Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis,
2023
Technological University Dublin
Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis, Katryna Cisek
Articles
Background. There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor. Chronic stroke management encompasses rehabilitation and reintegration, and can require decades of personalized medicine and care. Information technology (IT) tools have the potential to support individuals managing chronic stroke symptoms. Objectives. This scoping review identifies prevalent topics and concepts in research literature on IT technology for stroke rehabilitation and reintegration, utilizing content analysis, based on topic modelling techniques from natural language processing to identify gaps in this literature. Eligibility Criteria. Our methodological search initially identified over 14,000 …
Know An Emotion By The Company It Keeps: Word Embeddings From Reddit/Coronavirus,
2023
Institut Guttmann, Institut Universitari de Neurorehabilitació Adscrit a la UAB, Badalona, Spain
Know An Emotion By The Company It Keeps: Word Embeddings From Reddit/Coronavirus, Alejandro García-Rudolph, David Sanchez-Pinsach, Dietmar Frey, Eloy Opisso, Katryna Cisek, John Kelleher
Articles
Social media is a crucial communication tool (e.g., with 430 million monthly active users in online forums such as Reddit), being an objective of Natural Language Processing (NLP) techniques. One of them (word embeddings) is based on the quotation, “You shall know a word by the company it keeps,” highlighting the importance of context in NLP. Meanwhile, “Context is everything in Emotion Research.” Therefore, we aimed to train a model (W2V) for generating word associations (also known as embeddings) using a popular Coronavirus Reddit forum, validate them using public evidence and apply them to the discovery of context for specific …
A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions,
2023
Marshall University
A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions, Peter Estephan
Theses, Dissertations and Capstones
This thesis presents a path planning framework for a very-large-scale robotic (VLSR) system in an known obstacle environment, where the time-varying distributions of agents are applied to represent the multi-agent robotic system (MARS). A novel family of the multivariate skew-normal (MVSN) distributions is proposed based on the Bernoulli random field (BRF) referred to as the Bernoulli-random-field based skew-normal (BRF-SN) distribution. The proposed distributions are applied to model the agents’ distributions in an obstacle-deployed environment, where the obstacle effect is represented by a skew function and separated from the no-obstacle agents’ distributions. First, the obstacle layout is represented by a Hilbert …
Encryption And Compression Classification Of Internet Of Things Traffic,
2023
Wright State University
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
Browse all Theses and Dissertations
The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …
Efficient Cloud-Based Ml-Approach For Safe Smart Cities,
2023
Wright State University
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
Browse all Theses and Dissertations
Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …
Contributors To Pathologic Depolarization In Myotonia Congenita,
2023
Wright State University
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
Browse all Theses and Dissertations
Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …
The Effects Of Disinformation Upon National Attitudes Towards The Eu And Its Institutions,
2023
Technological University Dublin, Ireland
The Effects Of Disinformation Upon National Attitudes Towards The Eu And Its Institutions, Alex Murphy
Dissertations
This work explores the effects of misinformation and disinformation upon national attitudes towards the EU. Several nations, in particular the Russian Federation, have been working for decades to spread narratives that debase the political processes of healthy democracies around the world. There is strong evidence to show that extensive efforts have been made to disrupt the inner workings and overall membership of the EU, to support disruptive policies in the United States such that political deadlock is maintained indefinitely. These efforts are largely based on the spreading of misinformation and disinformation across social networks that have done very little to …
Development Of A Hospital Discharge Planning System Augmented With A Neural Clinical Decision Support Engine,
2023
Technological University Dublin, Ireland
Development Of A Hospital Discharge Planning System Augmented With A Neural Clinical Decision Support Engine, David Mulqueen
Dissertations
The process of discharging patients from a tertiary care hospital, is one of the key activities to ensure the efficient and effective operation of a hospital. However, the decision to discharge a patient from a hospital is complex, as it requires multiple interactions with nurses, family, consultants, health information records and doctors, which can be very time consuming and prone to error. This thesis descries how a neural network based Clinical Decision Support system can be developed, to help in the decision making process and dramatically reduce the time and effort in running the discharge process in a hospital. A …
Forecasting Covid-19 Cases Using Dynamic Time Warping And Incremental Machine Learning Methods,
2023
Technological University Dublin, Ireland
Forecasting Covid-19 Cases Using Dynamic Time Warping And Incremental Machine Learning Methods, Luis Miralles-Pechuán, Ankit Kumar, Andres L. Suarez-Cetrulo
Articles
The investment of time and resources for developing better strategies is key to dealing with future pandemics. In this work, we recreated the situation of COVID-19 across the year 2020, when the pandemic started spreading worldwide. We conducted experiments to predict the coronavirus cases for the 50 countries with the most cases during 2020. We compared the performance of state-of-the-art machine learning algorithms, such as long-short-term memory networks, against that of online incremental machine learning algorithms. To find the best strategy, we performed experiments to test three different approaches. In the first approach (single-country), we trained each model using data …
Artificial Emotional Intelligence In Socially Assistive Robots,
2023
University of Denver
Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi
Electronic Theses and Dissertations
Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …
Understanding And Quantifying Human Factors In Programming From Demonstration: A User Study Proposal,
2023
Technological University Dublin, Ireland
Understanding And Quantifying Human Factors In Programming From Demonstration: A User Study Proposal, Shakra Mehak, Aayush Jain, John D. Kelleher, Philip Long, Michael Guilfoyle, Maria Chiara Leva
Conference papers
Programming by demonstration (PbD) is a promising method for robots to learn from direct, non-expert human interaction. This approach enables the interactive transfer of human skills to the robot. As the non-expert user is at the center of PbD, the efficacy of the learned skill is largely dependent on the demonstrations provided. Although PbD methods have been extensively developed and validated in the field of robotics, there has been inadequate confirmation of their effectiveness from the perspective of human teachability. To address this gap, we propose to experimentally investigate the impact of communicating robot learning process on the efficacy of …
Solidity Compiler Version Identification On Smart Contract Bytecode,
2023
Wright State University
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Browse all Theses and Dissertations
Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform,
2023
Wright State University
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii
Browse all Theses and Dissertations
The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique,
2023
Wright State University
A Secure And Efficient Iiot Anomaly Detection Approach Using A Hybrid Deep Learning Technique, Bharath Reedy Konatham
Browse all Theses and Dissertations
The Industrial Internet of Things (IIoT) refers to a set of smart devices, i.e., actuators, detectors, smart sensors, and autonomous systems connected throughout the Internet to help achieve the purpose of various industrial applications. Unfortunately, IIoT applications are increasingly integrated into insecure physical environments leading to greater exposure to new cyber and physical system attacks. In the current IIoT security realm, effective anomaly detection is crucial for ensuring the integrity and reliability of critical infrastructure. Traditional security solutions may not apply to IIoT due to new dimensions, including extreme energy constraints in IIoT devices. Deep learning (DL) techniques like Convolutional …
Sgs: Mutant Reduction For Higher-Order Mutation-Based Fault Localization,
2023
Beijing University of Chemical Technology, China
Sgs: Mutant Reduction For Higher-Order Mutation-Based Fault Localization, Luxi Fan, Zheng Li, Hengyuan Liu, Paul Doyle, Haifeng Wang, Xiang Chen, Yong Liu
Conference Papers
MBFL (Mutation-Based Fault Localization) is one of the most commonly studied fault localization techniques due to its promising fault localization effectiveness. However, MBFL incurs a high execution cost as it needs to execute the test suite on a large number of mutants. While previous studies have proposed mutant reduction methods for FOMs (First-Order Mutants) to help alleviate the cost of MBFL, the reduction of HOMs (Higher-Order Mutants) has not been thoroughly investigated. In this study, we propose SGS (Statement Granularity Sampling), a method which conducts HOMs reduction for HMBFL (Higher-Order Mutation-Based Fault Localization). Considering the relationship between HOMs and statements, …
Scheduling Electric Vehicle Charging For Grid Load Balancing,
2023
Western University
Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir
Electrical and Computer Engineering Publications
In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …
Handheld Concentric Tube Robot For Percutaneous Nephrolithotomy,
2023
Western University
Handheld Concentric Tube Robot For Percutaneous Nephrolithotomy, Filipe Pedrosa, Ruisi Zhang, Navid Feizi, Dianne Sacco, Rajni V. Patel, Jagadeesan Jayender
Electrical and Computer Engineering Publications
The field of continuum robotics continues to advance rapidly, giving these manipulators potential to change the paradigm of minimally invasive medical surgery (MIS) in a near future. As MIS techniques are refined to improve recovery and cosmesis and reduce invasiveness and co-morbidity, continuum robot requirements in MIS applications have become ever stricter. One such application is Percutaneous Nephrolithotomy (PCNL), a first-choice minimally invasive urological procedure for the extraction of large renal calculi (kidney stones) > 2 cm. The standard of care in PCNL entails the percutaneous insertion of a nephroscope via a small incision in the lumbar or lateral abdominal wall …
Design And Calibration Of A Robot-Driven Catheter Actuation System,
2023
Western University
Design And Calibration Of A Robot-Driven Catheter Actuation System, Navid Feizi, Filipe C. Pedrosa, Elaheh Arefinia, Jagadeesan Jayender, Rajni V. Patel
Electrical and Computer Engineering Publications
Flexible steerable tendon-driven systems are crucial in medical interventions, due to their ease of access to narrow spaces and safe operation [1]. Two examples of these systems are ablation and intra-cardiac echocardiog- raphy (ICE) catheters, used for non-invasive ultrasound imaging and ablation in cardiac procedures inside the heart. However, precise positioning of these devices to obtain optimal anatomical views is challenging for the cardiologist and requires specialized training [2]. Custom-made tendon-driven robots have been developed and modeled using Cosserat rod theory [3], [4]. How- ever, most of these efforts have been directed towards creating new flexible robots with known parameters …
Identifying Hazardous Patterns In Msha Data Using Random Forests,
2023
Marshall University
Identifying Hazardous Patterns In Msha Data Using Random Forests, Olivia Milam
Theses, Dissertations and Capstones
Mining safety and health in the US can be better understood through the application of machine learning techniques to data collected by the Mine Safety and Health Administration (MSHA). By identifying hazardous conditions that could lead to accidents before they occur, valuable insights can be gained by MSHA, mining operators, and miners. In this study, we propose using a Random Forest machine learning model to predict whether a given mining violation will lead to an accident, and if so, whether it will be fatal or non-fatal. To achieve this, the model is trained on MSHA violation data and the sum …
Responsible Robots And Ai Via Moral Conditioning,
2023
University of the Pacific
Responsible Robots And Ai Via Moral Conditioning, Omhier Khan, Mark Alberta, Dongbin Lee
All Faculty Articles - School of Engineering and Computer Science
This paper examines not only the main unresolved theoretical question, centered on the responsibility gap issue in autonomous robots, but also examines whether the robot can be responsible via moral conditioning and our proposed method bumper theory. Our scientific inquiry aims to discuss what is required to meet the goals and objectives of moral robotics, as well as promote dialogues and acquire quantitative results that hope to make robots responsible moral agents. Robots are morally conditioned with bumper theory by first detecting human-beings, dogs, or cars to avoid collision and reinforce prosocial morality. We adopted a scientific method such as …
