Engineering Commons^™

Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney

Articles

For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …

Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney

Articles

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …

Internet Of Medical Things (Iomt): Overview, Emerging Technologies, And Case Studies, Sahshanu Razdan, Sachin Sharma

Articles

No abstract provided.

Virtual Network Function Embedding Under Nodal Outage Using Deep Q-Learning, Swarna Bindu Chetty, Hamed Ahmadi, Sachin Sharma, Avishek Nag

Articles

With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear …

The Prospect Of Microwave Heating: Towards A Faster And Deeper Crack Healing In Asphalt Pavement, Shi Xu, Xueyan Liu, Amir Tabakovic, Erik Schlangen

Articles

Microwave heating has been shown to be an effective method of heating asphalt concrete and in turn healing the damage. As such, microwave heating holds great potential in rapid (1–3 min) and effective damage healing, resulting in improvement in the service life, safety, and sustainability of asphalt pavement. This study focused on the microwave healing effect on porous asphalt concrete. Steel wool fibres were incorporated into porous asphalt to improve the microwave heating efficiency, and the optimum microwave heating time was determined. Afterwards, the microwave healing efficiency was evaluated using a semi–circular bending and healing programme. The results show that …

Near-Field Propagation Analysis For Vivaldi Antenna Design: Insight Into The Propagation Process For Optimizing The Directivity, Integrity Of Signal Transmission, And Efficiency, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann

Articles

Refined optimization of complex curve–linear-shaped radiators, such as traveling-wave Vivaldi antennas, can be achieved by considering simulated near fields to interpret in detail the structural influences of a design. The relationships between the space and time distributions of electromagnetic (EM) energy clusters and the geometric features are revealed with appropriate use of impulse response analysis combined with the multiple signal classification (MUSIC) algorithm. This article reports a deeper approach when applied to the adjustment of the geometric features of a traveling-wave antenna based on an analysis of near-field propagation features.

Optimisation Of Retrofit Wall Insulation: An Irish Case Study, Rakshit D. Muddu, D M. Gowda, Anthony James Robinson, Aimee Byrne

Articles

Ireland has one of the highest rates of emissions per capita in the world and its residential sector is responsible for approximately 10% of total national CO2 emissions. Therefore, reducing the CO2 emissions in this sector will play a decisive role in achieving EU targets of reducing emissions by 40% by 2030. To better inform decisions regarding retrofit of the existing building stock, this study proposes Optimum Insulation Thicknesses (OIT) for typical walls in 25 regions in Ireland. The calculation of OIT includes annual heat energy expenditure, CO2 emissions, and material payback period. The approach taken is based on Heating …

Human Age And Gender Classification Using Convolutional Neural Networks, Eamon Kelliher

Dissertations

In a world relying ever more on human classification, this papers aims to improve on age and gender image classification through the use of Convolutional Neural Networks (CNN). Age and gender classification has become a popular area of study in the past number of years however there are still improvements to be made, particularly in the area of age classification. This research paper aims to test the currently accepted fact that CNN models are the superior model type for image classification by comparing CNN performance against Support Vector Machine performance on the same dataset. Using the Adience image classification dataset, …

Identifying Roles Of Software Developers From Their Answers On Stack Overflow, Dean Power

Dissertations

Stack Overflow is the world’s largest community of software developers. Users ask and answer questions on various tagged topics of software development. The set of questions a site user answers is representative of their knowledge base, or “wheelhouse”. It is proposed that clustering users by their wheelhouse yields communities of similar software developers by skill-set. These communities represent the different roles within software development and could be used as the basis to define roles at any point in time in an ever-evolving landscape of software development. A network graph of site users, linked if they answered questions on the same …

In Depth Characterisation Of The Biomolecular Coronas Of Polymer Coated Inorganic Nanoparticles With Differential Centrifugal Sedimentation, André Perez-Potti, Hender Lopez, Beatriz Pelaz, Abuelmagd Abdelmonem, Mahmoud G. Soliman, Ingmar Schoen, Philip M. Kelly, Kenneth A. Dawson, Wolfgang J. Parak, Zeljka Krpetic, Marco P. Monopoli

Articles

Advances in nanofabrication methods have enabled the tailoring of new strategies towards the controlled production of nanoparticles with attractive applications in healthcare. In many cases, their characterisation remains a big challenge, particularly for small-sized functional nanoparticles of 5 nm diameter or smaller, where current particle sizing techniques struggle to provide the required sensitivity and accuracy. There is a clear need for the development of new reliable characterisation approaches for the physico-chemical characterisation of nanoparticles with significant accuracy, particularly for the analysis of the particles in the presence of complex biological fluids. Herein, we show that the Differential Centrifugal Sedimentation can …

A Comparison Of Instructional Efficiency Models In Third Level Education, Murali Rajendran

Dissertations

This study investigates the validity and sensitivity of a novel model of instructional efficiency: the parabolic model. The novel model is compared against state-of-the-art models present in instructional design today; Likelihood model, Deviational model and Multidimensional model. This models is based on the assumption that optimal mental workload and high performance leads to high efficiency, while other models assume that low mental workload and high performance leads to high efficiency. The investigation makes use of two instructional design conditions: a direct instructions approach to learning and its extension with a collaborative activity. A control group received the former instructional design …

On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge

Articles

We consider the consequence of breaking with a fundamental result in complex analysisby lettingi2=±1wherei=√−1is the basic unit of all imaginary numbers. An analysis of theMandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object ispossible based oni2=−1andi2= +1, respectively. Further, we consider the transient behaviourassociated with the two cases to produce a range of non-standard sets in which a Fractal geometricstructure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclideanobject is a square whose properties are investigate. Coupled with the associated Julia sets and othercomplex plane mappings, this …

Feature Augmentation For Improved Topic Modeling Of Youtube Lecture Videos Using Latent Dirichlet Allocation, Nakul Srikumar

Dissertations

Application of Topic Models in text mining of educational data and more specifically, the text data obtained from lecture videos, is an area of research which is largely unexplored yet holds great potential. This work seeks to find empirical evidence for an improvement in Topic Modeling by pre- extracting bigram tokens and adding them as additional features in the Latent Dirichlet Allocation (LDA) algorithm, a widely-recognized topic modeling technique. The dataset considered for analysis is a collection of transcripts of video lectures on Machine Learning scraped from YouTube. Using the cosine similarity distance measure as a metric, the experiment showed …

Can Generative Adversarial Networks Help Us Fight Financial Fraud?, Sean Mciver

Dissertations

Transactional fraud datasets exhibit extreme class imbalance. Learners cannot make accurate generalizations without sufficient data. Researchers can account for imbalance at the data level, algorithmic level or both. This paper focuses on techniques at the data level. We evaluate the evidence of the optimal technique and potential enhancements. Global fraud losses totalled more than 80 % of the UK’s GDP in 2019. The improvement of preprocessing is inherently valuable in fighting these losses. Synthetic minority oversampling technique (SMOTE) and extensions of SMOTE are currently the most common preprocessing strategies. SMOTE oversamples the minority classes by randomly generating a point between …

Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy

Dissertations

Sentiment Analysis also known as opinion mining is a type of text research that analyses people’s opinions expressed in written language. Sentiment analysis brings together various research areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is fast becoming of major importance to companies and organizations as it is started to incorporate online commerce data for analysis. Often the data on which sentiment analysis is performed will be reviews. The data can range from reviews of a small product to a big multinational corporation. The goal of performing sentiment analysis is to extract information from those …

Performance Comparison Between A Distributed Particle Swarm Algorithm And A Centralised Algorithm, Ciarán O’Loughlin

Dissertations

Particle Swarm optimisation (PSO) is a particular form of swarm intelligence, which itself is an innovative intelligent paradigm for solving optimization problems. PSO is generally used to find a global optimum in a single optimisation function. This typically occurs on one node(machine) but there has been a significant body of research into creating distributed implementations of the PSO algorithm. Such research has often focused on the creation and performance of the distributed implementation in an isolated manner or compared to different distributed algorithms.

This research piece aims to bridge a gap in the existing literature, by testing a distributed implementation …

Stellar Classification Of Folded Spectra Using The Mk Classification Scheme And Convolutional Neural Networks, John Magee

Dissertations

The year 1943 saw the introduction of the Morgan-Keenan (MK) classification scheme and this replaced the existing Harvard Classification scheme. Both stellar classification scheme are fundamentally grounded in the field of spectroscopy. The Harvard Classification scheme classified stars based on stellar surface temperature. The MK Classification scheme introduced the concept of a luminosity class that is intrinsically linked to the surface gravity of a star. Temperature and luminosity class values are estimated directly from the stellar spectrum.

Machine learning is a well-established technique in astronomy. Traditionally, a spectrum is treated as a one-dimensional sequence of data. Techniques such as artificial …

Event-Driven Servers Using Asynchronous, Non-Blocking Network I/O: Performance Evaluation Of Kqueue And Epoll, Lorcan Leonard

Dissertations

This research project evaluates the performance of kqueue and epoll in the context of event-driven servers. The evaluation is done through benchmarking and tracing which are used to measure throughput and execution time respectively. The experiment is repeated for both a virtualised and native server environment. The results from the experiment are statistically analysed and compared. These results show significant differences between kqueue and epoll, and a profound impact of virtualisation as a variable.

Improving A Network Intrusion Detection System’S Efficiency Using Model-Based Data Augmentation, Vinicius Waterkemper Lodetti

Dissertations

A network intrusion detection system (NIDS) is one important element to mitigate cybersecurity risks, the NIDS allow for detecting anomalies in a network which may be a cyberattack to a corporate network environment. A NIDS can be seen as a classification problem where the ultimate goal is to distinguish between malicious traffic among a majority of benign traffic. Researches on NIDS are often performed using outdated datasets that don’t represent the actual cyberspace. Datasets such as the CICIDS2018 address this gap by being generated from attacks and an infrastructure that reflects an up-to-date scenario.

A problem may arise when machine …

A Hybrid Neural Network For Stock Price Direction Forecasting, Daniel Devine

Dissertations

The volatility of stock markets makes them notoriously difficult to predict and is the reason that many investors sell out at the wrong time. Contrary to the efficient market hypothesis (EMH) and the random walk theory, contribution to the study of machine learning models for stock price forecasting has shown evidence of stock markets predictability with varying degrees of success. Contemporary approaches have sought to use a hybrid of convolutional neural network (CNN) for its feature extraction capabilities and long short-term memory (LSTM) neural network for its time series prediction. This comparative study aims to determine the predictability of stock …

Identifying Significant Features For Player Evaluation In Nfl Comparing Anns And Traditional Models, Ronan Walsh

Dissertations

The evaluation of player performance in sports is popular and important in modern sports, enabling teams to use real data in the construction of their rosters. This dissertation proposes to apply machine learning algorithms to predicting the player evaluations from a leading NFL analytics company who use a combination of statistics and expert evaluation. In addition, it will investigate what features are significant in the evaluation of a position. Data for the dissertation is obtained from multiple online sources - Pro Football Reference and Pro Football Focus (the the NFL analytics company). These data sets are combined and analysed before …

Evaluating The Performance Of Transformer Architecture Over Attention Architecture On Image Captioning, Deepti Balasubramaniam

Dissertations

Over the last few decades computer vision and Natural Language processing has shown tremendous improvement in different tasks such as image captioning, video captioning, machine translation etc using deep learning models. However, there were not much researches related to image captioning based on transformers and how it outperforms other models that were implemented for image captioning. In this study will be designing a simple encoder-decoder model, attention model and transformer model for image captioning using Flickr8K dataset where will be discussing about the hyperparameters of the model, type of pre-trained model used and how long the model has been trained. …

Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir

Dissertations

Sentiment analysis is also known as Opinion mining or emotional mining which aims to identify the way in which sentiments are expressed in text and written data. Sentiment analysis combines different study areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is quickly becoming a key concern for businesses and organizations, especially as online commerce data is being used for analysis. Twitter is also becoming a popular microblogging and social networking platform today for information among people as they contribute their opinions, thoughts, and attitudes on social media platforms over the years. Because of the large …

An Evaluation On The Performance Of Code Generated With Webassembly Compilers, Raymond Phelan

Dissertations

WebAssembly is a new technology that is revolutionizing the web. Essentially it is a low-level binary instruction set that can be run on browsers, servers or stand-alone environments. Many programming languages either currently have, or are working on, compilers that will compile the language into WebAssembly. This means that applications written in languages like C++ or Rust can now be run on the web, directly in a browser or other environment. However, as we will highlight in this research, the quality of code generated by the different WebAssembly compilers varies and causes performance issues. This research paper aims to evaluate …

Enhancing The Visibility Of Vernier Effect In A Tri-Microfiber Coupler Fiber Loop Interferometer For Ultrasensitive Refractive Index And Temperature Sensing, Fangfang Wei, Dejun Liu, Zhe Wang, Zhuochen Wang, Gerald Farrell, Qiang Wu, Gang-Ding Peng, Yuliya Semenova

Articles

In this paper a Vernier effect based sensor is analyzed and demonstrated experimentally in a tri-microfiber coupler (Tri-MFC) and polarization-maintaining fiber (PMF) loop interferometer (Tri-MFC-PMF) to provide ultrasensitive refractive index and temperature sensing. The main novelty of this work is an analysis of parameters of the proposed Tri-MFC-PMF with the objective of determining the conditions leading to a strong Vernier effect. It has been identified by simulation that the Vernier effect is a primary factor in the design of Tri-MFC-PMF loop sensing structure for sensitivity enhancement. It is furthermore demonstrated experimentally that enhancing the visibility of the Vernier spectrum in …

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney

Articles

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …

The Fabrication And Properties Of Magnetorheological Elastomers Employing Bio-Inspired Dopamine Modified Carbonyl Iron Particles, Yanfen Zhou, Lele Li, Wenyue Li, Shipeng Wen, Liang Jiang, Stephen Jerrams, Jianwei Ma, Shaojuan Chen

Articles

To obtain magnetorheological elastomers (MREs) with improved mechanical properties and exhibiting an enhanced magnetorheological (MR) effect, bio-inspired dopamine modification has been used to improve the functionality at the surface of carbonyl iron (CI) particles. Various techniques including x-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to confirm that a polydopamine (PDA) layer of about 27.5 nm had been successfully deposited on the surface of the carbonyl iron particles prior to their inclusion in the MRE composites. The magnetic properties of PDA modified CI particles were shown to be almost the same as those …

Enhanced Covalent Interface, Crosslinked Network And Gas Barrier Property Of Functionalized Graphene Oxide/Styrene-Butadiene Rubber Composites Triggered By Thiol-Ene Click Reaction, Long Zheng, Stephen Jerrams, Tian Su, Zongchao Xu, Liqun Zhang, Li Liu, Shipeng Wen

Articles

The high gas barrier property of a rubber composite is of great significance for reducing the exhaust gas emissions due to tire rolling resistance and hence the contribution this factor makes to environmental protection. Enhanced covalent interfaces and crosslinked networks are crucial to the gas barrier property of rubber composites. In this research, γ-mercaptopropyltriethoxysilane (MPS) modified GO (MGO)/styrene-butadiene rubber (SBR) composites were prepared by a synergetic strategy of latex compounding method and thiol-ene click reaction. It was found that the mercapto groups in MGO reacted with the vinyl groups in SBR molecules through thiol-ene click reaction during the crosslinking process …

Simultaneous Measurement Of Displacement And Temperature Based On Two Cascaded Balloon-Like Bent Fibre Structures, Ke Tian, Ruoning Wang, Meng Zhang, Xiafan Wang, Xin Wang, Guoyong Jin, Elfed Lewis, Gerald Farrell, Pengfei Wang

Articles

A low-cost optical fibre sensor based on two cascaded balloon-like bent fibre (BBF) structures for simultaneous displacement and temperature measurement is reported. The sensor is fabricated by cascading two balloon-like bent single-mode fibres (SMFs) which with different bending radii, generating two separate interference dips within a limited wavelength range. The wavelength of the two interference dips exhibits different responses to external displacement and temperature variations, hence simultaneous measurement of displacement and temperature is realized. Experimental results show that the proposed optical fibre sensor achieves a displacement sensitivity of −318.8 pm/μm and a temperature sensitivity of 47.4 pm/°C. Taking advantage of …

Microfluidic Flow Direction And Rate Vector Sensor Based On A Partially Gold-Coated Tfbg, Changyu Shen, Dejun Liu, Xiaokang Lian, Tingting Lang, Chunliu Zhao, Yuliya Semenova, Jacques Albert

Articles

In microfluidic chips applications, the monitoring of the rate and the direction of a microfluidic flow is very important. Here, we demonstrate a liquid flow rate and a direction sensor using a partially gold-coated tilted fiber Bragg grating (TFBG) as the sensing element. Wavelength shifts and amplitude changes of the TFBG transmission resonances in the near infrared reveal the direction of the liquid flowing along the fiber axis in the vicinity of the TFBG due to a nanoscale gold layer over part of the TFBG. For a device length of 10 mm (and a diameter of 125 µm for easy …