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Articles 361 - 390 of 731
Full-Text Articles in Computer Engineering
From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji
From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji
Dissertations
This research project identifies the significant factors that affects the number of customer visits to a fast-casual restaurant every hour and proceeds to develop several machine learning models to forecast customer visits. The core value proposition of fast-casual restaurants is quality food delivered at speed which means they have to prepare meals in advance of customers visit but the problem with this approach is in forecasting future demand, under estimating demand could lead to inadequate meal preparation which would leave customers unsatisfied while over estimation of demand could lead to wastage especially with restaurants having to comply with food safety …
Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne
Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne
Dissertations
This study aimed to look at a traditional method used for measuring the severity and principle direction of force of a car crash and see if it could be improved on using machine learning models. The data used was publicly available from the NHTSA database and included descriptions of the vehicle, test and sensors as well as the accelerometer data over the period of the crashes. The models built were SVM classifiers and multinomial regression models. Although the SVM and Regression models were built successfully and gave higher levels of accuracy than the momentum models in terms of the severity, …
Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy
Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy
Dissertations
Forecasting stock market price movement is a well researched and an alluring topic within the machine learning and financial realm. Supervised machine learning algorithms such as Random Forest (RF) and Support Vector Machines (SVM) have been used independently to gain insight on the market. With such volatility in the market the scope of this study will utilized the RF and SVM in a very volatility market to determine if these models will perform at a high level or outperform each other in both markets. This relative study is performed on 16 stocks in 4 different sectors over the bear market …
Identifying Expert Investors On Financial Microblog Via Artificial Neural Networks, Pierluca Del Buono
Identifying Expert Investors On Financial Microblog Via Artificial Neural Networks, Pierluca Del Buono
Dissertations
In the recent years, thanks to social media platform, a plethora of information has been available to financial investors, that were traditionally dependent from financial institutions advisors. Strategies are now shared among web users, performances of stocks are commented in web communities and hints and suggestions are travelling on the internet with a fast pace, in a way that was unthinkable few years before. Several attempts have been made in the recent past, to predict Market movements and trends from activity of Financial Social Networks participants, and to evaluate if contributions from individuals with high level of expertise distinguish themselves …
Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena
Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena
Articles
This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …
Using Moocs To Promote Digital Accessibility And Universal Design, The Moocap Experience, John Gilligan, W. Chen, J. Darzentas
Using Moocs To Promote Digital Accessibility And Universal Design, The Moocap Experience, John Gilligan, W. Chen, J. Darzentas
Articles
The recently completed Massive Open Online Course for Accessibility Partnership project (MOOCAP), had the twin aims of establishing a strategic partnership around the promotion of Universal Design and Accessibility for ICT professionals and of developing a suite of Open Educational resources (OERs) in this domain. MOOCAP's eight university partners from Germany, Norway, Greece, Ireland, the UK and Austria have a significant history in developing and providing courses in the domains of Universal Design and Accessibility, as well as leading research and advocacy roles within Europe. The MOOCAP project consisted of two phases: the development of an introductory MOOC on Digital …
Examining The Effects Of A Virtual Character On Learning And Engagement In Serious Games, Vihanga Gamage, Cathy Ennis
Examining The Effects Of A Virtual Character On Learning And Engagement In Serious Games, Vihanga Gamage, Cathy Ennis
Articles
Virtual characters have been employed for many purposes including interacting with players of serious games, with a purpose to increase engagement. These characters are often embodied conversational agents playing diverse roles, such as demonstrators, guides, teachers or interviewers. Recently, much research has been conducted into properties that affect the realism and plausibility of virtual characters, but it is less clear whether the inclusion of interactive agents in serious applications can enhance a user’s engagement with the application, or indeed increase efficacy. In a first step towards answering these questions, we conducted a study where a Virtual Learning Environment was used …
Investigating The Application Of Deep Convolutional Neural Networks In Semi-Supervised Video Object Segmentation, Jayadeep Sasikumar
Investigating The Application Of Deep Convolutional Neural Networks In Semi-Supervised Video Object Segmentation, Jayadeep Sasikumar
Dissertations
This thesis investigates the different approaches to video object segmentation and the current state-of-the-art in the discipline, focusing on the different deep learning techniques used to solve the problem. The primary contribution of the thesis is the investigation of usefulness of Exponential Linear Units as activation functions for deep convolutional neural architectures trained to perform object semi-supervised segmentation in videos. Mask R-CNN was chosen as the base convolutional neural architecture, with the view of extending the image segmentation algorithm to videos. Two models were created, one with Rectified Linear Units and the other with Exponential Linear Units as the respective …
Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John D. Kelleher
Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John D. Kelleher
Conference papers
Projects that set out to create a linguistic resource often do so by using a machine learning model that pre-annotates or filters the content that goes through to a human annotator, before going into the final version of the resource. However, available budgets are often limited, and the amount of data that is available exceeds the amount of annotation that can be done. Thus, in order to optimize the benefit from the invested human work, we argue that the decision on which predictive model one should employ depends not only on generalized evaluation metrics, such as accuracy and F-score, but …
Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster
Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster
Conference papers
The relentless march of technology is increasingly opening new possibilities for the application of automation and new horizons for human machine interaction. However there is insufficient scientific evidence on human factors for modern socio-technical systems supporting the guidelines currently used to design Human Machine Interfaces (HMI) (ISA 2014). This dearth of knowledge presents a particular risk in safety critical industries. The continuing 60–90% of accidents currently that are rooted in Human Factors (HF) and the rapid developments in the Internet of Things (IoT) and its novel automation archetypes means that the requirements for new interfaces are becoming more demanding, and …
Ambiqual – A Full Reference Objective Quality Metric For Ambisonic Spatial Audio, Miroslaw Narbutt, Andrew Allen, Jan Skoglund, Michael Chinen, Andrew Hines
Ambiqual – A Full Reference Objective Quality Metric For Ambisonic Spatial Audio, Miroslaw Narbutt, Andrew Allen, Jan Skoglund, Michael Chinen, Andrew Hines
Conference papers
Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users’ perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. …
Ranking Semantics Based On Subgraphs Analysis, Pierpaolo Dondio
Ranking Semantics Based On Subgraphs Analysis, Pierpaolo Dondio
Conference papers
An abstract argumentation framework [15] consists of a direct graph where nodes represent arguments and arrows represent an attack relation among arguments. A semantics is used to evaluate arguments’ acceptability. In the labelling approach [7], this evaluation is done by assigning to each argument a label in, out or undec, meaning that the argument is considered consistently acceptable, non-acceptable or undecided (i.e. no decision can be taken on arguments’ acceptability).
On The Reliability, Validity And Sensitivity Of Three Mental Workload Assessment Techniques For The Evaluation Of Instructional Designs: A Case Study In A Third-Level Course, Luca Longo
Conference papers
Cognitive Load Theory (CLT) has been conceived for instructional designers eager to create instructional resources that are presented in a way that encourages the activities of the learners and optimise their performance, thus their learning. Although it has been researched for many years, it has been criticised because of its theoretical clarity and its methodological approach. In particular, one fundamental and open problem is the measurement of its cognitive load types and the measurement of the overall cognitive load of learners during learning tasks. This paper is aimed at investigating the reliability, validity and sensitivity of existing mental workload assessment …
Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez
Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez
Conference papers
As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other …
Beef Cattle Instance Segmentation Using Mask R-Convolutional Neural Network, Mohammad Danish
Beef Cattle Instance Segmentation Using Mask R-Convolutional Neural Network, Mohammad Danish
Dissertations
Maintaining the cattle farm along with the wellbeing of every heifer has been the major concern in dairy farm. A robust system is required which can tackle the problem of continuous monitoring of cows. the computer vision techniques provide a new way to understand the challenges related to the identification and welfare of the cows. This paper presents a state-of-art instance segmentation mask RCNN algorithm to train and build a model on a very challenging cow dataset that is captured during the winter season. The dataset poses many challenges such as overlapping of cows, partial occlusion, similarity between cows and …
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin
Conference papers
We present a tiled delay estimation technique in the context of Mobile Cloud Computing (MCC) environments. We examine its accuracy in the presence of multiple sources for (1) sub-sample delays and also (2) in the presence of phase-wrap around. Phase wrap-around is prevalent in MCC because the separation of acoustic sources may be large. We show that tiling a histogram of instantaneous phase estimates can improve delay estimates when phase-wrap around is sig- nificantly present and also when multiple sources are present. We report that error in the delay estimator is generally less than 5% of a sample, when the …
K-Bit-Swap: A New Operator For Real-Coded Evolutionary Algorithms, Aram Ter-Sarkisov, Stephen Marsland
K-Bit-Swap: A New Operator For Real-Coded Evolutionary Algorithms, Aram Ter-Sarkisov, Stephen Marsland
Articles
There has been a variety of crossover operators proposed for Real-Coded Genetic Algorithms (RCGAs), which recombine values from the same location in pairs of strings. In this article we present a recombination operator for RC- GAs that selects the locations randomly in both parents, and compare it to mainstream crossover operators in a set of experiments on a range of standard multidimensional optimization problems and a clustering problem. We present two variants of the operator, either selecting both bits uniformly at random in the strings, or sampling the second bit from a normal distribution centered at the selected location in …
The Use Of Persistent Explorer Artificial Ants To Solve The Car Sequencing Problem, Kieran O'Sullivan
The Use Of Persistent Explorer Artificial Ants To Solve The Car Sequencing Problem, Kieran O'Sullivan
Dissertations
Ant Colony Optimisation is a widely researched meta-heuristic which uses the behaviour and pheromone laying activities of foraging ants to find paths through graphs. Since the early 1990’s this approach has been applied to problems such as the Travelling Salesman Problem, Quadratic Assignment Problem and Car Sequencing Problem to name a few. The ACO is not without its problems it tends to find good local optima and not good global optima. To solve this problem modifications have been made to the original ACO such as the Max Min ant system. Other solutions involve combining it with Evolutionary Algorithms to improve …
Can Deep Learning Techniques Improve The Risk Adjusted Returns From Enhanced Indexing Investment Strategies, Anthony Grace
Can Deep Learning Techniques Improve The Risk Adjusted Returns From Enhanced Indexing Investment Strategies, Anthony Grace
Dissertations
Deep learning techniques have been widely applied in the field of stock market prediction particularly with respect to the implementation of active trading strategies. However, the area of portfolio management and passive portfolio management in particular has been much less well served by research to date. This research project conducts an investigation into the science underlying the implementation of portfolio management strategies in practice focusing on enhanced indexing strategies. Enhanced indexing is a passive management approach which introduces an element of active management with the aim of achieving a level of active return through small adjustments to the portfolio weights. …
Can A Strictly Defined Security Configuration For Iot Devices Mitigate The Risk Of Exploitation By Botnet Malware?, David Kennefick
Can A Strictly Defined Security Configuration For Iot Devices Mitigate The Risk Of Exploitation By Botnet Malware?, David Kennefick
Dissertations
The internet that we know and use every day is the internet of people, a collection of knowledge and data that can be accessed anywhere is the world anytime from many devices. The internet of the future is the Internet of Things. The Internet of Things is a collection of automated technology that is designed to be run autonomously, but on devices designed for humans to use. In 2016 the Mirai malware has shown there are underlying vulnerabilities in devices connected to the internet of things. Mirai is specifically designed to recognise and exploit IoT devices and it has been …
An Analysis Of Predicting Job Titles Using Job Descriptions, John Lynch
An Analysis Of Predicting Job Titles Using Job Descriptions, John Lynch
Dissertations
A job title is an all-encompassing very short form description that conveys all of the pertinent information relating to a job. The job title typically encapsulates - and should encapsulate - the domain, role and level of responsibility of any given job. Significant value is attached to job titles both internally within organisational structures and to individual job holders. Organisations map out all employees in an organogram on the basis of job titles. This has a bearing on issues like salary, level and scale of responsibility, employee selection and so on. Employees draw value from their own job titles as …
Cybercrime: An Investigation Of The Attitudes And Environmental Factors That Make People More Willing To Participate In Online Crime, Dearbhail Kirwan
Cybercrime: An Investigation Of The Attitudes And Environmental Factors That Make People More Willing To Participate In Online Crime, Dearbhail Kirwan
Dissertations
Cybercrime incidence rates are increasing. In order to identify solutions to this problem, the sources of cybercrime need to be identified. This research attempted to identify a potential set of circumstances that create an environment in which people are more likely to engage in cybercrime. There are three aspects to this; (1) Behaviour on the internet – Are people more likely to engage in illicit activities online than in the physical world? (2) Crime Perceptions – Do people perceive cybercrime as being less serious than non-cybercrime? (3) Resources on the Internet – Are people aware of the types of free …
“How Short Is A Piece Of String?”: An Investigation Into The Impact Of Text Length On Short-Text Classification Accuracy, Austin Mccartney
“How Short Is A Piece Of String?”: An Investigation Into The Impact Of Text Length On Short-Text Classification Accuracy, Austin Mccartney
Dissertations
The recent increase in the widespread use of short messages, for example micro-blogs or SMS communications, has created an opportunity to harvest a vast amount of information through machine-based classification. However, traditional classification methods have failed to produce accuracies comparable to those obtained from similar classification of longer texts. Several approaches have been employed to extend traditional methods to overcome this problem, including the enhancement of the original texts through the construction of associations with external data enrichment sources, ranging from thesauri and semantic nets such as Wordnet, to pre-built online taxonomies such as Wikipedia. Other avenues of investigation have …
Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, Malachy Mathews, Dan Robles, Brian Bowe
Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, Malachy Mathews, Dan Robles, Brian Bowe
Conference papers
This paper provides an overview of historic and current organizational limitations emerging in the Architecture, Engineering, Construction, Building Owner / Operations (AECOO) Industry. It then provides an overview of new technologies that attempt to mitigate these limitations. However, these technologies, taken together, appear to be converging and creating entirely new organizational structures in the AEC industries. This may be characterized by the emergence of what is called the Network Effect and it’s related calculus. This paper culminates with an introduction to Blockchain Technology (BT) and it’s integration with the emergence of groundbreaking technologies such as Internet of Things (IoT), Artificial …
Key Inference From Irish Traditional Music Scores And Recordings, Pierre Beauguitte, Bryan Duggan, John D. Kelleher
Key Inference From Irish Traditional Music Scores And Recordings, Pierre Beauguitte, Bryan Duggan, John D. Kelleher
Conference papers
The aim of this paper is to present techniques and results for identifying the key of Irish traditional music melodies, or tunes. Several corpora are used, consisting of both symbolic and audio representations. Monophonic and heterophonic recordings are present in the audio datasets. Some particularities of Irish traditional music are discussed, notably its modal nature. New key-profiles are defined, that are better suited to Irish music.
Chaos-Based Cryptography For Cloud Computing, Paul Tobin, Lee Tobin, Michael Mckeever, Jonathan Blackledge
Chaos-Based Cryptography For Cloud Computing, Paul Tobin, Lee Tobin, Michael Mckeever, Jonathan Blackledge
Conference papers
Cloud computing and poor security issues have quadrupled over the last six years and with the alleged presence of backdoors in common encryption ciphers, has created a need for personalising the encryption process by the client. In 2007, two Microsoft employees gave a presentation ``On the Possibility of a backdoor in the NIST SP800-90 Dual Elliptic Curve Pseudo Random Number Generators'' and was linked in 2013 by the New York Times with notes leaked by Edward Snowden. This confirmed backdoors were placed, allegedly, in a number of encryption systems by the National Security Agency, which if true creates an urgent …
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge
Conference papers
In this paper, we examine the design and application of a one-time pad encryption system for protecting data stored in the Cloud. Personalising security using a one-time pad generator at the client-end protects data from break-ins, side-channel attacks and backdoors in public encryption algorithms. The one-time pad binary sequences were obtained from modified analogue chaos oscillators initiated by noise and encoded client data locally. Specific ``one-to-Cloud'' storage applications returned control back to the end user but without the key distribution problem normally associated with one-time pad encryption. Development of the prototype was aided by ``Virtual Prototyping'' in the latest version …
Auto Generation Of Xliff Translation Documents From Proprietary File Formats, Kieran O'Connor, Geraldine Gray
Auto Generation Of Xliff Translation Documents From Proprietary File Formats, Kieran O'Connor, Geraldine Gray
The ITB Journal
The handling of proprietary documents by localisation vendors is time consuming and error prone, and represents a significant challenge to localisation projects. Vendors with many customers, each with its own set of document formats, must potentially support a document format set numbering in the hundreds or thousands. This paper describes an approach to automating the extraction of translatable text from a variety of file formats. The solution is based on XLIFF, language parsers, and XML transformations.
Developing Real-Time Multimedia Conferencing Services Using Java And Sip, Gavin Byrne, Declan Barber
Developing Real-Time Multimedia Conferencing Services Using Java And Sip, Gavin Byrne, Declan Barber
The ITB Journal
This paper examines Java's suitability in creating real-time multimedia communications-based applications in Next Generation Networks (NGNs). We investigate some of the current enabling technologies provided by the Java plaiform which are concerned with the rapid development of realtime communications-based products and services. In particular, we look at creating a multiparty conferencing and collaboration service using the Session Initiation Protocol (SIP) and the JAIN Framework and present an approach which models multiparty conferencing applications by separating signaling and media transfer functionality. We map our model through the design stage to an implementation in Java. This paper is based on real experiences …
Web Enabled Embedded Devices, Anthony Keane, Brian Myler
Web Enabled Embedded Devices, Anthony Keane, Brian Myler
The ITB Journal
The trend in manufacturing of computerised control systems has been to miniaturise the components while increasing the functionality of the systems. This has led to the development of small inexpensive hand-held computer devices coupled with the availability of a user friendly application development language, Java and public cost-effect communication networks has given the developer a programmable web-enabled embedded device. This paper investigates the steps involved in programming the Tiny InterNet Interface platform and analyses the limitations imposed by miniaturisation on this device.