An intelligent portfolio management approach to gas storage field deliverability maintenance and enhancement

The main goal of this thesis is to modify and apply the state-of-the-art intelligent, optimum portfolio management to the gas storage field in order to optimize the return on investment associated with well remedial operations. It continues the development of a methodology for candidate selection and stimulation design and optimization using Artificial Intelligence techniques. The project used the data of an actual gas storage field to test the results.;The project data include Well-bore, Completion, Perforation, Stimulation, Well-test and Reservoir Data. The software developed in parallel with this selection methodology includes an easy to use interface that allows the user to edit the data for a gas storage field, perform well-test analysis and use neural networks in association with Genetic optimization tool. The software ranks the well according to maximum change in skin value for a well and thus a decision to re-stimulate the well or not is made accordingly

The impact of the prevent duty on schools: a review of the evidence

The UK has emerged as an influential global player in developing policy to counter violent extremism, and therefore it is important to consider the emerging evidence about the impact of this policy in education. The Prevent Duty came into force in the UK in 2015, placing a legal responsibility on schools and teachers to implement anti-terrorist legislation and prevent young people from being drawn into extremism or radicalisation. This article reviews all of the material based on empirical studies in England involving school teachers and students published between 2015 (when the Duty was introduced) and the beginning of 2019 (27 articles and reports in total) to consider the impact of the policy on schools. The key themes emerging from our analysis of this evidence base are related (1) to the ways the policy is interpreted within Islamophobic discourses, (2) the emergence of Britishness as a key feature of fundamental British values, and (3) the implications of framing Prevent as a safeguarding issue. We argue that the evidence gives support to those who have been critical of the Prevent Duty in schools, and that it seems to be generating a number of unintended and negative side effects. However, the evidence also illustrates how teachers have agency in relation to the policy, and may thus be able to enact the policy in ways which reduce some of the most harmful effects

The interrelation between data and AI ethics in the context of impact assessments

In the growing literature on artificial intelligence (AI) impact assessments, the literature on data protection impact assessments is heavily referenced. Given the relative maturity of the data protection debate and that it has translated into legal codification, it is indeed a natural place to start for AI. In this article, we anticipate directions in what we believe will become a dominant and impactful forthcoming debate, namely, how to conceptualise the relationship between data protection and AI impact. We begin by discussing the value canvas i.e. the ethical principles that underpin data and AI ethics, and discuss how these are instantiated in the context of value trade-offs when the ethics are applied. Following this, we map three kinds of relationships that can be envisioned between data and AI ethics, and then close with a discussion of asymmetry in value trade-offs when privacy and fairness are concerned

Algorithm Auditing: Managing the Legal, Ethical, and Technological Risks of Artificial Intelligence, Machine Learning, and Associated Algorithms

Algorithms are becoming ubiquitous. However, companies are increasingly alarmed about their algorithms causing major financial or reputational damage. A new industry is envisaged: auditing and assurance of algorithms with the remit to validate artificial intelligence, machine learning, and associated algorithms

Scoring a forced-choice image-based assessment of personality: A comparison of machine learning, regression, and summative approaches

Recent years have seen rapid advancements in the way that personality is measured, resulting in a number of innovative predictive measures being proposed, including using features extracted from videos and social media profiles. In the context of selection, game- and image-based assessments of personality are emerging, which can overcome issues like social desirability bias, lack of engagement and low response rates that are associated with traditional self-report measures. Forced-choice formats, where respondents are asked to rank responses, can also mitigate issues such as acquiescence and social desirability bias. Previously, we reported on the development of a gamified forced-choice image-based assessment of the Big Five personality traits created for use in selection, using Lasso regression for the scoring algorithms. In this study, we compare the machine-learning-based Lasso approach to ordinary least squares regression, as well as the summative approach that is typical of forced-choice formats. We find that the Lasso approach performs best in terms of generalisability and convergent validity, although the other methods have greater discriminate validity. We recommend the use of predictive Lasso regression models for scoring forced-choice image-based measures of personality over the other approaches. Potential further studies are suggested

Accurate <i>ab initio</i> ro-vibronic spectroscopy of the X²&#8719; CCN radical using explicitly correlated methods

Explicitly correlated CCSD(T)-F12b calculations have been carried out with systematic sequences of correlation consistent basis sets to determine accurate near-equilibrium potential energy surfaces for the X&lt;sup&gt;2&lt;/sup&gt;&#8719; and a&lt;sup&gt;4&lt;/sup&gt;&#931;&lt;sup&gt;−&lt;/sup&gt; electronic states of the CCN radical. After including contributions due to core correlation, scalar relativity, and higher order electron correlation effects, the latter utilizing large-scale multireference configuration interaction calculations, the resulting surfaces were employed in variational calculations of the ro-vibronic spectra. These calculations also included the use of accurate spin-orbit and dipole moment matrix elements. The resulting ro-vibronic transition energies, including the Renner-Teller sub-bands involving the bending mode, agree with the available experimental data to within 3 cm&lt;sup&gt;−1&lt;/sup&gt; in all cases. Full sets of spectroscopic constants are reported using the usual second-order perturbation theory expressions. Integrated absorption intensities are given for a number of selected vibronic band origins. A computational procedure similar to that used in the determination of the potential energy functions was also utilized to predict the formation enthalpy of CCN, &#916;H&lt;sub&gt;f&lt;/sub&gt;(0K) = 161.7 &#177; 0.5 kcal/mol

The Role of Technology Entrepreneurship in Higher Education Sector of Developing Countries: A Case Study of Pakistan

In modern theories of growth and development, technological innovation has taken the focus stage and such innovations are commercialized by technology entrepreneurs. Colleges and universities are investing heavily in the development of their student’s entrepreneurial skills and have tremendous impact on innovation and entrepreneurial development. Universities today equally function as an important driving force to enhance economic value by creation of networks with innovators across a region through their incubators and scientific and technology parks. In developed countries many entrepreneurs start up their companies at their universities but in developing countries there are so many challenges yet to be faced by new starts up. Technology entrepreneurship in education basically explores how technology entrepreneurs are applying business practices or technology innovations to transform education to lead to higher performance. As higher education industry is changing radically and that transformation is worth for commercial benefits of businesses and also for innovative startups. Today the presence of colleges and universities are not only meant to be the gatekeeper of knowledge and information instead various innovators are in flowing as entrepreneurs in education industry. This study will explore that in what ways technology entrepreneurship is facilitating the educator sector of the emerging economies specifically in Pakistan. Keywords: Technology entrepreneurship, High Education Sector, Developing economies, Business Incubation Centers

Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem

In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national AI and data strategies, as well as a transparency standard. Extending these efforts, the Centre for Data Ethics and Innovation (CDEI) has published an AI Assurance Roadmap, which is the first of its kind and provides guidance on how to manage the risks that come from the use of AI. In this article, we provide an overview of the document's vision for a “mature AI assurance ecosystem” and how the CDEI will work with other organizations for the development of regulation, industry standards, and the creation of AI assurance practitioners. We also provide a commentary of some key themes identified in the CDEI's roadmap in relation to (i) the complexities of building “justified trust”, (ii) the role of research in AI assurance, (iii) the current developments in the AI assurance industry, and (iv) convergence with international regulation