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Articles 931 - 960 of 4606

Full-Text Articles in Engineering

Demand Side Management Of Electric Vehicles In Smart Grids: A Survey On Strategies, Challenges, Modeling, And Optimization, Sarthak Mohanty, Subhasis Panda, Shubhranshu Mohan Parida, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Hossam Zawbaa, Nallapaneni Manoj Kumar, Salah Kamel Jan 2022

Demand Side Management Of Electric Vehicles In Smart Grids: A Survey On Strategies, Challenges, Modeling, And Optimization, Sarthak Mohanty, Subhasis Panda, Shubhranshu Mohan Parida, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Hossam Zawbaa, Nallapaneni Manoj Kumar, Salah Kamel

Articles

The shift of transportation technology from internal combustion engine (ICE) based vehicles to electricvehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater efficiency hasbrought EV technology to the forefront of the electric power distribution systems due to theirability to interact with the grid through vehicle-to-grid (V2G) infrastructure. The greater adoptionof EVs presents an ideal use-case scenario of EVs acting as power dispatch, storage, and ancillaryservice-providing units. This EV aspect can be utilized more in the current smart grid (SG) scenarioby incorporating demand-side management (DSM) through EV integration. The integration of EVswith DSM techniques is hurdled …

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Optimization Based On Movable Damped Wave Algorithm For Design Of Photovoltaic/ Wind/ Diesel/ Biomass/ Battery Hybrid Energy Systems, Mohammed Kharrich, Salah Kamel, Mamdouh Abdel-Akher, Ahmad Eid, Hossam Zawbaa, Jonghoon Kim Jan 2022

Optimization Based On Movable Damped Wave Algorithm For Design Of Photovoltaic/ Wind/ Diesel/ Biomass/ Battery Hybrid Energy Systems, Mohammed Kharrich, Salah Kamel, Mamdouh Abdel-Akher, Ahmad Eid, Hossam Zawbaa, Jonghoon Kim

Articles

The actual energetic situation has several challenges such as pollution, the rarefaction of fossil fuel and the dangers of nuclear. Renewable sources are proposed as a solution and suggested, such as a cost-effectiveness system. The paper deals with the problem of feeding a domestic load with electricity which should respect the ecologies factors, so this work is a design problem of the hybrid renewable energy systems; PV/biomass, PV/diesel/battery, PV/wind/diesel/battery, and wind/diesel/battery to choose the best one of them which feed the load with the lowest cost. The study’s goal is to design a microgrid system by the minimization of the …

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Overarching Preventive Sympathetic Tripping Approach In Active Distribution Networks Without Telecommunication Platforms And Additional Protective Devices, Tahereh Dehghani Firouzabadi, Davoud Abootorabi Zarchi, Mohammadreza Mazid, Hadi Safdarkhani, Hamed Nafisi Jan 2022

Overarching Preventive Sympathetic Tripping Approach In Active Distribution Networks Without Telecommunication Platforms And Additional Protective Devices, Tahereh Dehghani Firouzabadi, Davoud Abootorabi Zarchi, Mohammadreza Mazid, Hadi Safdarkhani, Hamed Nafisi

Articles

Nowadays, distributed generation (DG) has made it possible to generate electricity close to the consumption site, resulting in improved efficiency, less environmental pollution, and higher economic profit. These advantages have led to increased penetration of DGs in the distribution system. Protective devices in a distribution system are set by considering the main substation as the only source for feeding short circuit current. However, with the increased influence of DGs as the second main source of short circuit current in distribution systems the short circuit level changes, which leads to false tripping of protective devices, including overcurrent relays. A sympathetic trip, …

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Efficient Flatness Based Energy Management Strategy For Hybrid Supercapacitor/Lithium-Ion Battery Power System, Salam J. Yaqoob, Seydali Ferahtia, Adel Obed, Hegazy Rezk, Naseer Tawfeeq Alwan, Hossam Zawbaa, Salah Kamel Jan 2022

Efficient Flatness Based Energy Management Strategy For Hybrid Supercapacitor/Lithium-Ion Battery Power System, Salam J. Yaqoob, Seydali Ferahtia, Adel Obed, Hegazy Rezk, Naseer Tawfeeq Alwan, Hossam Zawbaa, Salah Kamel

Articles

This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher effciency and stable DC bus voltage. First, the entire system model is analyzed theoretically under the differential flatness approach to reduce the model order as a at system. Second, the proposed FEMS is validated under different load conditions using MATLAB/Simulink. Thus, this FEMS provides high-quality energy to the load and reduces the fluctuations in the …

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Poster: Acoustic Source Localization Using Straight Line Approximations, Swarnadeep Bagchi, Ruairí De Fréin Jan 2022

Poster: Acoustic Source Localization Using Straight Line Approximations, Swarnadeep Bagchi, Ruairí De Fréin

Conference papers

The short paper extends an acoustic signal delay estimation method to general anechoic scenario using image processing techniques. The technique proposed in this paper localizes acoustic speech sources by creating a matrix of phase versus frequency histograms, where the same phases are stacked in appropriate bins. With larger delays and multiple sources coexisting in the same matrix, it becomes cluttered with activated bins. This results in high intensity spots on the spectrogram, making source discrimination difficult. In this paper, we have employed morphological filtering, chain-coding and straight line approximations to ignore noise and enhance the target signal features. Lastly, Hough …

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Dual-Band Dual-Polarized Microstrip Array For Mm-Wave And Sub-6 Ghz Applications, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy Jan 2022

Dual-Band Dual-Polarized Microstrip Array For Mm-Wave And Sub-6 Ghz Applications, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy

Conference papers

In this paper, a compact dual-band and dual-polarized antenna array with integrated crossover for mm-Wave and sub-6 GHz band Wi-Fi applications is proposed. The proposed dual-band antenna is comprised of a 2x2 array operating at 26 GHz and 5.48 GHz (channel 96). The dual-band crossover consists of a microstrip-grounded CPW-microstrip interface transition. The measured design shows inter and intraband isolation better than 25dB with the crossover on the same plane with a maximum gain of 9.2dBi and 11.83 dBi for 26.25 GHz and 5.48 GHz respectively.

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Application Of Climate-Smart Forestry – Forest Manager Response To The Relevance Of European Definition And Indicators, Euan Bowditch, Giovanni Santopuoli, Boyżdar Neroj, Jan Svetlik Jan Svetlik, Mark Tominlson, Vivien Pohl, Admir Avdagić, Miren Del Rio, Tzetvan Zlatanov Tzetvan Zlatanov, Höhn Maria, Gabriela Jamnická, Yusuf Serengil, Murat Sarginci, Sigríður Júlía Brynleifsdóttir, Jerzy Lesinki, João C. Azevedo Jan 2022

Application Of Climate-Smart Forestry – Forest Manager Response To The Relevance Of European Definition And Indicators, Euan Bowditch, Giovanni Santopuoli, Boyżdar Neroj, Jan Svetlik Jan Svetlik, Mark Tominlson, Vivien Pohl, Admir Avdagić, Miren Del Rio, Tzetvan Zlatanov Tzetvan Zlatanov, Höhn Maria, Gabriela Jamnická, Yusuf Serengil, Murat Sarginci, Sigríður Júlía Brynleifsdóttir, Jerzy Lesinki, João C. Azevedo

Articles

Climate change impacts are an increasing threat to forests and current approaches to management. In 2020, Climate-smart Forestry (CSF) definition and set of indicators was published. This study further developed this work by testing the definition and indicators through a forest manager survey across fifteen member European countries. The survey covered topic areas of demographics, climate change impacts, definition and indicators assessment, as well as knowledge and communication. Overall, forest managers considered the threat of climate change to their forests as high or critical and 62% found the CSF definition clear and concise; however, the minority suggested greater simplification or …

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Data Driven Bayesian Network To Predict Critical Alarm, Joseph Mietkiewicz, Anders Madsen Jan 2022

Data Driven Bayesian Network To Predict Critical Alarm, Joseph Mietkiewicz, Anders Madsen

Articles

Modern industrial plants rely on alarm systems to ensure their safe and effective functioning. Alarms give the operator knowledge about the current state of the industrial plants. Trip alarms indicating a trip event indicate the shutdown of systems. Trip events in power plants can be costly and critical for the running of the operation.This paper demonstrates how trips events based on an alarm log from an offshore gas production can be reliably predicted using a Bayesian network. If a trip event is reliably predicted and the main cause of it is identified, it will allow the operator to prevent it. …

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Development Of Modular And Adaptive Laboratory Set-Up For Neuroergonomic And Human-Robot Interaction Research, Marija Savkovic, Carlo Caiazzo, Marko Djapan, Arso M. Vukic´ Evi, Milos Pusica, Ivan Macˇ Užic Jan 2022

Development Of Modular And Adaptive Laboratory Set-Up For Neuroergonomic And Human-Robot Interaction Research, Marija Savkovic, Carlo Caiazzo, Marko Djapan, Arso M. Vukic´ Evi, Milos Pusica, Ivan Macˇ Užic

Articles

The industry increasingly insists on academic cooperation to solve the identified problems such as workers' performance, wellbeing, job satisfaction, and injuries. It causes an unsafe and unpleasant working environment that directly impacts the quality of the product, workers' productivity, and effectiveness. This study aimed to give a specialized solution for tests and explore possible solutions to the given problem in neuroergonomics and human-robot interaction. The designed modular and adaptive laboratory model of the industrial assembly workstation represents the laboratory infrastructure for conducting advanced research in the field of ergonomics, neuroergonomics, and human-robot interaction. It meets the operator's anatomical, anthropometric, physiological, …

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Deep Residual Policy Reinforcement Learning As A Corrective Term In Process Control For Alarm Reduction: A Preliminary Report, Ammar N. Abbas, Georgios C. Chasparis, John Kelleher Jan 2022

Deep Residual Policy Reinforcement Learning As A Corrective Term In Process Control For Alarm Reduction: A Preliminary Report, Ammar N. Abbas, Georgios C. Chasparis, John Kelleher

Articles

Conventional process controllers (such as proportional integral derivative controllers and model predictive controllers) are simple and effective once they have been calibrated for a given system. However, it is difficult and costly to re-tune these controllers if the system deviates from its normal conditions and starts to deteriorate. Recently, reinforcement learning has shown a significant improvement in learning process control policies through direct interaction with a system, without the need of a process model or the system characteristics, as it learns the optimal control by interacting with the environment directly. However, developing such a black-box system is a challenge when …

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Ensemble Approach To The Semantic Segmentation Of Satellite Images, Brendan Kent Jan 2022

Ensemble Approach To The Semantic Segmentation Of Satellite Images, Brendan Kent

Dissertations

Automatic classification and segmentation of land use land cover(LULC) is extremely important for understanding the relationship between humans and nature. Human pressures on the environment have drastically accelerated in the last decades, risking biodiversity and ecosystem services. Remote sensing via satellite imagery is an excellent tool to study LULC. Research has shown that deep learning encoder-decoder architectures have achieved worthy results in the area of LULC, however the application of an ensemble approach has not been well quantified. Studies have shown it to be useful in the area of medical imaging. Ensembling by pooling together predictions to produce better predictions …

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An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous Jan 2022

An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous

Dissertations

Botnets pose a significant and growing risk to modern networks. Detection of botnets remains an important area of open research in order to prevent the proliferation of botnets and to mitigate the damage that can be caused by botnets that have already been established. Botnet detection can be broadly categorised into two main categories: signature-based detection and anomaly-based detection. This paper sets out to measure the accuracy, false-positive rate, and false-negative rate of four algorithms that are available in Weka for anomaly-based detection of a dataset of HTTP and IRC botnet data. The algorithms that were selected to detect botnets …

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Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen Jan 2022

Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen

Dissertations

Dark patterns are user interfaces purposefully designed to manipulate users into doing something they might not otherwise do for the benefit of an online service. This study investigates the impact of dark patterns on overall user experience and site revisitation in the context of airline websites. In order to assess potential dark pattern effects, two versions of the same airline website were compared: a dark version containing dark pattern elements and a bright version free of manipulative interfaces. User experience for both websites were assessed quantitatively through a survey containing a User Experience Questionnaire (UEQ) and a System Usability Scale …

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Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy Jan 2022

Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy

Dissertations

Deepfake classification has seen some impressive results lately, with the experimentation of various deep learning methodologies, researchers were able to design some state-of-the art techniques. This study attempts to use an existing technology “Transformers” in the field of Natural Language Processing (NLP) which has been a de-facto standard in text processing for the purposes of Computer Vision. Transformers use a mechanism called “self-attention”, which is different from CNN and LSTM. This study uses a novel technique that considers images as 16x16 words (Dosovitskiy et al., 2021) to train a deep neural network with “self-attention” blocks to detect deepfakes. It creates …

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An Investigation Of The Relationship Between Subjective Mental Workload And Objective Indicators Of User Activity, Greg Byrne Jan 2022

An Investigation Of The Relationship Between Subjective Mental Workload And Objective Indicators Of User Activity, Greg Byrne

Dissertations

Whilst the concept of physical workload is intuitively understood and readily applicable in system design, the same cannot be said of mental workload (MWL), despite its importance in our increasingly technological society. Despite its origin in the mid 20th century, the very concept of ”mental workload” is still a topic of debate in the literature, although it can be loosely defined as “the amount of mental work necessary for a person to complete a task” (Miller, 1956; Longo, 2014). Several methods have been utilized to measure of MWL, including physiological methods such as neuro-imagery, performance-based metrics, and subjective measures via …

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Direct And Constructivist Approaches For The Design Of Instruction In Well-Structured Domains: A Comparison Of Efficiency Via Mental Workload And Performance., Giuliano Orru Jan 2022

Direct And Constructivist Approaches For The Design Of Instruction In Well-Structured Domains: A Comparison Of Efficiency Via Mental Workload And Performance., Giuliano Orru

Dissertations

This doctoral research investigates the efficiency of two instructional designs: a design based on the direct-instruction approach to learning and its extension with a collaborative activity based upon the community of inquiry approach to learning. This is motivated by the educational challenge associated with the improvement of the learning phase. The goal is to investigate the extent to which highly guided communities of inquiry, when added to direct-instruction teaching methods, can actually improve the efficiency of learners. A total of 577 students participated in the experiments across 24 third-level classes that were divided into two groups. A control group of …

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Kg-Cnn: Augmenting Convolutional Neural Networks With Knowledge Graphs For Multi-Class Image Classification, Aidan O'Neill Jan 2022

Kg-Cnn: Augmenting Convolutional Neural Networks With Knowledge Graphs For Multi-Class Image Classification, Aidan O'Neill

Dissertations

Computer vision is slowly becoming more and more prevalent in daily life. Tesla has recently announced that it plans to scale up the manufacturing of their Robotaxis by 2024, with this increase in self-driving vehicles being just one example, the importance of computer vision is growing year by year. Vision can be easy to take for granted, as most humans grow up using vision as their primary way of absorbing environmental information. The way humans process and classify visual information differs significantly from how current computer vision systems process and organise visual information. The human brain can use its past …

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The Impact Of Emotion Focused Features On Svm And Mlr Models For Depression Detection, Alexandria Mulligan Jan 2022

The Impact Of Emotion Focused Features On Svm And Mlr Models For Depression Detection, Alexandria Mulligan

Dissertations

Major depressive disorder (MDD) is a common mental health diagnosis with estimates upwards of 25% of the United States population remain undiagnosed. Psychomotor symptoms of MDD impacts speed of control of the vocal tract, glottal source features and the rhythm of speech. Speech enables people to perceive the emotion of the speaker and MDD decreases the mood magnitudes expressed by an individual. This study asks the questions: “if high level features deigned to combine acoustic features related to emotion detection are added to glottal source features and mean response time in support vector machines and multivariate logistic regression models, would …

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Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern Jan 2022

Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern

Dissertations

Hate speech can be defined as forms of expression that incite hatred or encourage violence towards a person or group based on race, religion, gender, or sexual orientation. Hate speech has gravitated towards social media as its primary platform, and its propagation represents profound risks to both the mental well-being and physical safety of targeted groups. Countermeasures to moderate hate speech face challenges due to the volumes of data generated in social media, leading companies, and the research community to evaluate methods to automate its detection. The emergence of BERT and other pre-trained transformer-based models for transfer learning in the …

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Performance Evaluation Of An Edge Computing Implementation Of Hyperledger Sawtooth For Iot Data Security, Sean Connolly Jan 2022

Performance Evaluation Of An Edge Computing Implementation Of Hyperledger Sawtooth For Iot Data Security, Sean Connolly

Dissertations

Blockchain offers a potential solution to some of the security challenges faced by the internet-of-things (IoT) by using its practically immutable ledger to store data transactions. However, past applications of blockchain in IoT encountered limitations in the rate at which transactions were committed to the chain as new blocks. These limitations were often the result of the time-consuming and computationally expensive consensus mechanisms found in public blockchains. Hyperledger Sawtooth is an open-source private blockchain platform that offers an efficient proof-of-elapsed-time (PoET) consensus mechanism. Sawtooth has performed well in benchmarks against other blockchains. However, a performance evaluation for a practical application …

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Examining The Effects Of Disabilities On Vr Usage And Accessibility Issues For Persons With Disabilities, Sean Williams Jan 2022

Examining The Effects Of Disabilities On Vr Usage And Accessibility Issues For Persons With Disabilities, Sean Williams

Dissertations

Virtual Reality (VR) is an emerging technology that’s popularity has been increasing at a yearly rate. Despite this, concerns about the accessibility of VR devices are ever-growing as many users struggle to use the technology, especially users with disabilities. This study analyses how different types of disabilities affect how often a user uses VR and any associated re-occurring difficulties that are related to specific types of disability. To do this, a previous survey regarding VR accessibility run by Disability Visibility Project and ILMxLAB is examined. In this survey, 79 participants who identify as having a disability answered questions related to …

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On The Dimensionality And Utility Of Convolutional Autoencoder’S Latent Space Trained With Topology-Preserving Spectral Eeg Head-Maps, Arjun Vinayak Chikkankod, Luca Longo Jan 2022

On The Dimensionality And Utility Of Convolutional Autoencoder’S Latent Space Trained With Topology-Preserving Spectral Eeg Head-Maps, Arjun Vinayak Chikkankod, Luca Longo

Articles

Electroencephalography (EEG) signals can be analyzed in the temporal, spatial, or frequency domains. Noise and artifacts during the data acquisition phase contaminate these signals adding difficulties in their analysis. Techniques such as Independent Component Analysis (ICA) require human intervention to remove noise and artifacts. Autoencoders have automatized artifact detection and removal by representing inputs in a lower dimensional latent space. However, little research is devoted to understanding the minimum dimension of such latent space that allows meaningful input reconstruction. Person-specific convolutional autoencoders are designed by manipulating the size of their latent space. A sliding window technique with overlapping is employed …

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Investigation Of The Combustion Of Exhaust Gas Recirculation In Diesel Engines With A Particulate Filter And Selective Catalytic Reactor Technologies For Environmental Gas Reduction, Megavath Vijay Kumar, Alur Veeresh Babu, Ch. Rami Reddy, A. Pandian, Mohit Bajaj, Hossam Zawbaa, Salah Kamel Jan 2022

Investigation Of The Combustion Of Exhaust Gas Recirculation In Diesel Engines With A Particulate Filter And Selective Catalytic Reactor Technologies For Environmental Gas Reduction, Megavath Vijay Kumar, Alur Veeresh Babu, Ch. Rami Reddy, A. Pandian, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

The Diesel Engine, invented by the German engineer Rudolf Diesel, was a marvelous creation that changed the way the automobile industry worked. It is an internal combustion engine that compresses air to elevate its pressure and temperature so high that the atomized diesel fuel undergoes combustion almost instantaneously when it is sprayed into the combustion chamber. The Major advantage of a Compression Ignition (CI) engine compared to a Spark Ignition (SI) engine is the higher compression ratio achieved in the former, making it more efficient. This makes diesel engines more suitable for heavy-duty vehicles, which require more torque to overcome …

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Modeling Cognitive Load As A Self-Supervised Brain Rate With Electroencephalography And Deep Learning, Luca Longo Jan 2022

Modeling Cognitive Load As A Self-Supervised Brain Rate With Electroencephalography And Deep Learning, Luca Longo

Articles

The principal reason for measuring mental workload is to quantify the cognitive cost of performing tasks to predict human performance. Unfortunately, a method for assessing mental workload that has general applicability does not exist yet. This is due to the abundance of intuitions and several operational definitions from various fields that disagree about the sources or workload, its attributes, the mechanisms to aggregate these into a general model and their impact on human performance. This research built upon these issues and presents a novel method for mental workload modelling from EEG data employing deep learning. This method is self-supervised, employing …

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Examining The Size Of The Latent Space Of Convolutional Variational Autoencoders Trained With Spectral Topographic Maps Of Eeg Frequency Bands, Taufique Ahmed, Luca Longo Jan 2022

Examining The Size Of The Latent Space Of Convolutional Variational Autoencoders Trained With Spectral Topographic Maps Of Eeg Frequency Bands, Taufique Ahmed, Luca Longo

Articles

Electroencephalography (EEG) is a technique of recording brain electrical potentials using electrodes placed on the scalp [1]. It is well known that EEG signals contain essential information in the frequency, temporal and spatial domains. For example, some studies have converted EEG signals into topographic power head maps to preserve spatial information [2]. Others have produced spectral topographic head maps of different EEG bands to both preserve information in The associate editor coordinating the review of this manuscript and approving it for publication was Ludovico Minati . the spatial domain and take advantage of the information in the frequency domain [3]. …

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Introduction To The Special Issue On Gala Conf 2021, Francesca De Rosa, Jannicke Baalsrud Hauge, Pierpaolo Dondio, Isa Marfizi-Schottman, Margarida Romero, Francesco Bellotti Jan 2022

Introduction To The Special Issue On Gala Conf 2021, Francesca De Rosa, Jannicke Baalsrud Hauge, Pierpaolo Dondio, Isa Marfizi-Schottman, Margarida Romero, Francesco Bellotti

Articles

This special issue of the International Journal of Serious Games is dedicated to the selected best papers of the 2021 edition of the GALA conference. This edition was organized by Francesca De Rosa and her team at NATO Centre for Maritime Research and Experimen-tation (CMRE), La Spezia, Italy. Because of the Covid-19 pandemic, it was held online, for the second year. The three papers published in this special issue were first selected for a content exten-sion, so to make them suitable as journal papers, then underwent the regular IJSG peer-review process, which, on the other hand, discarded other three selected …

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Power Management In Hybrid Anfis Pid Based Ac–Dc Microgrids With Eho Based Cost Optimized Droop Control Strategy, T. Narasimha Prasad, S. Devakirubakaran, S. Muthubalaji, S. Srinivasan, B. Karthikeyan, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel Jan 2022

Power Management In Hybrid Anfis Pid Based Ac–Dc Microgrids With Eho Based Cost Optimized Droop Control Strategy, T. Narasimha Prasad, S. Devakirubakaran, S. Muthubalaji, S. Srinivasan, B. Karthikeyan, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

One of the most critical operations aspects is power management strategies for hybrid AC/DC microgrids. This work presented power management in hybrid AC–DC microgrids with a droop control strategy. At first, photovoltaic, Wind, and battery are used as the power sources, which supply the power with uncertainties. The AC and DC microgrids are controlled by an Adaptive neuro-fuzzy inference system (ANFIS) controller and Proportional Integral Derivative (PID) controller. Simultaneously we calculate the running cost for photovoltaic, Wind, and Battery. Moreover, an optimizer based on the elephant herding optimization algorithm is formulated to reduce the cost price. This method utilizes two …

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The Association Between Ambient Uvb Dose And Anca‑Associated Vasculitis Relapse And Onset, Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos Van Geffen, Michiel Van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John Kelleher, Julie Power, James Ng, Declan O’Sullivan, Lucy Hederman, Neil Basu, Mark A. Little, Lina Zgaga Jan 2022

The Association Between Ambient Uvb Dose And Anca‑Associated Vasculitis Relapse And Onset, Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos Van Geffen, Michiel Van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John Kelleher, Julie Power, James Ng, Declan O’Sullivan, Lucy Hederman, Neil Basu, Mark A. Little, Lina Zgaga

Articles

The aetiology of ANCA-associated vasculitis (AAV) and triggers of relapse are poorly understood. Vitamin D (vitD) is an important immunomodulator, potentially responsible for the observed latitudinal differences between granulomatous and non-granulomatous AAV phenotypes. A narrow ultraviolet B spectrum induces vitD synthesis (vitD-UVB) via the skin. We hypothesised that prolonged periods of low ambient UVB (and by extension vitD deficiency) are associated with the granulomatous form of the disease and an increased risk of AAV relapse.

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Development Of An Explainability Scale To Evaluate Explainable Artificial Intelligence (Xai) Methods, Stephen Mccarthy Jan 2022

Development Of An Explainability Scale To Evaluate Explainable Artificial Intelligence (Xai) Methods, Stephen Mccarthy

Dissertations

Explainable Artificial Intelligence (XAI) is an area of research that develops methods and techniques to make the results of artificial intelligence understood by humans. In recent years, there has been an increased demand for XAI methods to be developed due to model architectures getting more complicated and government regulations requiring transparency in machine learning models. With this increased demand has come an increased need for instruments to evaluate XAI methods. However, there are few, if none, valid and reliable instruments that take into account human opinion and cover all aspects of explainability. Therefore, this study developed an objective, human-centred questionnaire …

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An Investigation Of The Relationship Between Subjective Mental Workload And Objective Indicators Of User Activity, Greg Byrne Jan 2022

An Investigation Of The Relationship Between Subjective Mental Workload And Objective Indicators Of User Activity, Greg Byrne

Dissertations

Whilst the concept of physical workload is intuitively understood and readily applicable in system design, the same cannot be said of mental workload (MWL), despite its importance in our increasingly technological society. Despite its origin in the mid 20th century, the very concept of ”mental workload” is still a topic of debate in the literature, although it can be loosely defined as “the amount of mental work necessary for a person to complete a task” (Miller, 1956; Longo, 2014). Several methods have been utilized to measure of MWL, including physiological methods such as neuro-imagery, performance-based metrics, and subjective measures via …

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