A Feature Selection Method for Multivariate Performance Measures

Feature selection with specific multivariate performance measures is the key to the success of many applications, such as image retrieval and text classification. The existing feature selection methods are usually designed for classification error. In this paper, we propose a generalized sparse regularizer. Based on the proposed regularizer, we present a unified feature selection framework for general loss functions. In particular, we study the novel feature selection paradigm by optimizing multivariate performance measures. The resultant formulation is a challenging problem for high-dimensional data. Hence, a two-layer cutting plane algorithm is proposed to solve this problem, and the convergence is presented. In addition, we adapt the proposed method to optimize multivariate measures for multiple instance learning problems. The analyses by comparing with the state-of-the-art feature selection methods show that the proposed method is superior to others. Extensive experiments on large-scale and high-dimensional real world datasets show that the proposed method outperforms $l_1$-SVM and SVM-RFE when choosing a small subset of features, and achieves significantly improved performances over SVM$^{perf}$ in terms of $F_1$-score

Fast and Robust Rank Aggregation against Model Misspecification

In rank aggregation, preferences from different users are summarized into a total order under the homogeneous data assumption. Thus, model misspecification arises and rank aggregation methods take some noise models into account. However, they all rely on certain noise model assumptions and cannot handle agnostic noises in the real world. In this paper, we propose CoarsenRank, which rectifies the underlying data distribution directly and aligns it to the homogeneous data assumption without involving any noise model. To this end, we define a neighborhood of the data distribution over which Bayesian inference of CoarsenRank is performed, and therefore the resultant posterior enjoys robustness against model misspecification. Further, we derive a tractable closed-form solution for CoarsenRank making it computationally efficient. Experiments on real-world datasets show that CoarsenRank is fast and robust, achieving consistent improvement over baseline methods

Addressing decision making for remanufacturing operations and design-for-remanufacture

Remanufacturing is a process of returning a used product to at least original equipment manufacturer original performance specification from the customers' perspective and giving the resultant product a warranty that is at least equal to that of a newly manufactured equivalent. This paper explains the need to combine ecological concerns and economic growth and the significance of remanufacturing in this. Using the experience of an international aero-engine manufacturer it discusses the impact of the need for sustainable manufacturing on organisational business models. It explains some key decision-making issues that hinder remanufacturing and suggests effective solutions. It presents a peer-validated, high-level design guideline to assist decision-making in design in order to support remanufacturing. The design guide was developed in the UK through the analysis of selections of products during case studies and workshops involving remanufacturing and conventional manufacturing practitioners as well as academics. It is one of the initial stages in the development of a robust design for remanufacture guideline

Burden of Proof:The Debate Surrounding Aerotoxic Syndrome

Since the 1980s, some commercial airline pilots and flight crews in the United States, United Kingdom and Australia began to report an illness they believed was caused by exposure to contaminated cabin air. Despite a body of scientific research and health activism calling for this condition, termed Aerotoxic Syndrome (AS), to be classified an occupational illness, it has not been accepted as a clinical entity because its causation remains contested. This article contends that debates over the recognition of AS have been shaped by the politics of science and what can be considered evidence of a causal link; the burden of proof lay with survivors and their allies rather than with airlines and manufacturers. The history of AS shows the challenges of reacting to health risks in a global industry that provides an important form of transportation, and enjoys considerable political and economic influence. It also reveals that at the heart of commercial jet air travel remains an unresolved public health issue, and those who claim to be suffering from AS expected prompt recognition, reform and assistance in light of scientific research and personal testimony, as well as a range of chemical, medical, legal and air safety reports

The impact of the climate emergency on 21st century fiction

This research supports a new movement in contemporary literature: cli-fi. The term has been attributed to environmental dystopias as far back as the nineteen-sixties. In the 21st Century, many writers are imagining life during or after severe changes to Earth’s climate. While science fiction, speculative fiction and dystopia are the lending genres exploring effects of climate change, the climate emergency has started to pervade contemporary fiction.The first half of this thesis explores Atwood’s MaddAddam trilogy. The trilogy is the focus in this thesis because it considers how humans will react to catastrophic climate change in the greatest depth. MaddAddam is a cornerstone of the cli-fi movement, a journey into a possible future in which human life reaches its penultimate chapter. Atwood’s trilogy proves that, when writing in the era of climate emergency, the threat of the changing climate can become a writer’s most evocative subject.The second part of this thesis explores cli-fi in the UK, focusing on Ben Smith’s Doggerland and Sarah Hall’s The Carhullan Army. The finding in these British novels was that setting is thrust more into the spotlight, whereas in American Literature, tropes such as Malthusian biological terrorism and religious extremism are more prominent. British writers seem concerned with political structures and resistance, whereas North American writers challenge more the ideologies which hold up political structures: religion, capitalism and consumerism, the dependence on fossil fuels. While cli-fi on both sides of the Atlantic has an interesting relationship with history and reflection, the British novels seem more philosophical: both aspects of cli-fi provoke stern self-examination in the reader.Finally, there is a section from the Wyke, the creative writing project undertaken alongside this research. The aim was to write a novel which could be considered popular by a mainstream readership

HaskHOL: A Haskell Hosted Domain Specific Language for Higher-Order Logic Theorem Proving

HaskHOL is an implementation of a HOL theorem proving capability in Haskell. Motivated by a need to integrate theorem proving capabilities into a Haskell-based tool suite, HaskHOL began as a simple port of HOL Light to Haskell. However, Haskell's laziness, immutable data, and monadic extensions both complicate an implementation and enable a new feature class. This thesis describes HaskHOL, its motivation and implementation. Its use to implement a primitive, interactive theorem prover is explored and its performance is evaluated using a collection of intuitionistically valid problems