pinecone/core-2020-05-10-deduplication huggingface dataset:
Blogging Climate Change: A Case Study

Public perception of the magnitude of challenges associated with climate change is still lower than that of the majority of scientists. The societal relevance of climate change has raised the need for a more direct communication between scientists and the public. However, peer-reviewed scientific articles are not well-suited to engaging a wider audience. This begets a need to explore other avenues for communicating climate change. Social media is a vibrant source for information exchange among the masses. Blogs in particular are a promising tool for disseminating complex findings on topics such as climate change, as they are easier to comprehend and are targeted at a broader audience compared to scientific publications. This chapter discusses the usefulness of blogs in communicating climate change, using our blog Climate Footnotes (climatefootnotes.com) as a case study. Drawing from communication theory and our experiences with Climate Footnotes, we identify and describe elements such as message framing, translation of scientific data, role of language, and interactivity in aiding climate change communication. The insights outlined herein help understand the nature and impact of online climate change communication. The chapter may also serve as a useful blueprint for scientists interested in utilizing blogs to communicate climate change
Automatic discovery and exploitation of promising subproblems for tabulation

Funding: EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship.The performance of a constraint model can often be improved by converting a subproblem into a single table constraint. In this paper we study heuristics for identifying promising subproblems. We propose a small set of heuristics to identify common cases such as expressions that will propagate weakly. The process of discovering promising subproblems and tabulating them is entirely automated in the tool Savile Row. A cache is implemented to avoid tabulating equivalent subproblems many times. We give a simple algorithm to generate table constraints directly from a constraint expression in Savile Row. We demonstrate good performance on the benchmark problems used in earlier work on tabulation, and also for several new problem classes.Postprin
Evaluating QBF Solvers: Quantifier Alternations Matter

We present an experimental study of the effects of quantifier alternations on
the evaluation of quantified Boolean formula (QBF) solvers. The number of
quantifier alternations in a QBF in prenex conjunctive normal form (PCNF) is
directly related to the theoretical hardness of the respective QBF
satisfiability problem in the polynomial hierarchy. We show empirically that
the performance of solvers based on different solving paradigms substantially
varies depending on the numbers of alternations in PCNFs. In related
theoretical work, quantifier alternations have become the focus of
understanding the strengths and weaknesses of various QBF proof systems
implemented in solvers. Our results motivate the development of methods to
evaluate orthogonal solving paradigms by taking quantifier alternations into
account. This is necessary to showcase the broad range of existing QBF solving
paradigms for practical QBF applications. Moreover, we highlight the potential
of combining different approaches and QBF proof systems in solvers.Comment: preprint of a paper to be published at CP 2018, LNCS, Springer,
  including appendi
Automatic generation and selection of streamlined constraint models via Monte Carlo search on a model lattice

Funding: EPSRC EP/P015638/1.Streamlined constraint reasoning is the addition of uninferred constraints to a constraint model to reduce the search space, while retaining at least one solution. Previously it has been established that it is possible to generate streamliners automatically from abstract constraint specifications in Essence and that effective combinations of streamliners can allow instances of much larger scale to be solved. A shortcoming of the previous approach was the crude exploration of the power set of all combinations using depth and breadth first search. We present a new approach based on Monte Carlo search over the lattice of streamlined models, which efficiently identifies effective streamliner combinations.Postprin
Metamorphic testing of constraint solvers

Funding: EPSRC EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship.Constraint solvers are complex pieces of software and are notoriously difficult to debug. In large part this is due to the difficulty of pinpointing the source of an error in the vast searches these solvers perform, since the effect of an error may only come to light long after the error is made. In addition, an error does not necessarily lead to the wrong result, further complicating the debugging process. A major source of errors in a constraint solver is the complex constraint propagation algorithms that provide the inference that controls and directs the search. In this paper we show that metamorphic testing is a principled way to test constraint solvers by comparing two different implementations of the same constraint. Specifically, specialised propagators for the constraint are tested against the general purpose table constraint propagator. We report on metamorphic testing of the constraint solver Minion. We demonstrate that the metamorphic testing method is very effective for finding artificial bugs introduced by random code mutation.Postprin
Multistep-ahead prediction: a comparison of analytical and algorithmic approaches

Most approaches to forecasting time series data employ one-step-ahead prediction approaches. However, recently there has been focus on multi-step-ahead prediction approaches. These approaches demonstrate enhanced prediction capabilities.\ud
However, multi-step-ahead prediction increases the complexity of the prediction process in comparison to one-step-ahead approaches. Typically, studies in the examination of multi-step ahead methods have addressed issues such as the increased complexity, inaccuracy, uncertainty, and error variance on the prediction horizon, and have been deployed in various domains such as finance, economics, agriculture and hydrology. When determining which algorithm to use in a time series analyses, the approach is to analyze the series for numerous characteristics and features, such as heteroscedasticity, auto-correlation, seasonality and stationarity. In this work, a comparative analysis of 20 different time series datasets is presented and a demonstration of the complexity in deciding which approach to use is given. The study investigates some of the main prediction approaches such as ARIMA (Autoregressive integrated moving average), NN (Neural Network), RNN (Recurrent neural network) and SVR (Support vector regression), which focus on the recursive prediction strategy and compare them to a new approach known as MRFA (Multi-Resolution Forecast Aggregation)
Learning by reviewing paper-based programming assessments

This paper presents a retrospective analysis of students’ use of self-regulated learning strategies while using an educational technology that connects physical and digital learning spaces. A classroom study was carried out in a Data Structures & Algorithms course offered by the School of Computer Science. Students’ reviewing behaviors were logged and the associated learning impacts were analyzed by monitoring their progress throughout the course. The study confirmed that students who had an improvement in their performance spent more time and effort reviewing formal assessments, particularly their mistakes. These students also demonstrated consistency in their reviewing behavior throughout the semester. In contrast, students who fell behind in class ineffectively reviewed their graded assessments by focusing mostly on what they already knew instead of their knowledge misconceptions
An exploratory study on student engagement with adaptive notifications in programming courses

This paper presents a study on students’ engagement and personalized weekly performance notifications. Students were offered to voluntarily opt-in to receive customized notifications regarding their predicted course performances and recommended resources. In addition, the predicted at-risk students were also recommended with code solutions from higher performers in the class. Data was collected from Computer Science programming courses. Students’ engagement with the notifications and resources were tracked and have been found to be an indicator of their differential improvement between their exams
Education and training for maritime spatial planners

The practice of Maritime Spatial Planning (MSP) has developed substantially during the last decade, calling for more qualified professionals. Education, training, and growth capacity for MSP, however, are (still) some of the less addressed themes in MSP forums and specific learning materials, such as textbooks and practice manuals. Some teaching initiatives have nevertheless arisen at the postgraduate level for training new and specialised practitioners in the MSP field. A quick overview of such initiatives will help answer some questions concerning the path to follow for MSP education and training. This chapter presents an exploratory diagnosis based on a discussion of the basic skills needed to achieve successful professional practice. What skills are expected from a maritime spatial planner? Is a specific background required to become a maritime spatial planner? How should such professionals be trained? These questions are discussed using the visions and insights of consultants, maritime sectors, policymakers, scientists, and teachers of MSP, with experience in countries where MSP processes are already in place
Automated Biometric Authentication with Cloud Computing

The convenience provided by cloud computing has led to an increasing trend of many business organizations, government agencies and individual customers to migrate their services and data into cloud environments. However, once clients’ data is migrated, the overall security control will be immedicably shifted form data owners to the hand of cloud service providers. In fact, most cloud clients do not even know where their data is physically stored, and therefore the question of how to limit data access to authorized users has been one of the biggest challenges in cloud environments. Although security tokens and passwords are widely used form of remote user authentication, they can be lost or stolen as they are not linked with the identity of data owner. Therefore, biometric based authentication can potentially offer a practical and reliable option for remote access control. This chapter starts with a brief introduction that covers the fundamental concepts of cloud computing and biometric based authentication. It then provides and in-depth discussions on authentication challenges for the cloud computing environment and the limitation of traditional solutions. This leads to the key sections related to biometric solutions for cloud computing in which we present state-of-art approaches that offer convenient and privacy-preserving authentication needed for cloud environment. The chapter argues that addressing privacy concerns surrounding the use of biometrics in cloud computing is one of the key challenges that has to be an integral part of any viable solution for any biometric-based authentication. It also argues that assuring cloud clients that their biometric templates will not be used without their permission to, for example, track them is not enough. Such solutions should make it technically infeasible to do so even if a cloud service provider wants to. This chapter explains a number of interesting solutions that have been recently proposed to improve security and, at the same time, maintain user privacy. Finally, we identify some challenges that still need to be addressed and highlight relevant Research Directions
Combining web and enterprise data for lightweight data mart construction

The Agri sector has shown an exponential growth in both the requirement for and the production \ud
and availability of data. In parallel with this growth, Agri organisations often have a need \ud
to integrate their in-house data with international, web-based datasets. Generally, data is\ud
freely available from official government sources but there is very little unity between \ud
sources, often leading to significant manual overhead in the development of data integration \ud
systems and the preparation of reports.\ud
While this has led to an increased use of data warehousing technology in the Agri sector, the \ud
issues of cost in terms of both time to access data and the financial costs of generating the\ud
Extract-Transform-Load layers remain high. In this work, we examine more lightweight data marts\ud
 in an infrastructure which can support on-demand queries. We focus on the construction of data \ud
marts which combine both enterprise and web data, and present an evaluation which verifies the transformation process from source to data mart
Overview of ImageCLEF 2018: challenges, datasets and evaluation

This paper presents an overview of the ImageCLEF 2018 evaluation campaign, an event that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) Labs 2018. ImageCLEF is an ongoing initiative (it started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval with the aim of providing information access to collections of images in various usage scenarios and domains. In 2018, the 16th edition of ImageCLEF ran three main tasks and a pilot task: (1) a caption prediction task that aims at predicting the caption of a figure from the biomedical literature based only on the figure image; (2) a tuberculosis task that aims at detecting the tuberculosis type, severity and drug resistance from CT (Computed Tomography) volumes of the lung; (3) a LifeLog task (videos, images and other sources) about daily activities understanding and moment retrieval, and (4) a pilot task on visual question answering where systems are tasked with answering medical questions. The strong participation, with over 100 research groups registering and 31 submitting results for the tasks, shows an increasing interest in this benchmarking campaign
Robotics and Integrated Formal Methods: Necessity meets Opportunity

Robotic systems are multi-dimensional entities, combining both hardware and software, that are heavily dependent on, and influenced by, interactions with the real world. They can be variously categorised as embedded, cyberphysical, real-time, hybrid, adaptive and even autonomous systems, with a typical robotic system being likely to contain all of these aspects. The techniques for developing and verifying each of these system varieties are often quite distinct. This, together with the sheer complexity of robotic systems, leads us to argue that diverse formal techniques must be integrated in order to develop, verify, and provide certification evidence for, robotic systems. Furthermore, we propose the fast evolving field of robotics as an ideal catalyst for the advancement of integrated formal methods research, helping to drive the field in new and exciting directions and shedding light on the development of large-scale, dynamic, complex systems
Making Linearizability Compositional for Partially Ordered Executions

In the interleaving model of concurrency, where events are\ud
totally ordered, linearizability is compositional: the composition of two\ud
linearizable objects is guaranteed to be linearizable. However, linearizability\ud
is not compositional when events are only partially ordered, as\ud
in the weak-memory models that describe multicore memory systems.\ud
In this paper, we present a generalisation of linearizability for concurrent\ud
objects implemented in weak-memory models. We abstract from the\ud
details of specific memory models by defining our condition using Lamport's\ud
execution structures. We apply our condition to the C11 memory\ud
model, providing a correctness condition for C11 objects. We develop a\ud
proof method for verifying objects implemented in C11 and related models.\ud
Our method is an adaptation of simulation-based methods, but in\ud
contrast to other such methods, it does not require that the implementation\ud
totally orders its events. We apply our proof technique and show\ud
correctness of the Treiber stack that blocks on empty, annotated with\ud
C11 release-acquire synchronisation
Ultra-Large Repair Search Space with Automatically Mined Templates: the
  Cardumen Mode of Astor

Astor is a program repair library which has different modes. In this paper,
we present the Cardumen mode of Astor, a repair approach based mined templates
that has an ultra-large search space. We evaluate the capacity of Cardumen to
discover test-suite adequate patches (aka plausible patches) over the 356 real
bugs from Defects4J. Cardumen finds 8935 patches over 77 bugs of Defects4J.
This is the largest number of automatically synthesized patches ever reported,
all patches being available in an open-science repository. Moreover, Cardumen
identifies 8 unique patches, that are patches for Defects4J bugs that were
never repaired in the whole history of program repair
The Impact of Coevolution and Abstention on the Emergence of Cooperation

This paper explores the Coevolutionary Optional Prisoner's Dilemma (COPD)
game, which is a simple model to coevolve game strategy and link weights of
agents playing the Optional Prisoner's Dilemma game. We consider a population
of agents placed in a lattice grid with boundary conditions. A number of Monte
Carlo simulations are performed to investigate the impacts of the COPD game on
the emergence of cooperation. Results show that the coevolutionary rules enable
cooperators to survive and even dominate, with the presence of abstainers in
the population playing a key role in the protection of cooperators against
exploitation from defectors. We observe that in adverse conditions such as when
the initial population of abstainers is too scarce/abundant, or when the
temptation to defect is very high, cooperation has no chance of emerging.
However, when the simple coevolutionary rules are applied, cooperators
flourish.Comment: To appear at Studies in Computational Intelligence (SCI), Springer,
  201
Classification of hardened cement and lime mortar using short-wave infrared spectrometry data

This paper evaluated the feasibility of using spectrometry data in the short-wave infrared range (1,300-2,200nm) to distinguish lime mortar and Type S cement mortar using 42 lab samples (21 lime-based, 21 cement-based) each 404040mm were created. A Partial Least Squares Discriminant Analysis model was developed using the mean spectra of 28 specimens as the calibration set. The results were tested on the mean spectra of the remaining 14 specimens as a validation set. The results showed that, spectrometry data were able to fully distinguish modern mortars (made with cement) from historic lime mortars with a 100% classification accuracy, which can be very useful in archaeological and architectural conservation applications. Specifically, being able to distinguish mortar composition in situ can provide critical information about the construction history of a structure, as well as to inform an appropriate intervention scheme when historic material needs to be repaired or replaced.Funding for this work was provided by New York University’s Center for Urban Science and Progress. Dr. Gowen acknowledges funding from the European Research Council (ERC) under the starting grant programme ERC-2013-StG call—Proposal No. 335508—BioWater
Investigating Language Variability on the Performance of Speaker Verification Systems

<p>In recent years, speaker verification technologies have received an extensive amount of attention. Designing and developing machines that could communicate with humans are believed to be one of the primary motivations behind such developments. Speaker verification technologies are applied to numerous fields such as security, Biometrics, and forensics.</p>\ud
\ud
<p>In this paper, the authors study the effects of different languages on the performance of the automatic speaker verification (ASV) system. The MirasVoice speech corpus (MVSC), a bilingual English and Farsi speech corpus, is used in this study. This study collects results from both an I-vector based ASV system and a GMM-UBM based ASV system. The experimental results show that a mismatch between the enrolled data used for training and verification data can lead to a significant decrease in the overall system efficiency. This study shows that it is best to use an i-vector based framework with data from the English language used in the enrollment phase to improve the robustness of the ASV systems. The achieved results in this study indicate that this can narrow the degradation gap caused by the language mismatch.</p
Simple games versus weighted voting games.

A simple game (N, v) is given by a set N of n players and a partition of   2N  into a set   L  of losing coalitions L with value   v(L)=0  that is closed under taking subsets and a set   W  of winning coalitions W with   v(W)=1 . Simple games with   α=minp≥0maxW∈W,L∈Lp(L)p(W)<1  are exactly the weighted voting games. Freixas and Kurz (IJGT, 2014) conjectured that   α≤14n  for every simple game (N, v). We confirm this conjecture for two complementary cases, namely when all minimal winning coalitions have size 3 and when no minimal winning coalition has size 3. As a general bound we prove that   α≤27n  for every simple game (N, v). For complete simple games, Freixas and Kurz conjectured that   α=O(n−−√) . We prove this conjecture up to a   lnn  factor. We also prove that for graphic simple games, that is, simple games in which every minimal winning coalition has size 2, computing   α  is NP-hard, but polynomial-time solvable if the underlying graph is bipartite. Moreover, we show that for every graphic simple game, deciding if   α<a  is polynomial-time solvable for every fixed   a>0
A Literature-Based Analysis of the Cyber-Physical Systems Under the Lens of Reconfigurability

Cyber-physical systems (CPSs) are an increasingly known set of technologies and applications promising to enable manufacturing firms improving their responsiveness to deal with the unpredictability of market requirements. Indeed, from an operational perspective, responsiveness can be achieved because CPSs are an enabler of the reconfigurability of factories. Reconfigurability is a capability that has been theorized since almost two decades. Therefore, today we can consider such grounded theory as a lens to frame emerging CPS-related knowledge. This paper is an effort to give a contribution in this direction. In particular, starting from the acknowledgement that a relevant characteristic of reconfigurability is modularity, this research proposes a literature-based analysis of the Cyber-Physical Systems of the future smart factory
A national certification programme for academic degrees in cyber security

© Crown, The National Cyber Security Centre 2018. With a growing need for cyber security skills, there has been a notable increase in the number of academic degrees targeting this topic area, at both undergraduate and postgraduate levels. However, with a widening and varied choice available to them, prospective students and employers require a means to identify academic degrees that offer appropriate and high-quality education in the subject area. This paper presents a case study of the establishment and operation of a certification programme for academic degrees in cyber security. It describes the means by which appropriate topic themes and subject areas for relevant degrees were identified and defined, leading to a certification programme that addresses degrees in general cyber security as well as notable specialisations including digital forensics and network security. The success of the programme is evidenced by 25 degrees across 19 universities having been certified to date, and a continued response to new calls for certification