pinecone/core-2020-05-10-deduplication huggingface dataset:
Towards a runtime verification framework for the Ada Programming Language

Runtime verification is an emerging discipline that investigates methods and tools to enable the verification of program properties during the execution of the application. The goal is to complement static analysis approaches, in particular when static verification leads to the explosion of states. Non-functional properties, such as the ones present in real-time systems are an ideal target for this kind of verification methodology, as are usually out of the range of the power and expressiveness of classic static analyses. In this paper, we present a framework that allows real-time programs written in Ada to be augmented with runtime verification capabilities. Our framework provides the infrastructures which is needed to instrument the code with runtime monitors. These monitors are responsible for observing the system and reaching verdicts about whether its behavior is compliant with its non-functional properties. We also sketch a contract language to extend the one currently provided by Ada, with the long term goal of having an elegant way in which runtime monitors can be automatically synthesized and instrumented into the target systems. The usefulness of the proposed approach is demonstrated by showing its use for an application scenario.This work was partially supported by Portuguese National Funds through FCT (Portuguese Founda- tion for Science and Technology) and by ERDF (European Regional Develop- ment Fund) through COMPETE (Operational Programme ’Thematic Factors of Competitiveness’), within projects FCOMP-01-0124-FEDER-037281 (CISTER), FCOMP-01-0124-FEDER-015006 (VIPCORE) and FCOMP-01-0124-FEDER- 020486 (AVIACC); and by FCT and EU ARTEMIS JU, within project ARTEMIS/0003/2012, JU grant nr. 333053 (CONCERTO)
Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain
Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms
Continuous after-the-fact leakage-resilient key exchange

Security models for two-party authenticated key exchange (AKE) protocols have developed over time to provide security even when the adversary learns certain secret keys. In this work, we advance the modelling of AKE protocols by considering more granular, continuous leakage of long-term secrets of protocol participants: the adversary can adaptively request arbitrary leakage of long-term secrets even after the test session is activated, with limits on the amount of leakage per query but no bounds on the total leakage. We present a security model supporting continuous leakage even when the adversary learns certain ephemeral secrets or session keys, and give a generic construction of a two-pass leakage-resilient key exchange protocol that is secure in the model; our protocol achieves continuous, after-the-fact leakage resilience with not much more cost than a previous protocol with only bounded, non-after-the-fact leakage
An Analysis of Tracking Service Settings in Blackberry 10 and Windows Phone 8 Smartphones

The use of tracking settings in smartphones facilitates the provision of tailored services to users by allowing service providers access to unique identifiers stored on the smartphones. In this paper, we investigate the `tracking of' settings on the Blackberry 10 and Windows Phone 8 platforms. To determine if they work as claimed, we set up a test bed suitable for both operating systems to capture traffic between the smartphone and external servers. We dynamically execute a set of similar Blackberry 10 and Windows Phone 8 applications, downloaded from their respective official markets. Our results indicate that even if users turn of tracking settings in their smartphones, some applications leak unique identifiers without their knowledge
A Survey on Approximation Mechanism Design without Money for Facility
  Games

In a facility game one or more facilities are placed in a metric space to
serve a set of selfish agents whose addresses are their private information. In
a classical facility game, each agent wants to be as close to a facility as
possible, and the cost of an agent can be defined as the distance between her
location and the closest facility. In an obnoxious facility game, each agent
wants to be far away from all facilities, and her utility is the distance from
her location to the facility set. The objective of each agent is to minimize
her cost or maximize her utility. An agent may lie if, by doing so, more
benefit can be obtained. We are interested in social choice mechanisms that do
not utilize payments. The game designer aims at a mechanism that is
strategy-proof, in the sense that any agent cannot benefit by misreporting her
address, or, even better, group strategy-proof, in the sense that any coalition
of agents cannot all benefit by lying. Meanwhile, it is desirable to have the
mechanism to be approximately optimal with respect to a chosen objective
function. Several models for such approximation mechanism design without money
for facility games have been proposed. In this paper we briefly review these
models and related results for both deterministic and randomized mechanisms,
and meanwhile we present a general framework for approximation mechanism design
without money for facility games
Topology Optimization for Human Proximal Femur Considering Bi-modulus Behavior of Cortical Bones

The material in the human proximal femur is considered as bi-modulus material and the density distribution is predicted by topology optimization method. To reduce the computational cost, the bi-modulus material is replaced with two isotropic materials in simulation. The selection of local material modulus is determined by the previous local stress state. Compared with density prediction results by traditional isotropic material in proximal femur, the bi-modulus material layouts are different obviously. The results also demonstrate that the bi-modulus material model is better than the isotropic material model in simulation of density prediction in femur bone
Coupled electromagnetic and elastic dynamics in metamaterials

Metamaterials are well established in the field of electromagnetism, where they have demonstrated a wide variety of exotic material properties. More recently, mechanical metamaterials have also been shown to be quite promising in achieving exotic properties for acoustic waves. Here we discuss an emerging class of metamaterials with both electromagnetic and elastic properties, which are coupled to each other, giving rise to a new range of metamaterial properties. In particular, this can yield a very strong nonlinear response, including bistable states and self-oscillations. We present several structures which exhibit these properties, and experimentally demonstrate their feasibility
Towards a framework for learning from networked data

Keynote lectureOver the past decades, one has seen databases of ever increasing size and com-
plexity. While the increasing size is easy to measure in bytes, kilobytes or ter-
abytes, the increase in complexity is more difficult to quantify, however, it has
a very deep effect on the theory we use to reason about the data. While in
earlier days many researchers reasoned in terms of sets of similarly structured
and independent objects, today we are facing large networks of data where ev-
erything is connected directly or indirectly to everything else. Examples include
social networks, traffic networks, biological networks, administrative networks
and economic networks.
These developments have spurred a renewed interest in data storage and
knowledge extraction (answers to queries, patterns, models, ...). Three key un-
derlying challenges are the representation of the data and knowledge, managing
the computational cost of the problems which we need to solve and the statistical
challenge related to the complexity of the data.
In this contribution, I will survey these challenges from a data mining point of
view. I will argue that in order to address the current challenges it is valuable to
gain a better understanding of fundamental statistical and algorithmic properties
of large data networks and to integrate ideas from the many fields of research
that are concerned with such networks.status: publishe
Defining Key Semantics for the RDF Datasets: Experiments and Evaluations

International audienceMany techniques were recently proposed to automate the linkage of RDF datasets. Predicate selection is the step of the linkage process that consists in selecting the smallest set of relevant predicates needed to enable instance comparison. We call keys this set of predicates that is analogous to the notion of keys in relational databases. We explain formally the different assumptions behind two existing key semantics. We then evaluate experimentally the keys by studying how discovered keys could help dataset interlinking or cleaning. We discuss the experimental results and show that the two different semantics lead to comparable results on the studied datasets
Dynamic OD transit matrix estimation: formulation and model-building environment

The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the input for building the space-state model is linked to network scenarios modeled with the transportation planning platform EMME. The transit assignment framework is optimal strategy-based, which determines the subset of paths related to the optimal strategies between all OD pairsPeer ReviewedPostprint (author’s final draft
Generalized Spring Tensor Model: A New Improved Load Balancing Method in Cloud Computing

Significant characteristics of cloud computing such as elasticity, scalability and payment model attract businesses to replace their legacy infrastructure with the newly offered cloud technologies. As the number of the cloud users is growing rapidly, extensive load volume will affect performance and operation of the cloud. Therefore, it is essential to develop smarter load management methods to ensure effective task scheduling and efficient management of resources. In order to reach these goals, varieties of algorithms have been explored and tested by many researchers. But so far, not many operational load balancing algorithms have been proposed that are capable of forecasting the future load patterns in cloud-based systems. The aim of this research is to design an effective load management tool, characterized by collective behavior of the workflow tasks and jobs that is able to predict various dynamic load patterns occurring in cloud networks. The results show that the proposed new load balancing algorithm can visualize the network load by projecting the existing relationships among submitted tasks and jobs. The visualization can be particularly useful in terms of monitoring the robustness and stability of the cloud systems
Autonomous Model of Software Architecture for Smart Grids

Smart grids are being deployed at global level to ensure energy efficiency. As a result, scalable smart software platforms are required which can be used to incorporate and integrate information coming from various consumers using smart meters. Smart grids are supported by smart software architectures which are supported by cloud platforms. Cloud and Internet-of-Things (IoT) platforms provide scalable resources which can be used to design software infrastructures which allow always-on applications. The report paper explores smart grid and energy efficiency, how cloud and IoT platforms are used to enhance smart software architecture for smart grids, and privacy and security issues that result from the use of clouds. © Springer International Publishing Switzerland 2015
An Overview of Chip Multi-Processors Simulators Technology

Computer System Architecture (CSA) simulators are generally used to develop and validate new CSA designs and developments. The goal of this paper is to provide an insight into the importance of CSA simulation and the possible criteria that differentiate between various CSA simulators. Multi-dimensional aspects determine the taxonomy of CSA simulators including their accuracy, performance, functionality and flexibility. The Sniper simulator has been selected for a closer look and testing. The Sniper proofs its ability to scale to hundred cores with a wide range of functionality and performance. © Springer International Publishing Switzerland 2015
Talking with Scholars: Developing a Research Environment for Oral History Collections.

Scholars are yet to make optimal use of Oral History collections. For the uptake of digital research tools in the daily working practice of researchers, practices and conventions commonly adhered to in the subfields of the humanities should be taken into account during development, in order to facilitate the uptake of digital research tools in the daily working practice of researchers. To this end, in the Oral History Today project a research tool for exploring Oral History collections is developed in close collaboration with scholarly researchers. This paper describes four stages of scholarly research and the first steps undertaken to incorporate requirements of these stages in a digital research environment
Tagging Scientific Publications using Wikipedia and Natural Language
  Processing Tools. Comparison on the ArXiv Dataset

In this work, we compare two simple methods of tagging scientific
publications with labels reflecting their content. As a first source of labels
Wikipedia is employed, second label set is constructed from the noun phrases
occurring in the analyzed corpus. We examine the statistical properties and the
effectiveness of both approaches on the dataset consisting of abstracts from
0.7 million of scientific documents deposited in the ArXiv preprint collection.
We believe that obtained tags can be later on applied as useful document
features in various machine learning tasks (document similarity, clustering,
topic modelling, etc.)
Linked Logainm: enhancing library metadata using linked data of Irish place names

Linked Logainm is the newly created Linked Data version of Logainm.ie, an online database holding the authoritative hierarchical list of Irish and English language place names in Ireland. As a use case to demonstrate the benefit of Linked Data to the library community, the Linked Logainm dataset was used to enhance the Longfield Map collection, a set of digitised 18th–19th century maps held by the National Library of Ireland. This paper describes the process of creating Linked Logainm, including the transformation of the data from XML to RDF, the generation of links to external geographic datasets like DBpedia and the Faceted Application of Subject Terminology, and the enhancement of the Library’s metadata records
Mathoid: Robust, Scalable, Fast and Accessible Math Rendering for
  Wikipedia

Wikipedia is the first address for scientists who want to recap basic
mathematical and physical laws and concepts. Today, formulae in those pages are
displayed as Portable Network Graphics images. Those images do not integrate
well into the text, can not be edited after copying, are inaccessible to screen
readers for people with special needs, do not support line breaks for small
screens and do not scale for high resolution devices. Mathoid improves this
situation and converts formulae specified by Wikipedia editors in a TeX-like
input format to MathML, with Scalable Vector Graphics images as a fallback
solution.Comment: 12 pages, accepted at Conferences on Intelligent Computer Mathematics
  CICM201
Mining state-based models from proof corpora

Interactive theorem provers have been used extensively to reason about various software/hardware systems and mathematical theorems. The key challenge when using an interactive prover is finding a suitable sequence of proof steps that will lead to a successful proof requires a significant amount of human intervention. This paper presents an automated technique that takes as input examples of successful proofs and infers an Extended Finite State Machine as output. This can in turn be used to generate proofs of new conjectures. Our preliminary experiments show that the inferred models are generally accurate (contain few false-positive sequences) and that representing existing proofs in such a way can be very useful when guiding new ones.Peer-reviewedPost-printInternational Conference, CICM 2014, Coimbra, Portugal, July 7-11, 2014
Interactive Simplifier Tracing and Debugging in Isabelle

The Isabelle proof assistant comes equipped with a very powerful tactic for
term simplification. While tremendously useful, the results of simplifying a
term do not always match the user's expectation: sometimes, the resulting term
is not in the form the user expected, or the simplifier fails to apply a rule.
We describe a new, interactive tracing facility which offers insight into the
hierarchical structure of the simplification with user-defined filtering,
memoization and search. The new simplifier trace is integrated into the
Isabelle/jEdit Prover IDE.Comment: Conferences on Intelligent Computer Mathematics, 201
Digital Repository of Mathematical Formulae

The purpose of the NIST Digital Repository of Mathematical Formulae (DRMF) is
to create a digital compendium of mathematical formulae for orthogonal
polynomials and special functions (OPSF) and of associated mathematical data.
The DRMF addresses needs of working mathematicians, physicists and engineers:
providing a platform for publication and interaction with OPSF formulae on the
web. Using MediaWiki extensions and other existing technology (such as software
and macro collections developed for the NIST Digital Library of Mathematical
Functions), the DRMF acts as an interactive web domain for OPSF formulae.
Whereas Wikipedia and other web authoring tools manifest notions or
descriptions as first class objects, the DRMF does that with mathematical
formulae. See http://gw32.iu.xsede.org/index.php/Main_Page
Towards the Formal Reliability Analysis of Oil and Gas Pipelines

It is customary to assess the reliability of underground oil and gas
pipelines in the presence of excessive loading and corrosion effects to ensure
a leak-free transport of hazardous materials. The main idea behind this
reliability analysis is to model the given pipeline system as a Reliability
Block Diagram (RBD) of segments such that the reliability of an individual
pipeline segment can be represented by a random variable. Traditionally,
computer simulation is used to perform this reliability analysis but it
provides approximate results and requires an enormous amount of CPU time for
attaining reasonable estimates. Due to its approximate nature, simulation is
not very suitable for analyzing safety-critical systems like oil and gas
pipelines, where even minor analysis flaws may result in catastrophic
consequences. As an accurate alternative, we propose to use a
higher-order-logic theorem prover (HOL) for the reliability analysis of
pipelines. As a first step towards this idea, this paper provides a
higher-order-logic formalization of reliability and the series RBD using the
HOL theorem prover. For illustration, we present the formal analysis of a
simple pipeline that can be modeled as a series RBD of segments with
exponentially distributed failure times.Comment: 15 page
Socio-economic inequalities: a statistical physics perspective

Socio-economic inequalities are manifested in different aspects of our social
life. We discuss various aspects, beginning with the evolutionary and
historical origins, and discussing the major issues from the social and
economic point of view. The subject has attracted scholars from across various
disciplines, including physicists, who bring in a unique perspective to the
field. The major attempts to analyze the results, address the causes, and
understand the origins using statistical tools and statistical physics concepts
are discussed.Comment: 26 pages, 7 figs. review article. To be published in "Econophysics
  and Data Driven Modelling of Market Dynamics", Eds. F Abergel, H. Aoyama,
  B.K. Chakrabarti, A. Chakraborti, A. Ghosh, New Economic Windows, Springer
  (2015
The Truth about Accuracy

When we evaluate the outcomes of investigative actions as justified or unjustified, good or bad, rational or irrational, we make, in a broad sense of the term, evaluative judgments about them. We look at operational accuracy as a desirable and evaluable quality of the outcomes and explore how the concepts of accuracy and precision, on the basis of insights borrowed from pragmatics and measurement theory, can be seen to do useful work in epistemology. Operational accuracy (but not metaphysical accuracy!) focuses on how a statement fits an explicit or implicit standard set by participants involved in a shared project. While truth can remain a thin semantic property of propositions, operational accuracy, as a quality of an outcome of inquiry and typically attached to a statement, a model, a diagram or a representation is an evaluation based on the non-epistemic goals set by the goal of inquiry (which every inquiry has), and a substantial evaluative notion. The goals, often made explicit by relevant questions in a context of inquiry, act as a filter, with truths a reliable epistemic method has access to functioning as input, and accurate representations as its output. Responsible inquiry seeks pragmatic equilibrium between what reliable knowledge on the one hand and degrees of accuracy required by the goal of inquiry.status: publishe