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Empathy and the ethics of posthuman reading in Never Let Me Go
Get PDFThis chapter examines a range of novels that explore the scientific creation of posthumans, notably Frankenstein (1818), Brave New World (1932), and Where Late the Sweet Birds Sang (1976), to provide a continuum within which to situate a more focused discussion of Ishiguro’s novel, in turn interrogating whether the presence of affective response in the reader is either a sufficient or necessary condition to confer the nebulous status of human onto other entities. Indeed, N. Katherine Hayles has suggested that ‘the age of the human has given way to the posthuman’, that ‘the concept of the human has given way to its evolutionary heir’, while Armstrong, seeing a comparable paradigm shift in literature, proposes that the contemporary novel ‘confront[s] us with forms of human life so innovative as to make it next to impossible for us to recognize ourselves in them’ (2016: 247; 2014: 442). With the aid of Martha Nussbaum’s work in Frontiers of Justice (2006), this essay is also an attempt to think through the literary implications, the ethics of reading in a world in which the human subject is, demonstrably, becoming a more fluid species. Much influential criticism of Ishiguro’s novel assumes a human reader, and so, as I will argue below, participates in both the anthropocentricism and human exceptionalism which it attempts, at least in principle, to challenge. I argue here that the novel as a form has always posed questions about human nature and human identity; that empathising in and with novels does not extend to real world altruism; and, that Armstrong exemplifies a strand of criticism which assumes a human reader (ourselves) of the posthuman (other), placing an implicit bias on reading as a human. Armstrong powerfully demonstrates her thesis, that ‘novels featuring an apparently damaged, subhuman, or insufficiently individuated human being prepare us to attempt the kind of sympathetic identification that novels have traditionally offered readers. They do so in order to turn a critical eye on all such person-to-person relationships’ (2014: 442). However, the contemporary novel aspires to more than simply ‘person-to-person’ relationships: both text and reader are undergoing an epistemological and even ontological resituating in relation to the refiguration of the humanities to the posthumanities in what Francis Fukuyama somewhat anxiously refers to as the ‘“posthuman” stage of history’ (2003: 7). Indeed, one might consider Ishiguro to be advocating for a neo-humanism, a recognition of species fluidity alongside a commitment to extending both empathy and rights to the traditionally post or non-human
Adaptation of Courts to Disruption
Get PDFThis article reflects on how courts in the USA and UK have remained active and resilient to provide access to justice, or due process, during times of emergency and disruptive events.. The focus here is not to define emergencies per se, but to analyse the impact of the emergencies and disruptive events that interrupt the functioning of courts and access to justice. The article provides a brief examination of the emergencies and the disruptions and the expected responses to those interruptions. The question for this paper is how do courts, adapt (or be adapted) in times of emergencies that disrupt their ordinary operation, both in terms of continuity of operations, but also in terms of protection of rights through judicial review? This paper will examine mainly two common law examples (England and USA) of how the courts adapted to such disruptions
Digital Twins as a Framework for IoT Applications: A Review
Get PDFThe integration of Digital Twins (DT) and
Internet of Things (IoT) technologies has emerged with
significant advancements across various domains. This review paper explores the fundamentals of Digital Twins, categorizations, state-of-the-art developments, and their integration with IoT. It dives into architectural considerations, data integration, communications, and analytical insights within the concept of using Digital Twins as a framework for IoT applications. Recent advancements, challenges and future directions are also discussed, highlighting the potential and complexities of this combined approach
Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design
Get PDFDeep convolutional neural networks (DCNNs) have demonstrated promising performance in classifying breast lesions in 2D ultrasound (US) images. Exiting approaches typically use pre-trained models based on architectures designed for natural images with transfer learning. Fewer attempts have been made to design customized architectures specifically for this purpose. This paper presents a comprehensive evaluation on transfer learning based solutions and automatically designed networks, analyzing the accuracy and robustness of different recognition models in three folds. First, we develop six different DCNN models (BNet, GNet, SqNet, DsNet, RsNet, IncReNet) based on transfer learning. Second, we adapt the Bayesian optimization method to optimize a CNN network (BONet) for classifying breast lesions. A retrospective dataset of 3034 US images collected from various hospitals is then used for evaluation. Extensive tests show that the BONet outperforms other models, exhibiting higher accuracy (83.33%), lower generalization gap (1.85%), shorter training time (66 min), and less model complexity (approximately 0.5 million weight parameters). We also compare the diagnostic performance of all models against that by three experienced radiologists. Finally, we explore the use of saliency maps to explain the classification decisions made by different models. Our investigation shows that saliency maps can assist in comprehending the classification decisions
Breast Lesion Detection in Ultrasound Images Using Deep Neural Networks: Clustering Based Approach for False Positive Reduction
Get PDFBreast cancer is one of the most common forms of cancer. Popular imaging modalities used for breast cancer screening include Mammograms, Ultrasound (US), and Magnetic Resonance Imaging (MRI). US is a widely adopted modality due to its relative affordability, portability and higher patient safety. Early detection of lesion(s) is crucial to ensure a high survival rate and minimise adverse effects on the body. Currently, we face a global crisis in the number of experienced radiologists available per patient. Therefore, automating lesion detection, with Artificial intelligence (AI) acting as a secondary opinion, can assist radiologists in faster diagnosis. In recent years, deep-learning (DL) based object detection methods have become popular in Computer-Aided Diagnosis (CAD) systems due to their ability in extracting high level, abstract features resulting in their higher generalisation capability and applicability in real-life operations. Compared to object detection in natural images, lesion detection in US images is a challenging task due to the inherent characteristics of these images. Due to these challenges and a lack of large scale US datasets, the number of DL-based lesion detection methods developed for US images is relatively lower compared to object detection methods developed for natural images. Thus, it is common practice to modify an existing object detector originally designed for natural images for lesion detection in US images. One such popularly adapted detector is Faster R-CNN (FRCNN). Limited attention has been given to adapted FRCNN for breast lesion detection in US images. The adaptation results in a relatively high detection rate along with a high number of false positive (FP) detections that degrade the overall performance. Such high FPs may mystify radiologists in reading and interpreting the US images and lead to unnecessary additional checks and biopsies. Reducing FPs in breast US images still remains an open investigation area which provides us the motivation for this study. Up to the point reported in this thesis, no work has been specifically developed to adequately address the issue of FPs in DL-based detection methods for breast lesion detection in US images. The aim of this research is to create a novel and effective DL-based method for detecting breast lesions from 2D US images. The research starts by investigating the effectiveness of FRCNN for breast lesion detection using large datasets of US images collected from different medical centres and machine makers. The research then provides the first solution to address the issue of FP detections by searching and identifying the optimal training and architectural hyperparameters of this powerful network. The adapted FRCNN model outperformed the original FRCNN through a significant reduction in FPs and small negative impact on the number of correct detections. Additionally, the adapted model also surpassed several existing detectors developed for natural images as well as those adapted for breast lesion detection in US images. Furthermore, this research develops a new U-Detect method. U-Detect is a clustering-based approach that combines unsupervised learning technique and the adapted FRCNN to reduce the FP detections. Two variants of the U-Detect method are developed: U-Detect-Base and U-Detect-RPN models. Both U Detect models outperform original and adapted FRCNN models through considerable reduction in FPs resulting in its higher precision. Additionally, U-Detect-RPN detected higher number of lesions than the adapted FRCNN model. Inspired by the domain knowledge of breast lesion characteristics, we further enhanced the architecture of U-Detect by developing a new classification-based approach (U-DetectH) that uses a fusion of textural and morphological handcrafted features to improve the classification scores in U-Detect and ultimately reduce the FP detections. Two variants of U-Detect-H are developed: U-DetectH-Base and U-DetectH-RPN models. The research concludes that on multiple datasets comprising a combined total of 3119 US images, U-DetectH-Base outperforms original FRCNN with 5.49% to 32.83% higher precision and a small drop of 0.27% to 10.02% in recall. This significantly higher precision is due to a 31.86% to 77.07% reduction in FPs. The work presented in this thesis provides an approach for scientists to design a robust object detection model for other cancer types as well as other medical modalities
Views of private primary school headteachers in Somalia about what it means to be professional headteacher
Get PDFA study carried out by the World Bank in 2018 recommended that there is a need to further study the role of school leadership, as they have important roles in determining the quality of schooling. This research investigated the views held by headteachers of private primary schools in Somalia about what it means to be a professional headteacher.
The research acknowledges that the enormity of the effects on education during armed conflict and post-conflict was felt everywhere, including the total destruction of the education infrastructure, teacher training provision, the disappearance of teachers and other education professionals, as well as the preparation and development of school leaders.
The main rationale behind focusing on private over public schools in Somalia is the wider representation of schools by non-state private schools. Regions do vary in the number of existing private schools. Over 65% of schools in Somalia are privately owned, and this made the study focus on the headteachers of this subsector. Globally, there is typically a lack of an agreed-upon set of definitions and limited information on education providers. In Somalia’s context, the definition of state and non-state schools is contested, and the absence of a commonly agreed-upon definition is a challenge for those who are interested in carrying out research about the subsector. The study highlights the significance of the role of headteachers in improving school performance and the management practices often deployed successfully. School leaders will require a broad range of skills, experience, personal qualities, or traits that make them more stable and resilient in order to effectively discharge these important roles. The study also presents a range of arguments about the eligibility and conditions for the professionalisation of a headteacher from international and regional perspectives. The study adopted a qualitative approach. A number of data collection tools were used, including semi-structured interviews and observations. Twenty-nine participants were interviewed, and eight were observed. For ethical purposes, the data collected in Somali was transcribed into English externally. The findings of the study indicate that participants held different views about being a professional headteacher, but they commonly agreed that a headteacher must hold a professional qualification in teaching, leadership, and management as well as leadership experience. Recommendations were made to a number of key players in the education sector in Somalia, including school owners, governments at both the state and federal levels, as well as private school associations and research institutions, for further research possibilities
On the Impact of Temperature for Precipitation Analysis
Get PDFClimate is the result of the constant interaction between different weather variables where temperature and precipitation are significant factors. Precipitation refers to the condensation of water vapor from clouds as a result of gravitational pull. These variables act as governing factors for determining rainfall, snowfall, and air pressure while determining wide-ranging effects on ecosystems. Different calculation methods could be employed such as Standard Precipitation Index for determining precipitation. Temperature is the measure that is used to identify the heat energy generated by solar radiation and other industrial factors. For understanding the interplay between these two variables, data gathered from several regions of the world including North America, Europe, Australia, and Central Asia was analyzed, and the findings are presented in this paper. Prediction methods such as multiple linear regression and long short-term memory (LSTM) have been employed for predicting rainfall from temperature and precipitation data. The inter-dependency of other weather parameters is also observed in this paper relating to rainfall prediction. The accuracy of the prediction models using machine learning has also been experimented within the study. The implementation of our work is available via https://github.com/MadaraPremawardhana/On-the-Impact-of-Temperature-for-Precipitation-Analysis
‘A lover's hand? A breath, An abyss’: Aloneness in Claire Denis
No full textIn readings of Beau Travail (1999), L’Intrus (2004), White Material (2009) and High Life (2018), films which feature aggressively solitary figures, I suggest that, for Denis, aloneness is often the result of, even a price paid willingly for, a passion or obsession which goes beyond that for companionship, love, family, or community. Her protagonists are usually already in enclaves (colonial, penal, military) which are themselves typified by facultative difference from their enclosing wider social settings. As Judith Mayne writes, all kinds of ‘Strangers populate the films of Claire Denis […] exiles who live sometimes on the margins, sometimes in the shifting spaces of the geographies of race and gender and colonization’ (2005: 80). These strangers with whom we become so fleetingly familiar in these brief but intense encounters are often intrusive foreign bodies, outcasts on distant outposts or islands, whether figurative or literal. It is not, however, the simple fact of their strangeness which marks them as remarkable, but the fact that they strive to perfect their sequestration within these stratified concentric spaces. In this sense, the films are not about the lonely, isolated, excluded or marginalised, but about the profoundly and voluntarily ontologically apart. Here, I focus on the forceful figures at the (faltering) heart of their often-solipsistic narratives; the landscapes which frame, enforce, symbolise their isolations; the fleeting moments of intimacy which temporarily irrupt within and offer ultimately illusory or unsatisfying alternatives to their aloneness; and finally, the ways in which each film witnesses its precarious subject in a moment of things – life, colony, humanity, comradery –collapsing. I want also to think through the significance of motion and stasis, velocity and inertia (‘are we rushing forward, are we standing still?’ as Robert Pattinson croons questioningly in Staples’ High Life soundtrack), the delicately balanced torsional forces between which play such a crucial role for Denis’s characters. Regardless of the shifting contexts and the ostensibly different lives portrayed, Denis’s films are united by an almost pathological idio-alienation which proves, ultimately, to be fatal
Examining the impact of a Volunteer-Delivered counselling service for people experiencing sight loss: a mixed methods evaluation
Get PDFInternational Energy Security Risk Index and Energy Diplomacy
No full textIt has long been recognised that energy supply disruption due to geopolitical issues, forces of nature or transient economic events have far-reaching adverse economic and social effects on energy importing countries and severe effects on producing and transit countries due to the loss of revenues. Several international organisations, including International Energy Agency (IEA), USA Global Energy Institute (GEI), World Economic Forum (WEF), Australian Government (RET) and researchers are engaged in identifying and quantifying the risks indicators, metrics, and indexes. Their objective is to formulate risk mitigation strategies, policies and actions, including increasing the reliance on renewable energy, energy diplomacy, diversification, development of local resources, improving agreements, and economisation on energy use. The energy triangle consisting of secure access to energy, economic growth and environmental degradation will increasingly derive much of the work on energy security. This chapter looks at the energy security risks, risk evaluation metrics, indexes, proposed mitigation strategies and policies, and discusses two of the indexes used to evaluate the energy security risks. In this chapter, the energy security risk is described in similar terms to those used in risk management standards and practices for other applications, not addressed clearly in the energy security literature