Computer Engineering Commons^™

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Dipadua

Dissertations

Stock forecasting is an enticing and well-studied problem in both finance and machine learning literature with linear-based models such as ARIMA and ARCH to non-linear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro- and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill-suitability of technicals as model inputs, this …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Di Padua

Dissertations

Stock forecasting is an enticing and well studied problem in both finance and machine learning literature with linear based models such as ARIMA and ARCH to nonlinear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill suitability of technicals as …

Using Spatialisation To Support Exploratory Search Behaviour, Clement Roux

Dissertations

Information-seekers traditionally interact with digital content through keyword-based search interfaces displaying results in list views. Well-defined lookup search tasks are performed brilliantly with these interfaces, enabling users to find relevant information and develop a relative understanding of the underlying information space. However, it is feasible to suggest that ill-defined and abstract search tasks could be better supported with a different interface that could allow the user to explore a library’s content and develop an appropriate mental model of the information space. One such approach is based on the use of visualisation, an approach to data analysis that aims to reduce …

A Regression Study Of Salary Determinants In Indian Job Markets For Entry Level Engineering Graduates, Rajveer Singh

Dissertations

The economic liberalisation of Indian markets in early 90s boosted the economic growth of the nation in various sectors over the next two decades. One such sector that has seen a massive growth in this time is Information Technology (IT). The IT industry has played a very crucial role in transforming India from a slow moving economy to one of the largest exporters of IT services. This growth created a huge demand in the labour markets for skilled labour, which in turn made engineering one of the top choices of study after high school over the years. In addition, the …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …

An Exploration Of The Impact Of Animal Agriculture On Human Sustainable Development Index And The Child Health Indicator, Hithesan Pandian

Dissertations

Several studies have shown that animal agriculture is one of the major contributors to climate change due to greenhouse gas emissions, deforestation, land degradation, freshwater shortages, general environmental pollution and world hunger. Apart from this, meat consumption is strongly associated with certain fatal health conditions such as cancer, cardiovascular disease and diabetes (Wu, 2014). Although meat production and export could be economically beneficial in the short run, it could lead to over-exploitation of natural resources and in turn the destruction of the environment in the long run. Hence, it is essential for the leaders of a nation to make smart …

Multi-Sensory Emotion Recognition With Speech And Facial Expression, Qingmei Yao

Dissertations

Emotion plays an important role in human beings’ daily lives. Understanding emotions and recognizing how to react to others’ feelings are fundamental to engaging in successful social interactions. Currently, emotion recognition is not only significant in human beings’ daily lives, but also a hot topic in academic research, as new techniques such as emotion recognition from speech context inspires us as to how emotions are related to the content we are uttering.

The demand and importance of emotion recognition have highly increased in many applications in recent years, such as video games, human computer interaction, cognitive computing, and affective computing. …

Subspace Methods For Portfolio Design, Onur Yilmaz

Dissertations

Financial signal processing (FSP) is one of the emerging areas in the field of signal processing. It is comprised of mathematical finance and signal processing. Signal processing engineers consider speech, image, video, and price of a stock as signals of interest for the given application. The information that they will infer from raw data is different for each application. Financial engineers develop new solutions for financial problems using their knowledge base in signal processing. The goal of financial engineers is to process the harvested financial signal to get meaningful information for the purpose.

Designing investment portfolios have always been at …

An Investigation Into The Effectiveness Of Hedonic Features In Regression Models For Domestic Rental Prices, Peter Prunty

Dissertations

Housing is a fundamental human right. Increasing rents and rising unemployment contribute to increased rates of homelessness. Traditionally housing prices are determined by supply and demand. This project will investigate the relationship between hedonic features and domestic rental prices in California and New York, using multivariate regression models. The literature outlines a number of approaches taken to model real estate pricing using hedonic regression.

Two models were created to analyse the difference between California and New York. Features were selected using correlation analysis. Some features were derived using logarithmic and dummy feature transformations. The models themselves were evaluated by assessing …

Investigation Into The Predictive Capability Of Macro-Economic Features In Modelling Credit Risk For Small Medium Enterprises, Kevin Mctiernan

Dissertations

This research project investigates the predictive capability of macro-economic features in modelling credit risk for small medium enterprises (SME/SMEs). There have been indications that there is strong correlation between economic growth and the size of the SME sector in an economy. However, since the financial crisis and consequent policies and regulations, SMEs have been hampered in attempts to access credit. It has also been noted that while there is a substantial amount of credit risk literature, there is little research on how macro-economic factors affect credit risk. Being able to improve credit scoring by even a small amount can have …

Using A Knowledge Management Approach To Support Effective Succession Planning In The Civil Service, Mary O’Donohue

Dissertations

The modern workforce is highly mobile. The challenge facing organisations is how to safeguard key expertise and knowledge in the face of staff mobility and turnover. The Irish Civil Service is still recovering from the impacts of significant loss of staff, and their knowledge and expertise, as a result of cutbacks over recent years. This project will establish the potential of using a Knowledge Management approach to support effective succession planning in the Civil Service. The literature review charts the evolution of Knowledge Management from when the phrase was first coined in 1986 through to what is considered to be …

An Exploration Of The Relationship Between The Partisan-Business Cycle And Economic Inequality Within Developed Economies, Richard O'Doherty

Dissertations

Recent contributions to the study of inequality have provided strong evidence towards the presence of an established trend, over several decades, of growing economic inequality (with a particular focus on distribution within their tails; i.e. top 10%, 1%) across countries with developed economies and indications of similar trends across developing economies. While the causality and influencing factors to these trends has widely been discussed, and has range from declining domestic growth rates as economies move towards high mass consumption states to globalisation, political decision making and policy application been referred to as both contributory or an instrument for dampening such …

Measuring The Effectiveness Of Software-Based Training To Improve The Spatial Visualization Skills Of Students In Stem Disciplines In Higher Education Institutions, Peter Cole

Dissertations

This research investigates how software can be used to teach spatial skills leading to greater success in Science, Technology, Engineering, and Mathematical (STEM) fields. Existing research indicates that spatial skills can be taught and that good spatial skills are common to people who succeed in STEM fields. In this work, a software-only testing system with a direct targeted, training intervention module was implemented to measure and teach spatial skills using mental rotations, which are believed to be one of the most significant indicators of success in STEM fields. Spatial skills were tested using a standardized and validated test that measures …

Forecasting Bike Rental Demand Using New York Citi Bike Data, Wen Wang

Dissertations

The idea of this project is from a Kaggle competition “Bike Sharing Demand”① which provides dataset of Capital Bikeshare in Washington D.C. and asked to combine historical usage patterns with weather data in order to forecast bike rental demand. This dissertation will extend this work, working with a broader range of project not only just focusing on the phrase of model building but all phases of KDD (Knowledge Discovery in Databases). This dissertation focuses on Citi Bike which is one of the biggest bike share projects in the world, collects Citi Bike data, weather data and holiday data from three …

An Evaluation Of Gamification To Assess Students’ Learning On Their Understanding Of First Year Computer Science Programming Module, Daniel Gebremichael

Dissertations

This research examines the use of gamification to develop an assessment tool, to assess students’ learning of a first year computer science module. The students’ undertaking of the first semester Programming and Algorithms module in 2015 were assessed on their knowledge of the programming language Python. The incorporation of gamification when assessing students can have various potential benefits. The research aims to identify these benefits and issues. Assessments and games have almost opposite effects on opinions on people, as games are usually expected to have an entertainment value but this is not the case for assessments. The research examines if …

How Do Teachers And Students Perceive The Utility Of Blackboard As A Distance Learning Platform? (Case Study From Taibah University, Saudi Arabia), Suad Alaofi

Dissertations

This research explores the role of Knowledge Management within the education field with a specific focus on the use of Learning Management Systems in the Distance Learning (e-learning) process. The aim of this study is to thoroughly examine how teachers and students perceive the utility of the Blackboard system as a distance learning platform. To achieve this, the study conducted qualitative interviews and quantitative questionnaire surveys with the teachers and students of Taibah University, Saudi Arabia. Questions in both data collection tools were geared towards gaining insight about how these two groups of Blackboard users view its usefulness as a …

Predicting Intake Of Applications For First Registration In The Property Registration Authority, Orlaith Mernagh

Dissertations

The motivation for this dissertation is rooted in a real business need. The Property Registration Authority is the state organisation tasked with maintaining a register of land ownership on the island of Ireland. The PRA currently faces a series of challenges; a high level of staff retiring and the inherent loss of knowledge associated with this trend, a lack of recruitment in recent years and a large increase in lodgement of applications for first registration as a result of legislation. The organisation therefore requires a reliable system for predicting future intake. Prior to this project, there has also been a …

Identifying Market Indicators And Content Quality From A Financial Micro-Blog Platform, Siobhán Mcnamara

Dissertations

Investment platforms and discussion platforms have come to change the face of finance. The stock market is open to both professional and non-professional investors via online financial channels. Information too comes via a shared domain as both professionals and non-professionals log onto online communication platforms to share, search and discuss market trends. Due to their growing role in finance, understanding online communities has become the focus of much stock market research. Determining who is influential in a network, how information spreads and what translates to buy or sell decision is potentially very lucrative. In this research paper a dataset from …