Digital Commons Network^™

Brexit: Psychometric Profiling The Political Salubrious Through Machine Learning: Predicting Personality Traits Of Boris Johnson Through Twitter Political Text, James Usher, Pierpaolo Dondio

Conference papers

Whilst the CIA have been using psychometric profiling for decades, Cambridge Analytica showed that people's psychological characteristics can be accurately predicted from their digital footprints, such as their Facebook or Twitter accounts. To exploit this form of psychological assessment from digital footprints, we propose machine learning methods for assessing political personality from Twitter. We have extracted the tweet content of Prime Minster Boris Johnson’s Twitter account and built three predictive personality models based on his Twitter political content. We use a Multi-Layer Perceptron Neural network, a Naive Bayes multinomial model and a Support Machine Vector model to predict the OCEAN …

Brain Disease Detection From Eegs: Comparing Spiking And Recurrent Neural Networks For Non-Stationary Time Series Classification, Hristo Stoev

Dissertations

Modeling non-stationary time series data is a difficult problem area in AI, due to the fact that the statistical properties of the data change as the time series progresses. This complicates the classification of non-stationary time series, which is a method used in the detection of brain diseases from EEGs. Various techniques have been developed in the field of deep learning for tackling this problem, with recurrent neural networks (RNN) approaches utilising Long short-term memory (LSTM) architectures achieving a high degree of success. This study implements a new, spiking neural network-based approach to time series classification for the purpose of …

Content-Based Filtering Recommendation Approach To Label Irish Legal Judgements, Sandesh Gangadhar

Dissertations

Machine learning approaches are applied across several domains to either simplify or automate tasks which directly result in saved time or cost. Text document labelling is one such task that requires immense human knowledge about the domain and efforts to review, understand and label the documents. The company Stare Decisis summarises legal judgements and labels them as they are made available on Irish public legal source www.courts.ie. This research presents a recommendation-based approach to reduce the time for solicitors at Stare Decisis by reducing many numbers of available labels to pick from to a concentrated few that potentially contains the …

Optimization Of Home Mortgage Mover Predictive Model Applying Geo-Spatial Analysis And Machine Learning Techniques, Natalia Riscovaia

Dissertations

In the last decade digital innovations and online banking services have significantly changed customers banking preferences and behaviour. Banking industry is going through the changes and developments in the provision of banking services that are affecting the structure and the organization of the bank network. However, private home loan, referred as Home Mortgage hereinafter, continue to remain among the products, that customers prefer to have personal interaction about with professional advisors prior making the decision to apply for the loan with financial institution.

Synthetic Data Generation Using Wasserstein Conditional Gans With Gradient Penalty (Wcgans-Gp), Manhar Singh Walia

Dissertations

With data protection requirements becoming stricter, the data privacy has become increasingly important and more crucial than ever. This has led to restrictions on the availability and dissemination of real-world datasets. Synthetic data offers a viable solution to overcome barriers of data access and sharing. Existing data generation methods require a great deal of user-defined rules, manual interactions and domainspecific knowledge. Moreover, they are not able to balance the trade-off between datausability and privacy. Deep learning based methods like GANs have seen remarkable success in synthesizing images by automatically learning the complicated distributions and patterns of real data. But they …

Improving Transfer Learning For Use In Multi-Spectral Data, Yuvraj Sharma

Dissertations

Recently Nasa as well as the European Space Agency have made observational satellites images public. The main reason behind opening it to public is to foster research among university students and corporations alike. Sentinel is a program by the European Space Agency which has plans to release a series of seven satellites in lower earth orbit for observing land and sea patterns. Recently huge datasets have been made public by the Sentinel program. Many advancements have been made in the field of computer vision in the last decade. Krizhevsky, Sutskever & Hinton, 2012, revolutionized the field of image analysis by …

Research And Innovation As A Catalyst For Food System Transformation, A.C.L. Den Boer, K.P.W. Kok, M. Gill, J. Breda, Jean Cahill, C. Callenius, P. Caron, Z. Damianova, M. Gurinovic, L. Lahteenmaki, T. Lang, R. Sonnino, G. Verburg, H. Westhoek, T. Cesuroglu, B.J. Regeer, J.E.W. Broerse

Research and Innovation - Other

Background Food systems are associated with severe and persistent problems worldwide. Governance approaches aiming to foster sustainable transformation of food systems face several challenges due to the complex nature of food systems.

Scope and approach In this commentary we argue that addressing these governance challenges requires the development and adoption of novel research and innovation (R&I) approaches that will provide evidence to inform food system transformation and will serve as catalysts for change. We first elaborate on the complexity of food systems (transformation) and stress the need to move beyond traditional linear R&I approaches to be able to respond to …

Β-Methylumbelliferone Surface Modification And Permeability Investigations At Pentel™ Graphite Electrodes, Susan Warren, Brian Seddon, Ruth Pilkington, Alison Crossely, Philip Holdway, Eithne Dempsey

Articles

Electrochemical and micro-imaging analysis of a commercial graphite-composite material is presented following electro-oxidation with β-methylumbelliferone. Charge-transfer surface modification was observed for the graphite electrode, presumed to have arisen from adsorbed interfacial umbelliferone moieties. The molecular permeability of the new surface towards a range of similar, yet size-variable (23 Å3–136 Å3) molecular redox probes is discussed. Red-shift fluorescence in confocal microscopy offers further support for the presence of a surface-bound umbelliferone layer. An SEM-platinum profiling technique was used as an imaging tool to map the umbelliferone surface and size-distribution of electroactive sites.

Audio Interval Retrieval Using Convolutional Neural Networks, Ievgeniia Kuzminykh, Dan Shevchuk, Stavros Shiaeles, Bogdan Ghita

School of Engineering, Computing and Mathematics

No abstract provided.

Model Comparison From Ligo-Virgo Data On Gw170817'S Binary Components And Consequences For The Merger Remnant, B. P. Abbott, R. Abbott, Marco Cavaglia, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

GW170817 is the very first observation of gravitational waves originating from the coalescence of two compact objects in the mass range of neutron stars, accompanied by electromagnetic counterparts, and offers an opportunity to directly probe the internal structure of neutron stars. We perform Bayesian model selection on a wide range of theoretical predictions for the neutron star equation of state. For the binary neutron star hypothesis, we find that we cannot rule out the majority of theoretical models considered. In addition, the gravitational-wave data alone does not rule out the possibility that one or both objects were low-mass black holes. …

Robustness Metric For Robust Design Optimization Under Time-And Space-Dependent Uncertainty Through Metamodeling, Xinpeng Wei, Xiaoping Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Product performance varies with respect to time and space in many engineering applications. This paper discusses how to measure and evaluate the robustness of a product or component when its quality characteristics (QCs) are functions of random variables, random fields, temporal variables, and spatial variables. At first, the existing time-dependent robustness metric is extended to the present time-and space-dependent problem. The robustness metric is derived using the extreme value of the quality characteristics with respect to temporal and spatial variables for the nominal-the-better type quality characteristics. Then, a metamodel-based numerical procedure is developed to evaluate the new robustness metric. The …

Cagniard-Dehoop Technique-Based Computation Of Retarded Partial Coefficients: The Coplanar Case, Martin Stumpf, Giulio Antonini, Albert E. Ruehli

Electrical and Computer Engineering Faculty Research & Creative Works

Efficient computation of partial elements plays a key role in the Partial Element Equivalent Circuit (PEEC) method. A novel analytical method for computing retarded partial coefficients based on the Cagniard-DeHoop (CdH) technique is proposed. The methodology is first theoretically developed and then illustrated on the computation of a surface retarded partial coefficient pertaining to two coplanar rectangular surface elements. An efficient way for incorporating loss mechanisms in the time domain (TD) via the Schouten-Van der Pol theorem is proposed. Illustrative numerical examples demonstrating the validity of the introduced solution are given.

Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally …

Thermal Atomic Layer Deposition Of Silver Metal Films: Synthesis And Characterization Of Thermally Stable Silver Metal Precursors, Harshani Jayabahu Arachchilage

Wayne State University Dissertations

ABSTRACT

THERMAL ATOMIC LAYER DEPOSITION OF SILVER METAL FILMS: SYNTHESIS AND CHARACTERIZATION OF THERMALLY STABLE SILVER METAL PRECURSORS

by

HARSHANI JAYABAHU ARACHCHILAGE

August 2020

Advisor: Professor Charles H. Winter

Major: Chemistry (Inorganic)

Degree: Doctor of Philosophy

Traditional film deposition techniques such as PVD and CVD are widely used in the microelectronics industry. However, the lack of thickness control and conformality requirements limit these techniques for current and future applications. By contrast, ALD offers the deposition of ultra-thin conformal films with accurate thickness control due to the self-limiting growth behavior. Ag metal has the lowest resistivity (1.59 µΩ cm) of all …

Vietnamese Punctuation Prediction Using Deep Neural Networks, Thuy Pham, Nhu Nguyen, Hong Quang Pham, Han Cao, Binh Nguyen

Research Collection School Of Computing and Information Systems

Adding appropriate punctuation marks into text is an essential step in speech-to-text where such information is usually not available. While this has been extensively studied for English, there is no large-scale dataset and comprehensive study in the punctuation prediction problem for the Vietnamese language. In this paper, we collect two massive datasets and conduct a benchmark with both traditional methods and deep neural networks. We aim to publish both our data and all implementation codes to facilitate further research, not only in Vietnamese punctuation prediction but also in other related fields. Our project, including datasets and implementation details, is publicly …

Server-Aided Revocable Attribute-Based Encryption For Cloud Computing Services, Hui Cui, Tsz Hon Yuen, Robert H. Deng, Guilin Wang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) has been regarded as a promising solution in cloud computing services to enable scalable access control without compromising the security. Despite of the advantages, efficient user revocation has been a challenge in ABE. One suggestion for user revocation is using the binary tree in the key generation phase of an ABE scheme, which enables a trusted key generation center to periodically distribute the key update information to all nonrevoked users over a public channel. This revocation approach reduces the size of key updates from linear to logarithmic in the number of users. But it requires each user …

Spatial Multi-Objective Land Use Optimization Toward Livability Based On Boundary-Based Genetic Algorithm: A Case Study In Singapore, Kai Cao, Muyang Liu, Shu Wang, Mengqi Liu, Wenting Zhang, Qiang Meng, Bo Huang

Research Collection School Of Computing and Information Systems

In this research, the concept of livability has been quantitatively and comprehensively reviewed and interpreted to contribute to spatial multi-objective land use optimization modelling. In addition, a multi-objective land use optimization model was constructed using goal programming and a weighted-sum approach, followed by a boundary-based genetic algorithm adapted to help address the spatial multi-objective land use optimization problem. Furthermore, the model is successfully and effectively applied to the case study in the Central Region of Queenstown Planning Area of Singapore towards livability. In the case study, the experiments based on equal weights and experiments based on different weights combination have …

Teacher-Student Networks With Multiple Decoders For Solving Math Word Problem, Jipeng Zhang, Roy Ka-Wei Lee, Ee-Peng Lim, Wei Qin, Lei Wang, Jie Shao, Qianru Sun

Research Collection School Of Computing and Information Systems

Math word problem (MWP) is challenging due to the limitation in training data where only one “standard” solution is available. MWP models often simply fit this solution rather than truly understand or solve the problem. The generalization of models (to diverse word scenarios) is thus limited. To address this problem, this paper proposes a novel approach, TSN-MD, by leveraging the teacher network to integrate the knowledge of equivalent solution expressions and then to regularize the learning behavior of the student network. In addition, we introduce the multiple-decoder student network to generate multiple candidate solution expressions by which the final answer …

Planningvis: A Visual Analytics Approach To Production Planning In Smart Factories, Dong Sun, Renfei Huang, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu

Research Collection School Of Computing and Information Systems

Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent of industry 4.0, plenty of data recording the status of factory resources have been collected and further involved in production planning, which brings an unprecedented opportunity to understand, evaluate and adjust complex production plans through a data-driven approach. However, developing a systematic analytics approach for production planning is challenging due to the large volume of production data, the complex dependency between products, and unexpected changes in the market and the plant. Previous studies only provide …

Challenges And Trends In Sustainable Corporate Finance: A Bibliometric Systematic Review, Tad Dat Bui, Mohd Helmi Ali, Feng Ming Tsai, Mohammad Iranmanesh, Ming-Lang Tseng, Ming K. Lim

Research outputs 2014 to 2021

Sustainable corporate finance is an attractive field of study in sustainability literature; however, the literature lacks systematic bibliometric analysis that provides a comprehensive review to clarify state-of-the-art sustainable corporate finance and that discusses new opportunities and potential instructions for further studies. To address this gap, this study adopts a literature review, bibliometric analysis, network analysis and co-wording technique to systematically investigate the Scopus database. In total, 30 keywords listed at least three times are used and are divided into six clusters considering six fields of research, namely, corporate finance in corporate sustainability, sustainable competitive advantages, sustainable stakeholder engagement, circular economy, …

Applications Of Polynomial Chaos-Based Cokriging To Aerodynamic Design Optimization Benchmark Problems, Jethro Nagawkar, Leifur Leifsson, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this work, the polynomial chaos-based Cokriging (PC-Cokriging) is applied to a benchmark aerodynamic design optimization problem. The aim is to perform fast design optimization using this multifidelity metamodel. Multifidelity metamodels use information at multiple levels of fidelity to make accurate and fast predictions. Higher amount of lower fidelity data can provide important information on the trends to a limited amount of high-fidelity (HF) data. The PC-Cokriging metamodel is a multivariate version of the polynomial chaos-based Kriging (PC-Kriging) metamodel and its construction is similar to Cokriging. It combines the advantages of the interpolation-based Kriging metamodel and the regression-based polynomial chaos …

Stochastic Volatility And Garch: Do Squared End-Of-Day Returns Provide Similar Information?, David Edmund Allen

Research outputs 2014 to 2021

The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to twenty plus years of daily data for three indices. As a benchmark, I use the realized volatility (RV) for the S&P 500, DOW JONES and STOXX50 indices, sampled at 5-minute intervals, taken from the Oxford Man Realised Library. Both models demonstrate comparable performance and are correlated to a similar extent with the RV estimates, when measured by OLS. However, a crude variant of Corsi’s (2009) Heterogenous Auto-Regressive (HAR) model, applied to squared demeaned daily returns on the indices, appears to predict the daily RV of …

How Location-Aware Access Control Affects User Privacy And Security In Cloud Computing Systems, Wen Zeng, Reem Bashir, Trevor Wood, Francois Siewe, Helge Janicke, Isabel Wagner

Research outputs 2014 to 2021

The use of cloud computing (CC) is rapidly increasing due to the demand for internet services and communications. The large number of services and data stored in the cloud creates security risks due to the dynamic movement of data, connected devices and users between various cloud environments. In this study, we will develop an innovative prototype for location-aware access control and data privacy for CC systems. We will apply location-aware access control policies to role-based access control of Cloud Foundry, and then analyze the impact on user privacy after implementing these policies. This innovation can be used to address the …

Application Of A Brain-Inspired Spiking Neural Network Architecture To Odor Data Classification, Anup Vanarse, Josafath Israel Espinosa-Ramos, Adam Osseiran, Alexander Rassau, Nikola Kasabov

Research outputs 2014 to 2021

Existing methods in neuromorphic olfaction mainly focus on implementing the data transformation based on the neurobiological architecture of the olfactory pathway. While the transformation is pivotal for the sparse spike-based representation of odor data, classification techniques based on the bio-computations of the higher brain areas, which process the spiking data for identification of odor, remain largely unexplored. This paper argues that brain-inspired spiking neural networks constitute a promising approach for the next generation of machine intelligence for odor data processing. Inspired by principles of brain information processing, here we propose the first spiking neural network method and associated deep machine …

A Multipurpose Desalination, Cooling, And Air-Conditioning System Powered By Waste Heat Recovery From Submarine Diesel Exhaust Fumes And Cooling Water, Abdellah Shafieian, Mehdi Khiadani

Research outputs 2014 to 2021

The role of cooling and air-conditioning systems in submarines is assessed as indispensable, and a reliable water supply is essential for both crew and equipment. At the same time, the large amounts of high-temperature exhaust fumes discharged from submarine engines provide an excellent opportunity to recover and apply this waste energy in required applications. This paper introduces a novel multipurpose desalination, cooling, and air-conditioning system to recover waste heat from both the exhaust fumes and the cooling water of submarine engines. The whole system is mathematically modelled and analysed based on the actual thermo-physical parameters of the engine's exhaust fumes. …

Development Of A Composite Sustainability Index For Roadway Intersecttion Design Alternatives In The Uae, Maryam Juma Al-Kaabi

Theses

Many studies had been carried out to evaluate the sustainability of transportation systems, but little attention was given in these studies to the design of roadway intersections. The objective of this study was to define a framework to assess intersection sustainability from a road-user perspective and to develop a visual tool that helps decision-makers to support a more sustainable design of roadway intersections. Suitable sustainability indicators that would serve as elements in the built framework at the strategic and early planning level were extracted from the literature. The extracted indicators were utilized with relative weights to develop basic dimensional indices …

Identifying The Critical Factors Of Sustainable Manufacturing Using The Fuzzy Dematel Method, Luwei Jiang, Tenghao Zhang, Yanfei Feng

Research outputs 2014 to 2021

© 2020 Luwei Jiang et al., published by Sciendo 2020. The burgeoning trend of globalization gives rise to the formation of the manufacturing ecosystem. This study aims to identify the critical factors of sustainable manufacturing for countries and regions across the globe finding their unique ecological niches. From the perspective of the ecological niche, we develop an evaluation system of the manufacturing niche. By using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, the critical factors, and its causal relationships of the manufacturing niche can be quantified and visualized. The results indicate that: (1) the evaluation system of the …

Synergistic Effect Of Hydrophilic Nanoparticles And Anionic Surfactant On The Stability And Viscoelastic Properties Of Oil In Water (O/W) Emulations; Application For Enhanced Oil Recovery (Eor), Sarmad Al-Anssari, Zain-Ul-Abedin Arain, Haider A. Shanshool, Alireza Keshavarz, Mohammad Sarmadivaleh

Research outputs 2014 to 2021

With the rapidly increased global energy demand, great attention has been focused on utilizing nanotechnology and particularly nanofluids in enhanced oil recovery (EOR) to produce more oil from low-productivity oil reservoirs. Nanofluid flooding has introduced as one of the promising methods for enhanced oil recovery using environment-friendly nanoparticles (NPs) to be as an innovative-alternative for chemical methods of EOR. This work investigates the synergistic effects of anionic surfactant and hydrophilic silica nanoparticles on the stability and the mechanical behavior of oil in water (O/W) emulsions for their application in EOR. To achieve this, an extensive series of experiments were conducted …

Morphological And Heartwood Variation Of Santalum Macgregorii In Papua New Guinea, T. Page, G. K. Jeffrey, P. Macdonell, D. Hettiarachchi, Mary C. Boyce, A. Lata, L. Oa, G. Rome

Research outputs 2014 to 2021

© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Santalum macgregorii (sandalwood), which is endemic to the southern part of Papua New Guinea (PNG), has been heavily exploited for its fragrant heartwood and is classified as threatened across its natural range. Domestication and smallholder agroforestry offer the means to preserve remaining diversity. This study was undertaken to understand the extent of remaining natural variation to support the species’s conservation and domestication. We evaluated morphological, heartwood and essential oil characters in 126 S. macgregorii trees in five populations (districts) in PNG’s Central, Gulf and Western …

Memory And Resource Leak Defects And Their Repairs In Java Projects, Mohammadreza Ghanavati, Diego Costa, Janos Seboek, David Lo, Artur Andrzejak

Research Collection School Of Computing and Information Systems

Despite huge software engineering efforts and programming language support, resource and memory leaks are still a troublesome issue, even in memory-managed languages such as Java. Understanding the properties of leak-inducing defects, how the leaks manifest, and how they are repaired is an essential prerequisite for designing better approaches for avoidance, diagnosis, and repair of leak-related bugs. We conduct a detailed empirical study on 452 issues from 10 large opensource Java projects. The study proposes taxonomies for the leak types, for the defects causing them, and for the repair actions. We investigate, under several aspects, the distributions within each taxonomy and …