Beyond subjective and objective in statistics

We argue that the words "objectivity" and "subjectivity" in statistics discourse are used in a mostly unhelpful way, and we propose to replace each of them with broader collections of attributes, with objectivity replaced by transparency, consensus, impartiality, and correspondence to observable reality, and subjectivity replaced by awareness of multiple perspectives and context dependence. The advantage of these reformulations is that the replacement terms do not oppose each other. Instead of debating over whether a given statistical method is subjective or objective (or normatively debating the relative merits of subjectivity and objectivity in statistical practice), we can recognize desirable attributes such as transparency and acknowledgment of multiple perspectives as complementary goals. We demonstrate the implications of our proposal with recent applied examples from pharmacology, election polling, and socioeconomic stratification.Comment: 35 page

The Camera in conservation: determining photography’s place in the preservation of wildlife

This MA by research study is a reflection of photography’s past, current and future role within wildlife conservation, or whether there is indeed a necessity for it moving forwards. The following investigation and analysis of photography seeks to materialise how in fact the photographic medium can be both beneficial and negatively impactful to the preservation of wildlife, and how best it can be used by photographers in future conservation projects to ensure the preservation of wildlife. Several significant aspects of photography and external influences are engaged with in this study, firstly investigating the importance of empathy within wildlife conservation and how it can be elicited through imagery and photographic methods. Furthermore, I investigate the other side of conservation photography’s success, analysing what negative or neutral impacts it can bring with it, before researching the role that social media does and has the potential to play in conservation, and how photography can adapt to it to maximise its success. Lastly, I explore alternative visual media such as moving image, and how photography can best applicate successful techniques learned from them to reinterpret how conservation photography is perceived. Finally, using information and research from across my thesis, I have produced a ‘guide’ as to how conservation photography can be shaped to achieve its full potential for success, drawing upon previous successes and failures of other conservation attempts and photographers

Metadiscourse Tagging in Academic Lectures

This thesis presents a study into the nature and structure of academic lectures, with a special focus on metadiscourse phenomena. Metadiscourse refers to a set of linguistics expressions that signal specific discourse functions such as the Introduction: “Today we will talk about...” and Emphasising: “This is an important point”. These functions are important because they are part of lecturers’ strategies in understanding of what happens in a lecture. The knowledge of their presence and identity could serve as initial steps toward downstream applications that will require functional analysis of lecture content such as a browser for lectures archives, summarisation, or an automatic minute-taker for lectures. One challenging aspect for metadiscourse detection and classification is that the set of expressions are semi-fixed, meaning that different phrases can indicate the same function. To that end a four-stage approach is developed to study metadiscourse in academic lectures. Firstly, a corpus of metadiscourse for academic lectures from Physics and Economics courses is built by adapting an existing scheme that describes functional-oriented metadiscourse categories. Second, because producing reference transcripts is a time-consuming task and prone to some errors due to the manual efforts required, an automatic speech recognition (ASR) system is built specifically to produce transcripts of lectures. Since the reference transcripts lack time-stamp information, an alignment system is applied to the reference to be able to evaluate the ASR system. Then, a model is developed using Support Vector Machines (SVMs) to classify metadiscourse tags using both textual and acoustical features. The results show that n-grams are the most inductive features for the task; however, due to data sparsity the model does not generalise for unseen n-grams. This limits its ability to solve the variation issue in metadiscourse expressions. Continuous Bag-of-Words (CBOW) provide a promising solution as this can capture both the syntactic and semantic similarities between words and thus is able to solve the generalisation issue. However, CBOW ignores the word order completely, something which is very important to be retained when classifying metadiscourse tags. The final stage aims to address the issue of sequence modelling by developing a joint CBOW and Convolutional Neural Network (CNN) model. CNNs can work with continuous features such as word embedding in an elegant and robust fashion by producing a fixed-size feature vector that is able to identify indicative local information for the tagging task. The results show that metadiscourse tagging using CNNs outperforms the SVMs model significantly even on ASR outputs, owing to its ability to predict a sequence of words that is more representative for the task regardless of its position in the sentence. In addition, the inclusion of other features such as part-of-speech (POS) tags and prosodic cues improved the results further. These findings are consistent in both disciplines. The final contribution in this thesis is to investigate the suitability of using metadiscourse tags as discourse features in the lecture structure segmentation model, despite the fact that the task is approached as a classification model and most of the state-of-art models are unsupervised. In general, the obtained results show remarkable improvements over the state-of-the-art models in both disciplines

Advances and Applications of Dezert-Smarandache Theory (DSmT) for Information Fusion (Collected Works), Vol. 4

The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals. First Part of this book presents the theoretical advancement of DSmT, dealing with Belief functions, conditioning and deconditioning, Analytic Hierarchy Process, Decision Making, Multi-Criteria, evidence theory, combination rule, evidence distance, conflicting belief, sources of evidences with different importance and reliabilities, importance of sources, pignistic probability transformation, Qualitative reasoning under uncertainty, Imprecise belief structures, 2-Tuple linguistic label, Electre Tri Method, hierarchical proportional redistribution, basic belief assignment, subjective probability measure, Smarandache codification, neutrosophic logic, Evidence theory, outranking methods, Dempster-Shafer Theory, Bayes fusion rule, frequentist probability, mean square error, controlling factor, optimal assignment solution, data association, Transferable Belief Model, and others. More applications of DSmT have emerged in the past years since the apparition of the third book of DSmT 2009. Subsequently, the second part of this volume is about applications of DSmT in correlation with Electronic Support Measures, belief function, sensor networks, Ground Moving Target and Multiple target tracking, Vehicle-Born Improvised Explosive Device, Belief Interacting Multiple Model filter, seismic and acoustic sensor, Support Vector Machines, Alarm classification, ability of human visual system, Uncertainty Representation and Reasoning Evaluation Framework, Threat Assessment, Handwritten Signature Verification, Automatic Aircraft Recognition, Dynamic Data-Driven Application System, adjustment of secure communication trust analysis, and so on. Finally, the third part presents a List of References related with DSmT published or presented along the years since its inception in 2004, chronologically ordered

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Safety lifecycle management in the process industries : the development of a qualitative safety related information analysis technique

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Seeing affect: knowledge infrastructures in facial expression recognition systems

Efforts to process and simulate human affect have come to occupy a prominent role in Human-Computer Interaction as well as developments in machine learning systems. Affective computing applications promise to decode human affective experience and provide objective insights into usersʼ affective behaviors, ranging from frustration and boredom to states of clinical relevance such as depression and anxiety. While these projects are often grounded in psychological theories that have been contested both within scholarly and public domains, practitioners have remained largely agnostic to this debate, focusing instead on the development of either applicable technical systems or advancements of the fieldʼs state of the art. I take this controversy as an entry point to investigate the tensions related to the classification of affective behaviors and how practitioners validate these classification choices. This work offers an empirical examination of the discursive and material repertoires ‒ the infrastructures of knowledge ‒ that affective computing practitioners mobilize to legitimize and validate their practice. I build on feminist studies of science and technology to interrogate and challenge the claims of objectivity on which affective computing applications rest. By looking at research practices and commercial developments of Facial Expression Recognition (FER) systems, the findings unpack the interplay of knowledge, vision, and power underpinning the development of machine learning applications of affective computing. The thesis begins with an analysis of historical efforts to quantify affective behaviors and how these are reflected in modern affective computing practice. Here, three main themes emerge that will guide and orient the empirical findings: 1) the role that framings of science and scientific practice play in constructing affective behaviors as “objective” scientific facts, 2) the role of human interpretation and mediation required to make sense of affective data, and 3) the prescriptive and performative dimensions of these quantification efforts. This analysis forms the historical backdrop for the empirical core of the thesis: semi-structured interviews with affective computing practitioners across the academic and industry sectors, including the data annotators labelling the modelsʼ training datasets. My findings reveal the discursive and material strategies that participants adopt to validate affective classification, including forms of boundary work to establish credibility as well as the local and contingent work of human interpretation and standardization involved in the process of making sense of affective data. Here, I show how, despite their professed agnosticism, practitioners must make normative choices in order to ʻseeʼ (and teach machines how to see) affect. I apply the notion of knowledge infrastructures to conceptualize the scaffolding of data practices, norms and routines, psychological theories, and historical and epistemological assumptions that shape practitionersʼ vision and inform FER design. Finally, I return to the problem of agnosticism and its socio-ethical relevance to the broader field of machine learning. Here, I argue that agnosticism can make it difficult to locate the technologyʼs historical and epistemological lineages and, therefore, obscure accountability. I conclude by arguing that both policy and practice would benefit from a nuanced examination of the plurality of visions and forms of knowledge involved in the automation of affect

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute

The Impossibilities of the Circular Economy

The fifth Factor X publication from the Federal Environment Agency (Umweltbundesamt, UBA), The Impossibilities of the Circular Economy provides an overview of the limits to the circular economy, emphasising the relationship between integrated resource use and more systemic leadership-management approaches. On a European level, the book ties into the recent European Green Deal and aims to empower actors across sectors and EU member countries to transition from existing linear models of value capture and expression to more systemic-circular solutions of value capture and expression. The volume provides a hands-on contribution towards building the knowledge and skill sets of current and future decision-makers who face these complex-systemic crises in their day-to-day business. The book further provides access to best practices from cutting-edge research and development findings, which will empower decision-makers to develop a more sustainable and equitable economy. Providing solutions for a more sustainable economy, this book is essential reading for scholars and students of natural resource use, sustainable business, environmental economics and sustainable development, as well as decision-makers and experts from the fields of policy development, industry and civil society