Application of Artificial Intelligence Approaches in the Flood Management Process for Assessing Blockage at Cross-Drainage Hydraulic Structures

Floods are the most recurrent, widespread and damaging natural disasters, and are ex-pected to become further devastating because of global warming. Blockage of cross-drainage hydraulic structures (e.g., culverts, bridges) by flood-borne debris is an influen-tial factor which usually results in reducing hydraulic capacity, diverting the flows, dam-aging structures and downstream scouring. Australia is among the countries adversely impacted by blockage issues (e.g., 1998 floods in Wollongong, 2007 floods in Newcas-tle). In this context, Wollongong City Council (WCC), under the Australian Rainfall and Runoff (ARR), investigated the impact of blockage on floods and proposed guidelines to consider blockage in the design process for the first time. However, existing WCC guide-lines are based on various assumptions (i.e., visual inspections as representative of hy-draulic behaviour, post-flood blockage as representative of peak floods, blockage remains constant during the whole flooding event), that are not supported by scientific research while also being criticised by hydraulic design engineers. This suggests the need to per-form detailed investigations of blockage from both visual and hydraulic perspectives, in order to develop quantifiable relationships and incorporate blockage into design guide-lines of hydraulic structures. However, because of the complex nature of blockage as a process and the lack of blockage-related data from actual floods, conventional numerical modelling-based approaches have not achieved much success. The research in this thesis applies artificial intelligence (AI) approaches to assess the blockage at cross-drainage hydraulic structures, motivated by recent success achieved by AI in addressing complex real-world problems (e.g., scour depth estimation and flood inundation monitoring). The research has been carried out in three phases: (a) litera-ture review, (b) hydraulic blockage assessment, and (c) visual blockage assessment. The first phase investigates the use of computer vision in the flood management domain and provides context for blockage. The second phase investigates hydraulic blockage using lab scale experiments and the implementation of multiple machine learning approaches on datasets collected from lab experiments (i.e., Hydraulics-Lab Dataset (HD), Visual Hydraulics-Lab Dataset (VHD)). The artificial neural network (ANN) and end-to-end deep learning approaches reported top performers among the implemented approaches and demonstrated the potential of learning-based approaches in addressing blockage is-sues. The third phase assesses visual blockage at culverts using deep learning classifi-cation, detection and segmentation approaches for two types of visual assessments (i.e., blockage status classification, percentage visual blockage estimation). Firstly, a range of existing convolutional neural network (CNN) image classification models are imple-mented and compared using visual datasets (i.e., Images of Culvert Openings and Block-age (ICOB), VHD, Synthetic Images of Culverts (SIC)), with the aim to automate the process of manual visual blockage classification of culverts. The Neural Architecture Search Network (NASNet) model achieved best classification results among those im-plemented. Furthermore, the study identified background noise and simplified labelling criteria as two contributing factors in degraded performance of existing CNN models for blockage classification. To address the background clutter issue, a detection-classification pipeline is proposed and achieved improved visual blockage classification performance. The proposed pipeline has been deployed using edge computing hardware for blockage monitoring of actual culverts. The role of synthetic data (i.e., SIC) on the performance of culvert opening detection is also investigated. Secondly, an automated segmentation-classification deep learning pipeline is proposed to estimate the percentage of visual blockage at circular culverts to better prioritise culvert maintenance. The AI solutions proposed in this thesis are integrated into a blockage assessment framework, designed to be deployed through edge computing to monitor, record and assess blockage at cross-drainage hydraulic structures

Exploring the human factors in moral dilemmas of autonomous vehicles

Given the widespread popularity of autonomous vehicles (AVs), researchers have been exploring the ethical implications of AVs. Researchers believe that empirical experiments can provide insights into human characterization of ethically sound machine behaviour. Previous research indicates that humans generally endorse utilitarian AVs; however, this paper explores an alternative account of the discourse of ethical decision-making in AVs. We refrain from favouring consequentialism or non-consequential ethical theories and argue that human moral decision-making is pragmatic, or in other words, ethically and rationally bounded, especially in the context of intelligent environments. We hold the perspective that our moral preferences shift based on various externalities and biases. To further this concept, we conduct three Amazon Mechanical Turk studies, comprising 479 respondents to investigate factors, such as the “degree of harm,” “level of affection,” and “fixing the responsibility” that influences people’s moral decision-making. Our experimental findings seem to suggest that human moral judgments cannot be wholly deontological or utilitarian and offer evidence on the ethical variations in human decision-making processes that favours a specific moral framework. The findings also offer valuable insights for policymakers to explore the overall public perception of the ethical implications of AV as part of user decision-making in intelligent environments

Simulator based performance metrics to estimate reliability of control room operators

Chemical processes rely on several layers of protection to prevent accidents. One of the most important layers of protection is human operators. Human errors are a key contributor in a majority of accidents today. Estimation of human failure probabilities is a challenge due to the numerous drivers of human error, and still heavily dependent on expert judgment. In this paper, we propose a strategy to estimate the reliability of control room operators by measuring their control performance on a process simulator. The performance of the operator is translated to two metrics - margin-of-failure and available-time to respond to process events - which can be calculated using process operations data that can be generated from training simulator based studies. These metrics offer a qualitative estimate of operators' reliability. We conducted a set of experiments involving 128 students of differing capabilities from two different institutions and tasked to control a simulated ethanol production plant. Our results demonstrate that differences in the performance of expert vs. novice student operators can be clearly distinguished using the metrics

Assisting People of Determination and the Elderly Using Social Robot: A Case Study

A technological innovation that has recently garnered attention in the literature is social humanoid robots' applications. Ever since their commercialization, social robots have been viewed as a valuable tool to assist individuals in their daily activities. As people grow older, their capabilities to accomplish everyday activities gradually deteriorate. Consequently, there is a pressing need for research on the positive benefits offered by humanoid robots. This paper explores the implications of a social robot, Zenbo, in the United Arab Emirates (UAE). We propose that the Zenbo be helpful in assisting vulnerable elderly populations, ordinary citizens, and People of Determination. This study can guide the UAE policymakers to allow elderly peoples and disabled individuals to use Zenbo to ensure their safety and well-being. This technological advancement can help transform the traditional support systems offered to the vulnerable populations in the Middle East

Social Robots in Retail: Emotional Experiences a Critical Driver of Purchase Intention

The purpose of the current study is to explore whether emotional experiences prompted due to human-social robot interaction in retail environments significantly influence consumers' purchase intentions. This present study focuses primarily on emotional experience, comprising factors, namely, enjoyment, arousal, and emotional involvement. The study tests the conceptual model on a sample of 229 respondents using the PLS-SEM (Partial Least Squares – Structural Equation Modeling) approach. The results reveal that emotional experiences significantly impact consumers’ purchase intentions in retail settings. All three emotional experiences, including enjoyment, emotional involvement, and arousal were significant in shaping consumers' purchase intentions. The study findings offer unique insights for manufacturers developing social robots for the retail sector. The present research extends the current body of work exploring hedonic predictors of consumers' purchase intentions in novel socio-technical contexts, such as social robotics

A comparative assessment of human factors in cybersecurity: Implications for cyber governance

This paper provides an extensive overview of cybersecurity awareness in the young, educated, and technology-savvy population of the United Arab Emirates (UAE), compared to the United States of America (USA) for advancing the scholarship and practice of global cyber governance. We conducted comparative empirical studies to identify differences in specific human factors that affect cybersecurity behaviour in the UAE and the USA. In addition, we employed several control variables to observe reliable results. We used Hofstede’s theoretical framework on culture to advance our investigation. The results show that the targeted population in the UAE exhibits contrasting interpretations of cybersecurity awareness of critical human factors as compared to their counterparts from the USA. We identify possible explanations for this relatively different behaviour in the UAE population. Our key contributions are to provide valuable information for cybersecurity policymakers in the UAE and Gulf Cooperation Council (GCC) region to further enhance cyber safety, governance, awareness, and trust among citizens

Can Seasonal Thermal Energy Storage with Solar Thermal Collectors Provide the Heating Demand for Norwegian Households?

Problemstillingen for denne oppgaven var å se om sesonglagring av termisk energi kan bidra til at solfangere alene kan benyttes til oppvarming av boliger i Norge. Problemstillingen kommer fram som et alternativ til konvensjonelle oppvarmingsteknologier for å kunne kontre en eventuell framtidig økning i energiforbruket. Rundt tre fjerdedeler av energibruken til husholdningene går til oppvarming og en slik løsning vil komme godt med. Det ses på andre muligheter også hvor solfangere og BTES (Borehole Thermal Storage Energy) er med som supplement til andre oppvarmingsmetoder. Det er mer enn nok solenergi tilgjengelig i verden til å kunne dekke verdens energibehov. For denne oppgaven er det sett på solfangere som et alternativ for oppvarming av varmtvann og romoppvarming for boliger. Solfangere leverer varme fra solinnstråling ved oppvarmet varmemedium. Utfordringa med solfangere i Norge er at varmen solfangerne fanger, blir fanget på sommeren. Nesten alt av forbruk skjer om vinteren, bortsett ifra for oppvarming av varmtvann som står for 15 % av det totale energiforbruket til husholdningene. En løsning på utfordringa med lagring av varme fra sommer til vinteren er sesonglagring av varme. Sesonglagring av varme vil si at en lagrer overskuddsvarmen solfangerne leverer om sommeren til vinteren. UTES-systemer (Underground Thermal Storage Energy) som BTES og ATES (Aquifer Thermal Energy Storage) er sett på i denne oppgaven. ATES viser seg å ikke være passende for Norge. BTES på sin side er avhengig av varmeledningsevnen til berggrunnen der den ønskes boret. BTES fungerer ved at varmemediet føres gjennom borehullene som varmer opp grunnen rundt borehullene. Om vinteren når en ønsker å hente varme fra BTES systemet vil varmemediet bli varmet opp ved at varmemediet ført gjennom borehullene får varme tilført fra grunnen. Resultatene viser at Solfanger-BTES-system, ikke vil klare å levere nok varme til å kunne dekke oppvarmingsbehovet alene. På en annen side er det mulig å dekke deler av behovet som supplement til konvensjonelle oppvarmingsteknologier.The objective of this thesis was to see if seasonal thermal energy storage could contribute to solar thermal collectors, being able to provide the heating needs for a household in Norway. The issue of increased energy consumption in the future is the reasoning behind this thesis. As three fourths of the energy consumption of households is to space heating and water heating, such a solution would significantly decrease the need for increased energy production in the future. In this thesis, I also look at other options, as for example a solution were solar collectors with BTES (Borehole Thermal Storage Energy) is a supplement to other heating methods. The solar energy earth receives is more than enough to supply the world with its energy demands. For this thesis, solar thermal collectors are looked at as an alternative to conventional heating methods for space and water heating. The issue for solar thermal collectors in Norway, is the issue of the energy being collected in the summer while most of the need for the energy is in the winter. In the summer period, only water heating is needed, and water heating is only 15 % of the entire energy consumption of a household while space heating is between 60-70 %. Seasonal thermal energy storage of the excess energy collected during the summer is a solution to the issue at hand. The excess heat from the summer is stored and then used during the winter. UTES-systems (Underground Thermal Storage Energy) as BTES and ATES (Aquifer Thermal Energy Storage) are looked at in this thesis. ATES is showed to not be suitable for Norway. While BTES is dependent on the thermal conductivity of the bedrock. BTES-system operates with a heat transfer fluid running through the system. During the summer, the heat transfer fluid provides heat to the bedrock, which is warmed up. During the winter, the bedrock warms up the heat transfer fluid. The results show that solar thermal collectors with BTES-system are not able to meet the entire heating needs of a household alone. As a supplementary heating unit with conventional heating methods, it may be able to contribute to a households needs.M-I

Persuasive Technology in Games: A Brief Review and Reappraisal

Persuasive technology is a new field of research that has attracted considerable attention from game designers since there is a growing interest in games promoting positive behavioral changes. Persuasive games have been exploited to tremendous effect with applications ranging from mobile healthcare, which persuade users to exercise more often and adopt a healthy lifestyle, to government programs encouraging civic engagement. Therefore, persuasive technologies have become an indispensable part of the modern game designer’s toolkit, and their importance is only set to grow with time. In this paper, we begin by reviewing the existing body of work in this field while also explaining the pros and cons of emerging design models and theoretical frameworks. We then uncover major pitfalls in the current work and suggest directions for future research. Hopefully, this article will prove instructive to game designers and leave them with a better understanding of the central concepts in the field of persuasive technology

An Alternate Account on the Ethical Implications of Autonomous Vehicles

Given the widespread popularity of Autonomous Vehicles (AVs), researchers have been exploring the ethical implications of AVs. Researchers believe that empirical experiments can provide insights into human characterization of ethically sound machine behavior. Previous research indicates that humans generally endorse utilitarian AVs, however, this paper explores an alternative account on the discourse of ethical decision-making in AVs. We refrain from favoring consequentialism or non-consequential ethical theories, and argue that human moral decision-making is pragmatic, or in other words, ethically and rationally bounded. We hold the perspective that our moral preferences shift based on various externalities and biases. To further this concept, we conduct two Amazon Mechanical Turk studies to investigate factors, such as, the \u27degree of harm\u27, and \u27level of affection\u27, which influence people\u27s moral decision-making. Our experimental findings seem to suggest that human moral judgements cannot be wholly deontological or utilitarian. We discovered that as the degree of harm decreased, people became less utilitarian (more deontological), and as the level of affection increased, people became less utilitarian (more deontological). These findings offer evidence on the ethical variations in human decision-making processes and refutes the view that aim to advocate application of a specific moral framework based on empirical evidence. The findings also offer useful insights for policymakers to explore the overall public perception on the ethical implications of AV

On Software Implementation of High Performance GHASH Algorithms

There have been several modes of operations available for symmetric key block ciphers, among which Galois Counter Mode (GCM) of operation is a standard. GCM mode of operation provides confidentiality with the help of symmetric key block cipher operating in counter mode. The authentication component of GCM comprises of Galois hash (GHASH) computation which is a keyed hash function. The most important component of GHASH computation is carry-less multiplication of 128-bit operands which is followed by a modulo reduction. There have been a number of schemes proposed for efficient software implementation of carry-less multiplication to improve performance of GHASH by increasing the speed of multiplications. This thesis focuses on providing an efficient way of software implementation of high performance GHASH function as being proposed by Meloni et al., and also on the implementation of GHASH using a carry-less multiplication instruction provided by Intel on their Westmere architecture. The thesis work includes implementation of the high performance GHASH and its comparison to the older or standard implementation of GHASH function. It also includes comparison of the two implementations using Intel’s carry-less multiplication instruction. This is the first time that this kind of comparison is being done on software implementations of these algorithms. Our software implementations suggest that the new GHASH algorithm, which was originally proposed for the hardware implementations due to the required parallelization, can't take advantage of the Intel carry-less multiplication instruction PCLMULQDQ. On the other hand, when implementations are done without using the PCLMULQDQ instruction the new algorithm performs better, even if its inherent parallelization is not utilized. This suggest that the new algorithm will perform better on embedded systems that do not support PCLMULQDQ