The Need For Energy Storage On Renewable Energy Generator Outputs To Lessen The Geeth Effect, I.E. Short-Term Variations Mainly Associated With Wind Turbine Active Power Output,
2023
Technological University Dublin
The Need For Energy Storage On Renewable Energy Generator Outputs To Lessen The Geeth Effect, I.E. Short-Term Variations Mainly Associated With Wind Turbine Active Power Output, Tony Kealy
Articles
Many studies investigating the short-term variations associated with the power output from wind turbine generators utilise simulated or modelled data in the analysis. This current study uses short-term empirical data downloaded directly from operational wind turbines via electrical power quality meters. The empirical data shows that the short-term variations (one-second or sub-one-second timeframe) occur continuously over most of the power output range. A novel name is proposed, the Geeth Effect, for this variability phenomenon. The Geeth Effect is measured using the coefficient of variation mathematical expression and is likely contributing to (i) lower-than-expected financial and environmental benefits associated with …
Editorial,
2023
School of Information Technology, Illinois State University (ISU), Normal, IL.
Editorial, Sameeh Ullah Dr.
International Journal of Smart Sensor and Adhoc Network
This special issue seeks papers that provide a convergent research perspective on business futures, i.e., research that draws on many disciplinary views and strives to establish fresh integrative frameworks and vocabularies. Addressing the difficulty of work culture and intelligent machines in a broad sense necessitates grappling with complicated issues such as motivation, cognition, machine learning, human learning, and system design, among others.
Aircraft Communication Systems - Topologies, Protocols, And Vulnerabilities,
2023
University of North Dakota
Aircraft Communication Systems - Topologies, Protocols, And Vulnerabilities, Tyler Przybylski, Niroop Sugunaraj, Prakash Ranganathan
Electrical Engineering Student Publications
Aviation systems are facing fierce competition driven by private investments promoting the development of new avionics suites (AS). With these new AS comes the need for a faster and larger bandwidth requirement for next generation communication systems. The legacy military (MIL) standard 1553 communication system (e.g., 1Mbps) can no longer keep up with the surge in bandwidth demand requirements. The new communication systems need to be designed with a system architecture background that can enable simplistic integration with Information Technology (IT) controlled groundnetworks, military, and commercial payloads. To facilitate a seamless integration with communication architecture, the current system is highly …
Extended Version Of Stability Of A Groucho-Style Bounding Run In The Sagittal Plane,
2023
University of Pennsylvania
Extended Version Of Stability Of A Groucho-Style Bounding Run In The Sagittal Plane, Jeff Duperret, D. E. Koditschek
Technical Reports (ESE)
This paper develops a three degree-of-freedom sagittal-plane hybrid dynamical systems model of a Groucho-style bounding quadrupedal run. Simple within-stance controls using a modular architecture yield a closed form expression for a family of hybrid limit cycles that represent bounding behavior over a range of user-selected fore-aft speeds as a function of the model's kinematic and dynamical parameters. Controls acting on the hybrid transitions are structured so as to achieve a cascade composition of in-place bounding driving the fore-aft degree of freedom, thereby decoupling the linearized dynamics of an approximation to the stride map. Careful selection of the feedback channels used …
Introduction To Control Engineering,
2023
Louisiana State University at Baton Rouge
Introduction To Control Engineering, Xiangyu Meng
E-Textbooks
This is an introductory level textbook for control engineering.
State Of The Art In Drivers’ Attention Monitoring – A Systematic Literature Review,
2023
Department of Telecommunications University POLITEHNICA of Bucharest, Romania
State Of The Art In Drivers’ Attention Monitoring – A Systematic Literature Review, Sama Hussein Al-Gburi, Kanar Alaa Al-Sammak, Ion Marghescu, Claudia Cristina Oprea
Karbala International Journal of Modern Science
Recently, driver inattention has become the leading cause of automobile accidents. As a result, the driver's perception and decision-making abilities are diminished, and the driver can lose control of the car. To prevent accidents caused by driver inattention, it’s vital to continuously monitor the driver and his driving behaviour and inform him if he becomes distracted or sleepy. This topic has been the subject of study for decades. Whenever feasible to recognise unsafe driving in advance, accidents could be avoided. This document presents an overview of the existing driver alertness system and the various techniques for detecting driver attentiveness.
Influence Of Synthesis Conditions On The Physicochemical And Electrocatalytic Properties Of Non-Stoichiometric Ba2sr2la2ti4o12 Perovskites,
2023
Institute of Electrochemistry and Energy Systems Acad. Evgeni Budevski, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl 10, 1113 Sofia, Bulgaria
Influence Of Synthesis Conditions On The Physicochemical And Electrocatalytic Properties Of Non-Stoichiometric Ba2sr2la2ti4o12 Perovskites, Ofeliya Kostadinova, Iliyan Popov, Simeon M. Stankov, Hristo Kolev, Tamara Petkov
Karbala International Journal of Modern Science
Present work studies the influence of the pretreatment milling media (deionized water (BLTOS-H) and isopropanol (BLTOS-i)) on the surface characteristics, structure, chemical composition and catalytic activity of non-stoichiometric Ba2Sr2La2Ti4O12 perovskites. The IR spectroscopy and XRD analyses shows a difference in the structure and phase composition of the two materials. X-ray photoelectron spectroscopy detects a Ba2+- and La3+-enriched and Sr2+-depleted surface. The BLTOS-i sample appears to exhibit higher specific surface area (SSA) and pore volume in comparison to BLTOS-H. The electrochemical tests showed that BLTOS-H sample have similar behavior to platinum at current densi-ties up to 10 mA cm-2, while BLTOS-i …
Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators,
2023
Rowan University
Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi
Theses and Dissertations
Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …
Lesker Pvd75 E-Beam/Thermal Evaporator (Pvd-02) Standard Operating Procedure,
2023
University of Pennsylvania
Lesker Pvd75 E-Beam/Thermal Evaporator (Pvd-02) Standard Operating Procedure, David S. Barth, Jason A. Röhr
Standard Operating Procedures
Standard Operating Procedure for the Lesker PVD75 E-beam/Thermal Evaporator (PVD-02) located at the Quattrone Nanofabrication Facility within the Singh Center for Nanotechnology at the University of Pennsylvania
Running Shoe Pedometer,
2023
The University of Akron
Running Shoe Pedometer, Benjamin Kasper
Williams Honors College, Honors Research Projects
Running shoe pedometer aims to solve the issue of worn out running shoes. It can be difficult to know just how many miles you have run in your shoes and when a new pair is needed. Running in old shoes and worn out shoes is heavily linked to injury. My proposed project is a device that is powered by the compressive forces on the shoes soles that counts the number of steps the wearer takes using a microcontroller. Then, when the shoe reaches milestone that indicate it has been used 75% 90% and 100% of its expected life, it will …
An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density,
2023
Dartmouth College
An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density, Joachim Lohn-Jaramillo
Dartmouth College Ph.D Dissertations
Multiple-Object Tracking (MOT) methods are used to detect targets in individual video frames, e.g., vehicles, people, and other objects, and then record each unique target’s path over time. Current state-of-the-art approaches are extremely complex because most rely on extracting and comparing visual features at every frame to track each object. These approaches are geared toward high-difficulty-tracking scenarios, e.g., crowded airports, and require expensive dedicated hardware, e.g., Graphics Processing Units. In hardware-constrained applications, researchers are turning to older, less complex MOT methods, which reveals a serious scalability issue within the state-of-the-art. Crowded environments are a niche application for MOT, i.e., there …
Topologically Optimized Electrodes For Electroosmotic Actuation,
2023
Old Dominion University
Topologically Optimized Electrodes For Electroosmotic Actuation, Jianwen Sun, Jianyu Zhang, Ce Guan, Teng Zhou, Shizhi Qian, Yongbo Deng
Mechanical & Aerospace Engineering Faculty Publications
Electroosmosis is one of the most used actuation mechanisms for the microfluidics in the current active lab-on-chip devices. It is generated on the induced charged microchannel walls in contact with an electrolyte solution. Electrode distribution plays the key role on providing the external electric field for electroosmosis, and determines the performance of electroosmotic microfluidics. Therefore, this paper proposes a topology optimization approach for the electrodes of electroosmotic microfluidics, where the electrode layout on the microchannel wall can be determined to achieve designer desired microfluidic performance. This topology optimization is carried out by implementing the interpolation of electric insulation and electric …
Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance,
2023
University of South Carolina - Columbia
Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth
Publications
Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge (Pro-Know). In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively (ProKnow-algo). We demonstrate the …
Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance For Telehealth: The Mental Health Case,
2023
University of South Carolina - Columbia
Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance For Telehealth: The Mental Health Case, Kaushik Roy, Vedant Khandelwal, Raxit Goswami, Nathan Dolbir, Jinendra Malekar, Amit Sheth
Publications
After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed …
Ierl: Interpretable Ensemble Representation Learning - Combining Crowdsourced Knowledge And Distributed Semantic Representations,
2023
University of South Carolina - Columbia
Ierl: Interpretable Ensemble Representation Learning - Combining Crowdsourced Knowledge And Distributed Semantic Representations, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit Sheth
Publications
Large Language Models (LLMs) encode meanings of words in the form of distributed semantics. Distributed semantics capture common statistical patterns among language tokens (words, phrases, and sentences) from large amounts of data. LLMs perform exceedingly well across General Language Understanding Evaluation (GLUE) tasks designed to test a model’s understanding of the meanings of the input tokens. However, recent studies have shown that LLMs tend to generate unintended, inconsistent, or wrong texts as outputs when processing inputs that were seen rarely during training, or inputs that are associated with diverse contexts (e.g., well-known hallucination phenomenon in language generation tasks). Crowdsourced and …
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback,
2023
Argonne National Laboratory
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Publications
In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …
Data-Integrity Aware Stochastic Model For Cascading Failures In Power Grids,
2023
Marquette University
Data-Integrity Aware Stochastic Model For Cascading Failures In Power Grids, Rezoan Ahmed Shuvro, Pankaz Das, Jamir Shariar Jyoti, Joana Abreu, Majeed M. Hayat
Electrical and Computer Engineering Faculty Research and Publications
The reliable operation of power grids during cascading failures is heavily dependent on the interdependencies between the power grid components and the supporting communications and control networks. Moreover, the system operators' expertise in dealing with cascading failures can play a pivotal role during contingencies. In this paper, a dynamical probabilistic model is developed based on Markov-chains, which captures the dynamics of cascading failures in the power grid. Specifically, a previously developed Markov-chain based model is extended to capture the trade-off between the benefits of having a robust communication infrastructure and its vulnerability from data integrity (e.g., cyber-attacks). State-space reduction of …
Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits,
2023
TÜBİTAK
Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu
Turkish Journal of Electrical Engineering and Computer Sciences
This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …
An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization,
2023
TÜBİTAK
An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang
Turkish Journal of Electrical Engineering and Computer Sciences
In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …
A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19,
2023
TÜBİTAK
A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …