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Articles 31 - 60 of 1012
Full-Text Articles in Engineering
Exploring The Impact Of Competition And Incentives On Game Jam Participation And Behaviour, John Healy, Niamh Germaine
Exploring The Impact Of Competition And Incentives On Game Jam Participation And Behaviour, John Healy, Niamh Germaine
Conference papers
Competitive elements are a common feature of many game jams. However, there has been little research to date on the impact of competition on participants and their behaviours. To better understand how incentives and competition may affect the motivations and behaviour of game jam participants, we surveyed 47 game jam participants and analysed data from 4,564 online game jams. We found that incentives and competition were neither strong deterrents nor significant motivators for game jam participation. However, a significant percentage of the participants surveyed indicated that incentives and competition would affect their behaviour during a game jam. Our findings suggest …
Graph-Based Mutations For Music Generation, Maziar Kanani, Sean O'Leary, James Mcdermott
Graph-Based Mutations For Music Generation, Maziar Kanani, Sean O'Leary, James Mcdermott
Conference papers
Our study aims to compare the effects of direct mutation and graphbased mutation on representations of music domain. We focus on short tunes from the Irish folk tradition, represented as integer sequences, and use a graph-based representation based on Pathway Assembly (a directed acyclic graph) and the Sequitur algorithm. We define multiple mutation operators to work directly on the sequences or on the graphs, hypothesizing that graph-based mutations will tend to preserve the pattern used per tune, while direct mutation of sequences will tend to destroy patterns, resulting in new generated tunes that are more complex. We perform experiments on …
Combinedeepnet: A Deep Network For Multistep Prediction Of Near-Surface Pm2.5 Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan
Combinedeepnet: A Deep Network For Multistep Prediction Of Near-Surface Pm2.5 Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan
Conference papers
PM2.5 is a type of air pollutant that can cause respiratory and cardiovascular problems. Precise PM2.5 ( μg/m3 ) concentration prediction may help reduce health concerns and provide early warnings. To better understand air pollution, a number of approaches have been presented for predicting PM2.5 concentrations. Previous research used deep learning models for hourly predictions of air pollutants due to their success in pattern recognition, however, these models were unsuitable for multisite, long-term predictions, particularly in regard to the correlation between pollutants and meteorological data. This article proposes the combine deep network (CombineDeepNet), which combines multiple deep networks, including a …
Action Classification In Human Robot Interaction Cells In Manufacturing, Shakra S.M. Mehak, Maria Chiara Leva, John Kelleher, Michael Guilfoyle
Action Classification In Human Robot Interaction Cells In Manufacturing, Shakra S.M. Mehak, Maria Chiara Leva, John Kelleher, Michael Guilfoyle
Conference papers
Action recognition has become a prerequisite approach to fluent Human-Robot Interaction (HRI) due to a high degree of movement flexibility. With the improvements in machine learning algorithms, robots are gradually transitioning into more human-populated areas. However, HRI systems demand the need for robots to possess enough cognition. The action recognition algorithms require massive training datasets, structural information of objects in the environment, and less expensive models in terms of computational complexity. In addition, many such algorithms are trained on datasets derived from daily activities. The algorithms trained on non-industrial datasets may have an unfavorable impact on implementing models and validating …
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
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 …
Impact Of Character N-Grams Attention Scores For English And Russian News Articles Authorship Attribution, Liliya Mukhmutova, Robert J. Ross, Giancarlo Salton
Impact Of Character N-Grams Attention Scores For English And Russian News Articles Authorship Attribution, Liliya Mukhmutova, Robert J. Ross, Giancarlo Salton
Conference papers
Language embeddings are often used as black-box word-level tools that provide powerful language analysis across many tasks, but yet for many tasks such as Authorship Attribution access to feature level information on character n-grams can provide insights to help with model refinement and development. In this paper we investigate and evaluate the importance of character n-grams within an embeddings context in authorship attribution through the use of attention scores. We perform this investigation both for English (Reuters_50_50) and Russian (Taiga) news authorship datasets. Our analysis show that character n-grams attention score is higher for n-grams that are considered to be …
Indication Of Pedestrian’S Travel Direction Through Bluetooth Low Energy Signals Perceived By A Single Observer Device, Mayank Parmar, Paula Kelly, Damon Berry
Indication Of Pedestrian’S Travel Direction Through Bluetooth Low Energy Signals Perceived By A Single Observer Device, Mayank Parmar, Paula Kelly, Damon Berry
Conference papers
This paper presents a study to understand the directional sensitivity of a Bluetooth Low Energy (BLE) monitoring device (Observer) and whether, using a single such Observer, the characteristics of its antenna can be used to identify the direction of a pedestrian’s movement. To comprehend the directional characteristics of the antenna of the Observer employed for this study, the device is subjected to BLE signals emitted from a BLE beacon (Broadcaster) in an anechoic chamber. The results of this study confirmed that in the clean, noiseless environment of the chamber, the antenna we employed is clearly more receptive to signals emerging …
Show, Prefer And Tell: Incorporating User Preferences Into Image Captioning, Annika Lindh, Robert J. Ross, John Kelleher
Show, Prefer And Tell: Incorporating User Preferences Into Image Captioning, Annika Lindh, Robert J. Ross, John Kelleher
Conference papers
Image Captioning (IC) is the task of generating natural language descriptions for images. Models encode the image using a convolutional neural network (CNN) and generate the caption via a recurrent model or a multi-modal transformer. Success is measured by the similarity between generated captions and human-written “ground-truth” captions, using the CIDEr [14], SPICE [1] and METEOR [2] metrics. While incremental gains have been made on these metrics, there is a lack of focus on end-user opinions on the amount of content in captions. Studies with blind and low-vision participants have found that lack of detail is a problem [6, 13, …
How Will Air Source Heat Pumps Affect Electricity Load Profiles In Buildings In Ireland? A Data Logger Used To Model Electrical Energy Profiles, Michael Mcdonald
How Will Air Source Heat Pumps Affect Electricity Load Profiles In Buildings In Ireland? A Data Logger Used To Model Electrical Energy Profiles, Michael Mcdonald
Conference papers
There are many global factors that are challenging the colossal transition to Zero Carbon Economy, ranging from regional conflicts, possible new cold wars, inflation to rising interest rates. The climate challenge is, de facto, an energy transition challenge, which historically takes generations. Governments all over the world are working to implement policy that encourages society to foster clean energy and low carbon technologies. It is a fine balance between supply and demand of energy networks, whilst maintaining energy security. This was evident in Ireland during the winter of 2022 which witnessed several Systems Alerts, from the Transmission System Operator (TSO), …
Meme Sentiment Analysis Enhanced With Multimodal Spatial Encoding And Face Embedding, Muzhaffar Hazman, Susan Mckeever, Josephine Griffith
Meme Sentiment Analysis Enhanced With Multimodal Spatial Encoding And Face Embedding, Muzhaffar Hazman, Susan Mckeever, Josephine Griffith
Conference papers
Internet memes are characterised by the interspersing of text amongst visual elements. State-of-the-art multimodal meme classifiers do not account for the relative positions of these elements across the two modalities, despite the latent meaning associated with where text and visual elements are placed. Against two meme sentiment classification datasets, we systematically show performance gains from incorporating the spatial position of visual objects, faces, and text clusters extracted from memes. In addition, we also present facial embedding as an impactful enhancement to image representation in a multimodal meme classifier. Finally, we show that incorporating this spatial information allows our fully automated …
Using Machine Learning To Identify Patterns In Learner-Submitted Code For The Purpose Of Assessment, Botond Tarcsay, Fernando Perez-Tellez, Jelena Vasic
Using Machine Learning To Identify Patterns In Learner-Submitted Code For The Purpose Of Assessment, Botond Tarcsay, Fernando Perez-Tellez, Jelena Vasic
Conference papers
Programming has become an important skill in today’s world and is taught widely both in traditional and online settings. Instructors need to grade increasing amounts of student work. Unit testing can contribute to the automation of the grading process but it cannot assess the structure or partial correctness of code, which is needed for finely differentiated grading. This paper builds on previous research that investigated machine learning models for determining the correctness of programs from token-based features of source code and found that some such models can be successful in classifying source code with respect to whether it passes unit …
Detecting Road Intersections From Satellite Images Using Convolutional Neural Networks, Fatmaelzahraa Eltaher, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever
Detecting Road Intersections From Satellite Images Using Convolutional Neural Networks, Fatmaelzahraa Eltaher, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever
Conference papers
Automatic detection of road intersections is an important task in various domains such as navigation, route planning, traffic prediction, and road network extraction. Road intersections range from simple three-way T-junctions to complex large-scale junctions with many branches. The location of intersections is an important consideration for vulnerable road users such as People with Blindness or Visually Impairment (PBVI) or children. Route planning applications, however, do not give information about the location of intersections as this information is not available at scale. As a first step to solving this problem, a mechanism for automatically mapping road intersection locations is required, ideally …
Dynamic Influence Diagram-Based Deep Reinforcement Learning Framework And Application For Decision Support For Operators In Control Rooms, Joseph Mietkiewicz, Ammar N. Abbas, Chidera Winifred Amazu, Anders L. Madsen, Gabriele Baldissone
Dynamic Influence Diagram-Based Deep Reinforcement Learning Framework And Application For Decision Support For Operators In Control Rooms, Joseph Mietkiewicz, Ammar N. Abbas, Chidera Winifred Amazu, Anders L. Madsen, Gabriele Baldissone
Conference papers
In today’s complex industrial environment, operators are often faced with challenging situations that require quick and accurate decision-making. The human-machine interface (HMI) can display too much information, leading to information overload and potentially compromising the operator’s ability to respond effectively. To address this challenge, decision support models are needed to assist operators in identifying and responding to potential safety incidents. In this paper, we present an experiment to evaluate the effectiveness of a recommendation system in addressing the challenge of information overload. The case study focuses on a formaldehyde production simulator and examines the performance of an improved Human-Machine Interface …
Bilstm−Bigru: A Fusion Deep Neural Network For Predicting Air Pollutant Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan
Bilstm−Bigru: A Fusion Deep Neural Network For Predicting Air Pollutant Concentration, Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan
Conference papers
Predicting air pollutant concentrations is an efficient way to prevent incidents by providing early warnings of harmful air pollutants. A precise prediction of air pollutant concentrations is an important factor in controlling and preventing air pollution. In this paper, we develop a bidirectional long-short-term memory and a bidirectional gated recurrent unit (BiLSTM−BiGRU) to predict PM 2.5 concentrations in a target city for different lead times. The BiLSTM extracts preliminary features, and the BiGRU further extracts deep features from air pollutant and meteorological data. The fully connected (FC) layer receives the output and makes an accurate prediction of the PM 2.5 …
Modelling The Hydrating Behaviour Of Fly-Ash In Blended Cements Using Thermodynamics, Nikki Shaji, Niall Holmes Dr., Mark Tyrer
Modelling The Hydrating Behaviour Of Fly-Ash In Blended Cements Using Thermodynamics, Nikki Shaji, Niall Holmes Dr., Mark Tyrer
Conference papers
This paper presents a new method to thermodynamically model the hydration behaviour of fly-ash (FA) blended cements by deriving individual phase descriptions depending on the proportion of FA in the blended cement. The predicted hydrated phase assemblage, pore solution chemistries and pH over 1,000 days of hydration and with increasing FA proportions are presented. The thermodynamic data for the FA phases are derived using oxide proportions and mineral compositions are copied directly into the PHREEQC input file. The FA phases take account of all minerals to give a more accurate description of its behaviour during hydration. The calcium aluminosilicate hydrate …
How Will Heat Pumps Affect Electricity Load Profiles For Buildings In Ireland? Empirical Data Used To Model Possible Financial Impacts Facing Consumers, Michael Mcdonald
How Will Heat Pumps Affect Electricity Load Profiles For Buildings In Ireland? Empirical Data Used To Model Possible Financial Impacts Facing Consumers, Michael Mcdonald
Conference papers
The current geopolitical situation is certainly challenging the colossal transition to Zero carbon Economy. In fact, in the coming years, the electricity sector will have to find new innovative ways to meet the ever increasing need for energy without the over reliance on fossil fuels and their country of origin. Over the next decade, oil and gas boilers will not be permitted in new buildings in Ireland, in line with the Irish Building Regulations, Technical Guidance Document L – Conservation of Fuel and Energy 2021. This is a major shift in traditional building services methodology and heat technology. …
Acoustic Source Localization Using Straight Line Approximations, Swarnadeep Bagchi, Ruairí De Fréin
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 …
Reality Analagous Synthetic Dataset Generation With Daylight Variance For Deep Learning Classification, Thomas Lee, Susan Mckeever, Jane Courtney
Reality Analagous Synthetic Dataset Generation With Daylight Variance For Deep Learning Classification, Thomas Lee, Susan Mckeever, Jane Courtney
Conference papers
For the implementation of Autonomously navigating Unmanned Air Vehicles (UAV) in the real world, it must be shown that safe navigation is possible in all real world scenarios. In the case of UAVs powered by Deep Learning algorithms, this is a difficult task to achieve, as the weak point of any trained network is the reduction in predictive capacity when presented with unfamiliar input data. It is possible to train for more use cases, however more data is required for this, requiring time and manpower to acquire. In this work, a potential solution to the manpower issues of exponentially scaling …
Evaluating Safety And Productivity Relationship In Human-Robot Collaboration, Aayush Jain, Shakra Mehak, Philip Long, John D. Kelleher, Michael Guilfoyle, Maria Chiara Leva
Evaluating Safety And Productivity Relationship In Human-Robot Collaboration, Aayush Jain, Shakra Mehak, Philip Long, John D. Kelleher, Michael Guilfoyle, Maria Chiara Leva
Conference papers
Collaborative robots can improve ergonomics on factory floors while allowing a higher level of flexibility in production. The evolution of robotics and cyber-physical systems in size and functionality has enabled new applications which were never foreseen in traditional industrial robots. However, the current human-robot collaboration (HRC) technologies are limited in reliability and safety, which are vital in risk-critical scenarios. Certainly, confusion about European safety regulations has led to situations where collaborative robots operate behind security barriers, thus negating their advantages while reducing overall application productivity. Despite recent advances, developing a safe collaborative robotic system for performing complex industrial or daily …
Review Of Fly-Ash As A Supplementary Cementitious Material, Nikki Shaji, Niall Holmes Dr., Mark Tyrer
Review Of Fly-Ash As A Supplementary Cementitious Material, Nikki Shaji, Niall Holmes Dr., Mark Tyrer
Conference papers
This paper presents a review of fly-ash as a Supplementary Cementitious Material (SCM) in concrete in terms of its effects on hydration and durability. The climate change agenda has focused the cement and concrete industry on using low embodied CO2 materials and much effort has been made on incorporating industrial by-products into cement as SCMs. With worldwide cement production (circa 4 billion tonnes) currently accounting for approximately 8% of global CO2 emissions and 7% of industry energy use, the use of suitable SCMs to partially replace cement in concrete is extremely important. However, while coal-fired power stations are in the …
Improving The Reliability Of Visual Inspections Conducted By Fire And Rescue Services During Pre-Incident Planning Visits, Victor Hrymak
Improving The Reliability Of Visual Inspections Conducted By Fire And Rescue Services During Pre-Incident Planning Visits, Victor Hrymak
Conference papers
Fire and rescues services the world over commonly conduct pre-incident planning familiarisation visits. During such visits, fire crews typically look for observable fire safety hazards. Accordingly, two research questions were investigated in this study being; how many fire hazards are typically observed during such familiarisation visits and can the reliability of visual inspection conduct be improved by using a novel systematic visual inspection method. A fire and rescue service with 22 fire fighters was recruited, and they conducted 21 pre-incident planning visits to occupied apartments blocks. The experimental design involved one of the fire crew being tasked with observing fire …
Deriving Discrete Solid Phases From Csh-3t And Cshq End-Members To Model Cement Hydration In Phreeqc, Niall Holmes Dr., Colin Walker, Mark Tyrer, Denis Kelliher
Deriving Discrete Solid Phases From Csh-3t And Cshq End-Members To Model Cement Hydration In Phreeqc, Niall Holmes Dr., Colin Walker, Mark Tyrer, Denis Kelliher
Conference papers
This paper presents a cement hydration model over time using the CEMDATA thermodynamic database and a series of discrete solid phases (DSP) to represent calcium silicate hydrate (C-S-H) as a ternary (CSH-3T) and quaternary (CSHQ) solid solution. C-S-H in cement is amorphous and poorly crystalline with a range of molar Ca/Si ratios = 0.6-1.7 and displays strongly incongruent dissolution behaviour where the release of calcium into solution is several orders of magnitude greater than silicon. It is therefore important that any cement hydration model provides a credible account of this behaviour. C-S-H has been described in the CEMDATA thermodynamic database …
Modelling The Thermoelectric Properties Of Cement-Based Materials Using Finite Element Method And Effective Medium Theory, Lorenzo Stella, Conrad Johnston, Javier Troncoso, Piotr Chudzinski, Esther Orisakwee, Jorge Kohanoff, Ruchita Jani, Niall Holmes Dr., Brian Norton, Xiaoli Liu, Ming Qu, Hongxi Yin, Kazuaki Yazawa
Modelling The Thermoelectric Properties Of Cement-Based Materials Using Finite Element Method And Effective Medium Theory, Lorenzo Stella, Conrad Johnston, Javier Troncoso, Piotr Chudzinski, Esther Orisakwee, Jorge Kohanoff, Ruchita Jani, Niall Holmes Dr., Brian Norton, Xiaoli Liu, Ming Qu, Hongxi Yin, Kazuaki Yazawa
Conference papers
Because of the thermoelectric (TE) effect (or Seebeck effect), a difference of potential is generated as a consequence of a temperature gradient across a sample. The TE effect has been mostly studied and engineered in semiconducting materials and it already finds several commercial applications. Only recently the TE effect in cement-based materials has been demonstrated and there is a growing interest in its potential. For instance, a temperature gradient across the external walls of a building can be used to generate electricity. By the inverse of the TE effect (or Peltier effect), one can also seek to control the indoor …
Improving The Reliability Of Visual Inspections Conducted By Environmental Health And Safety Professionals, On A Hyperscale Data Centre Construction Site, Alex A. Schouten, Victor Hrymak
Improving The Reliability Of Visual Inspections Conducted By Environmental Health And Safety Professionals, On A Hyperscale Data Centre Construction Site, Alex A. Schouten, Victor Hrymak
Conference papers
The conduct of visual inspections on construction sites is of crucial importance for workplace safety. This is because visual inspection is the primary method by which construction site hazards are routinely observed, monitored and controlled. However, there is no consensus guidance as to how such visual inspections should be conducted. This is resulting in many observable hazards going unseen and therefore not being appropriately managed on construction sites worldwide. In an attempt to improve the reliability of visual inspection, this study presents results from an innovative method called systematic visual inspection which utilises an iterative set eye scan pattern during …
Towards Emulation Of Intelligent Iot Networks On Eu-Us Testbeds, Sachin Sharma, Saish Urumkar, Gianluca Fontanesi, Venkat Sai Suman Lamba Karanam, Boyang Hu, Byrav Ramamurthy, Avishek Nag
Towards Emulation Of Intelligent Iot Networks On Eu-Us Testbeds, Sachin Sharma, Saish Urumkar, Gianluca Fontanesi, Venkat Sai Suman Lamba Karanam, Boyang Hu, Byrav Ramamurthy, Avishek Nag
Conference papers
This paper introduces our project on experimental validation of intelligent Internet of Things (IoT) networks. The project is a part of the NGIAtlantic H2020 third open call to perform experiments on EU and US wireless testbeds. The project proposes five different experiments to be performed on EU/US testbeds: (1) automatic configuration/discovery of Software Defined Networking (SDN) in wireless IoT sensor networks, (2) Machine Learning (ML) assisted control and data traffic path discovery experiments, (3) GPU and Hadoop cluster assisted experiments for ML algorithms, (4) Inter-testbed experiments, and (5) Failure recovery intercity experiments. Further, initial experimentation on EU/US testbeds is explored …
Demonstrating Configuration Of Software Defined Networking In Real Wireless Testbeds, Saish Urumkar, Gianluca Fontanesi, Avishek Nag, Sachin Sharma
Demonstrating Configuration Of Software Defined Networking In Real Wireless Testbeds, Saish Urumkar, Gianluca Fontanesi, Avishek Nag, Sachin Sharma
Conference papers
Currently, several wireless testbeds are available to test networking solutions including Fed4Fire testbeds such as w-ilab. t and CityLab in the EU, and POWDER and COSMOS in the US. In this demonstration, we use the w-ilab.t testbed to set up a wireless ad-hoc Software-Defined Network (SDN). OpenFlow is used as an SDN protocol and is deployed using a grid wireless ad-hoc topology in w-ilab.t. In this paper, we demonstrate: (1) the configuration of a wireless ad-hoc network based on w-ilab.t and (2) the automatic deployment of OpenFlow in an ad-hoc wireless network where some wireless nodes are not directly connected …
Experimenting An Edge-Cloud Computing Model On The Gpulab Fed4fire Testbed, Vikas Tomer, Sachin Sharma
Experimenting An Edge-Cloud Computing Model On The Gpulab Fed4fire Testbed, Vikas Tomer, Sachin Sharma
Conference papers
There are various open testbeds available for testing algorithms and prototypes, including the Fed4Fire testbeds. This demo paper illustrates how the GPULAB Fed4Fire testbed can be used to test an edge-cloud model that employs an ensemble machine learning algorithm for detecting attacks on the Internet of Things (IoT). We compare experimentation times and other performance metrics of our model based on different characteristics of the testbed, such as GPU model, CPU speed, and memory. Our goal is to demonstrate how an edge-computing model can be run on the GPULab testbed. Results indicate that this use case can be deployed seamlessly …
Performance Modeling And Analysis Of A Thermoelectric Building Envelope For Space Heating, Xiaoli Liu, Ming Qu, Kazuaki Yazawa, Jorge Kohanoff, Piotr Chudzinski, Lorenzo Stella, Brian Norton, Niall Holmes Dr., Ruchita Jani, Hongxi Yin
Performance Modeling And Analysis Of A Thermoelectric Building Envelope For Space Heating, Xiaoli Liu, Ming Qu, Kazuaki Yazawa, Jorge Kohanoff, Piotr Chudzinski, Lorenzo Stella, Brian Norton, Niall Holmes Dr., Ruchita Jani, Hongxi Yin
Conference papers
To provide energy-efficient space heating and cooling, a thermoelectric building envelope (TBE) embeds thermoelectric devices in building walls. The thermoelectric device in the building envelope can provide active heating and cooling without requiring refrigerant use and energy transport among subsystems. Thus, the TBE system is energy and environmentally friendly. A few studies experimentally investigated the TBE under limited operating conditions, and only simplified models for the commercial thermoelectric module (TEM) were developed to quantify its performance. A holistic approach to optimum system performance is needed for the optimal system design and operation. The study developed a holistic TBE-building system model …
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany
Conference papers
Gender imbalance in computing education is a well-known issue around the world. For example, in the UK and Ireland, less than 20% of the student population in computer science, ICT and related disciplines are women. Similar figures are seen in the labour force in the field across the EU. The term "leaky pipeline"; is often used to describe the lack of retention of women before they progress to senior roles. Numerous initiatives have targeted the problem of the leaky pipeline in recent decades. This paper provides a comprehensive review of initiatives related to techniques used to boost recruitment and improve …
Generating Reality-Analogous Datasets For Autonomous Uav Navigation Using Digital Twin Areas, Thomas Lee, Susan Mckeever, Jane Courtney
Generating Reality-Analogous Datasets For Autonomous Uav Navigation Using Digital Twin Areas, Thomas Lee, Susan Mckeever, Jane Courtney
Conference papers
In order for autonomously navigating Unmanned Air Vehicles(UAVs) to be implemented in day-to-day life, proof of safe operation will be necessary for all realistic navigation scenarios. For Deep Learning powered navigation protocols, this requirement is challenging to fulfil as the performance of a network is impacted by how much the test case deviates from data that the network was trained on. Though networks can generalise to manage multiple scenarios in the same task, they require additional data representing those cases which can be costly to gather. In this work, a solution to this data acquisition problem is suggested by way …