reflect the primary electrophysiological conduction processes in the myocardium. Fetal electrocardiography (fECG) has the potential to better support fetal arrhythmia diagnosis through the continuous analysis of …


Design Of A Hemi-Anechoic Chamber For Acoustic Testing Of Hearing Devices And Development Of Custom-Designed 3d Printed Pinnae For Accurate Representation Of The Anatomical Frequency Response, Hector Hugo Estrada Medinilla Aug 2022

Design Of A Hemi-Anechoic Chamber For Acoustic Testing Of Hearing Devices And Development Of Custom-Designed 3d Printed Pinnae For Accurate Representation Of The Anatomical Frequency Response, Hector Hugo Estrada Medinilla

Open Access Theses & Dissertations

Sound localization is the capacity to identify the general location from which a sound is originating. The primary anatomical feature responsible for the ability to localize sound is the external portion of the ear, also known as the auricle or pinna. This faculty is significantly hindered when the ear is obstructed, as is the case with hearing protection devices (HPD), which act as a barrier between sound waves and the ear canal. In the case of electronic HPDs, certain frequencies are entirely filtered out by a digital sound processor (DSP) while the remaining frequencies are delivered directly into the ear …


Deep Learning For Robust Adaptive Inverse Control Of Nonlinear Dynamic Systems: Improved Settling Time With An Autoencoder, Nuha A. S. Alwan, Zahir M. Hussain Aug 2022

Deep Learning For Robust Adaptive Inverse Control Of Nonlinear Dynamic Systems: Improved Settling Time With An Autoencoder, Nuha A. S. Alwan, Zahir M. Hussain

Research outputs 2022 to 2026

An adaptive deep neural network is used in an inverse system identification setting to approximate the inverse of a nonlinear plant with the aim of constituting the plant controller by copying to the latter the weights and architecture of the converging deep neural network. This deep learning (DL) approach to the adaptive inverse control (AIC) problem is shown to outperform the adaptive filtering techniques and algorithms normally used in adaptive control, especially when in nonlinear plants. The deeper the controller, the better the inverse function approximation, provided that the nonlinear plant has an inverse and that this inverse can be …


Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa Jul 2022

Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa

Beyond: Undergraduate Research Journal

Radioactive sources, such as uranium-235, are nuclides that emit ionizing radiation, and which can be used to build nuclear weapons. In public areas, the presence of a radioactive nuclide can present a risk to the population, and therefore, it is imperative that threats are identified by radiological search and response teams in a timely and effective manner. In urban environments, such as densely populated cities, radioactive sources may be more difficult to detect, since background radiation produced by surrounding objects and structures (e.g., buildings, cars) can hinder the effective detection of unnatural radioactive material. This article presents a computational model …


Development Of A Configurable Real-Time Event Detection Framework For Power Systems Using Swarm Intelligence Optimization, Umar Farooq Jul 2022

Development Of A Configurable Real-Time Event Detection Framework For Power Systems Using Swarm Intelligence Optimization, Umar Farooq

Dissertations and Theses

Modern power systems characterized by complex topologies require accurate situational awareness to maintain an adequate level of reliability. Since they are large and spread over wide geographical areas, occurrence of failures is inevitable in power systems. Various generation and transmission disturbances give rise to a mismatch between generation and demand, which manifest as frequency events. These events can take the form of negligible frequency deviations or more severe emergencies that can precipitate cascading outages, depending on the severity of the disturbance and efficacy of remedial action schema. The impacts of such events have become more critical with recent decline in …


Failure Detection In Deep Neural Networks For Medical Imaging, Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool Jul 2022

Failure Detection In Deep Neural Networks For Medical Imaging, Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool

Electrical and Computer Engineering Faculty Publications

Deep neural networks (DNNs) have started to find their role in the modern healthcare system. DNNs are being developed for diagnosis, prognosis, treatment planning, and outcome prediction for various diseases. With the increasing number of applications of DNNs in modern healthcare, their trustworthiness and reliability are becoming increasingly important. An essential aspect of trustworthiness is detecting the performance degradation and failure of deployed DNNs in medical settings. The softmax output values produced by DNNs are not a calibrated measure of model confidence. Softmax probability numbers are generally higher than the actual model confidence. The model confidence-accuracy gap further increases for …


Interactive Planetarium Project, Eric Babcock, Cody Park, Johann Van Hilst Jul 2022

Interactive Planetarium Project, Eric Babcock, Cody Park, Johann Van Hilst

Discovery Day - Prescott

The Interactive Planetarium Project will design and build the software framework for connectivity between the Digistar 6 planetarium projection software and the smartphones of all audience members in the Jim and Linda Lee Planetarium. The goal of this project is to make planetarium shows more participatory, add a feature to our planetarium shows that many other universities do not yet have, and create a framework for future students and faculty to build from. To demonstrate our technology, we will make a real-time competitive trivia game able to support 60 concurrent users (number of expected audience members in the planetarium).

The …


Adaptive Balancing Compensation In Distribution Grid Of Ultra High-Power Manufacturing Plants, Motab Almousa Jul 2022

Adaptive Balancing Compensation In Distribution Grid Of Ultra High-Power Manufacturing Plants, Motab Almousa

LSU Doctoral Dissertations

This dissertation presents a method of adaptive compensation, capable of handling power factor and the supply quality improvement under non-sinusoidal conditions. The focus in this dissertation is put on developing compensation for ultra-high power metallurgical plants, meaning on compensation in three-phase, four-wire ultra-high power dynamic, distribution systems. A separate attention in the dissertation is put on the adaptive compensation of ultrahigh power arc furnaces. The dissertation also presents an original method of adaptive compensation of DC current generated by such arc furnaces.

The proposed compensator is developed in the frame of the Currents’ Physical Components (CPC) – based power theory. …


Combining Solution Reuse And Bound Tightening For Efficient Analysis Of Evolving Systems, Clay Stevens, Hamid Bagheri Jul 2022

Combining Solution Reuse And Bound Tightening For Efficient Analysis Of Evolving Systems, Clay Stevens, Hamid Bagheri

School of Computing: Conference and Workshop Papers

Software engineers have long employed formal verification to ensure the safety and validity of their system designs. As the system changes—often via predictable, domain-specific operations—their models must also change, requiring system designers to repeatedly execute the same formal verification on similar system models. State-of-the-art formal verification techniques can be expensive at scale, the cost of which is multiplied by repeated analysis. This paper presents a novel analysis technique—implemented in a tool called SoRBoT—which can automatically determine domain-specific optimizations that can dramatically reduce the cost of repeatedly analyzing evolving systems. Different from all prior approaches, which focus on either tightening the …


Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler Jul 2022

Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …


A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System, Mohammed Abdullah Alsaid Jul 2022

A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System, Mohammed Abdullah Alsaid

Dissertations and Theses

Emergent from the shadows of the traditional grid flaws, the Smart Grid (SG) idea was born and led by government mandates toward cleaner energy production. The SG represents the next generation of electricity distribution systems that subsume recent technological innovations. It uses digital communication between its components and entities to attain more automation, self-sufficiency, and reliability. Unfortunately, this relatively new concept is not flawless; the intrinsic reliance on increased digital communication spreads open attack paths for adversaries. Therefore, finding solutions that address information exchange vulnerabilities has become imperative.

The Energy Grid of Things (EGoT) is Portland State University's implementation of …


Machine Learning Approach For Classifying Power Outage In Secondary Electric Distribution Network, Stephan Mgaya, Hellen Maziku Jul 2022

Machine Learning Approach For Classifying Power Outage In Secondary Electric Distribution Network, Stephan Mgaya, Hellen Maziku

Tanzania Journal of Engineering and Technology (TJET)

Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still faces a challenge in effectively classifying power line outage due to the nature of imbalanced datasets. …


Detection Of Rotorcraft Landing Sites: An Ai-Based Approach, Abdullah Nasir Jul 2022

Detection Of Rotorcraft Landing Sites: An Ai-Based Approach, Abdullah Nasir

Theses and Dissertations

The updated information about the location and type of rotorcraft landing sites is an essential asset for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, acquiring, verifying, and regularly updating information about landing sites is not straightforward. The lack of current and correct information about landing sites is a risk factor in several rotorcraft accidents and incidents. The current FAA database of rotorcraft landing sites contains inaccurate and missing entries due to the manual updating process. There is a need for an accurate and automated validation tool to identify landing sites from satellite imagery. This thesis …


Device Based On Spectral Analysis For Detection And Correction Of Speech Defects In Uzbek Speaking Children, Sh K. Nematov, Y M. Kamolova Jul 2022

Device Based On Spectral Analysis For Detection And Correction Of Speech Defects In Uzbek Speaking Children, Sh K. Nematov, Y M. Kamolova

Technical science and innovation

В статье рассматриваются возможности и необходимость использования прибора на основе спектрального анализа для выявления и коррекции дефектов речи у узбекоязычных детей. Прибор относится к медицинской технике и специальной педагогике, может быть использован в диагностических исследованиях и реабилитационных процессах, связанных с измерением правильности произношения после установки кохлеарных имплантов у (узбекоязычных) детей с тугоухостью, для улучшения слуха и коррекции речи в слухо- слабоумным детям, направленные на совершенствование правильного произношения. произношение, развитие слуха и речи. Технически визуализация звучащей речи в этом комплексе достигается за счет улавливания звуков микрофоном, преобразования их в дополнительном устройстве, передачи сигнала на процессор, и затем отображение компонентов звучащей речи …


Stochastic Optimal Shared Control With Non-Gaussian Processes, Paul Onor Jul 2022

Stochastic Optimal Shared Control With Non-Gaussian Processes, Paul Onor

Electrical and Computer Engineering ETDs

In this paper, we propose an approach for shared control of a planar quadrotor that allows for non-Gaussian disturbance in the model and non-Gaussian variation in the pilot's control actions. We do this by constructing empirical characteristic functions for the state, inputs, and disturbance using demonstrations by a human expert. These are then used to make predictions of future states and of the system disturbance, using the first and second moments of the empirical characteristic function to estimate the mean and variance of these processes. With this method, we can extend assumptions from additive white Gaussian noise to any real-valued …