pinecone/core-2020-05-10-deduplication huggingface dataset:
Conflation confers concurrency

Session types provide a static guarantee that concurrent programs respect communication protocols. Recent work has explored a correspondence between proof rules and cut reduction in linear logic and typing and evaluation of process calculi. This paper considers two approaches to extend logically-founded process calculi. First, we consider extensions of the process calculus to more closely resemble π-calculus. Second, inspired by denotational models of process calculi, we consider conflating dual types. Most interestingly, we observe that these approaches coincide: conflating the multiplicatives (⊗ and  ⅋) allows processes to share multiple channels; conflating the additives (⊕ and &) provides nondeterminism; and conflating the exponentials (! and ?) yields access points, a rendezvous mechanism for initiating session typed communication. Access points are particularly expressive: for example, they are sufficient to encode concurrent state and general recursion
Certifying Data in Multiparty Session Types

© Springer International Publishing Switzerland 2016.Multiparty session types (MPST) are a typing discipline for ensuring the coordination and orchestration of multi-agent communication in concurrent and distributed programs. However, by mostly focusing on the communication aspects of concurrency, MPST are often unable to capture important data invariants in programs. In this work we propose to increase the expressiveness of MPST by considering a notion of value dependencies in order to certify invariants of exchanged data in concurrent and distributed settings
iFloW: an integrated logistics software system for inbound supply chain traceability

Visibility plays an important role in supply chain management. Such visibility is not only important for better planning, but especially for real-time execution related with the traceability of goods. In inbound supply chain management, logistics planners need to trace raw materials from their requests in order to properly plan a plant’s production. The iFloW (Inbound Logistics Tracking System) integrates logistics providers IT applications and Global Positioning System (GPS) technology to track and trace incoming freights. The Estimated Time
of Arrival (ETA) is updated in real-time allowing an improved materials planning process. This paper presents the iFloW project and describes how these issues are addressed and validated in a real pilot project.This research is sponsored by the Portugal Incentive System for Research and technological Development PEst-UID/CEC/00319/2013 and by project in co-promotion no 36265/2013 (Project HMIExcel—2013–2015)
Translation of Heterogeneous Databases into RDF, and Application to the Construction of a SKOS Taxonomical Reference

International audienceWhile the data deluge accelerates, most of the data produced remains locked in deep Web databases. For the linked open data to benefit from the potential represented by this huge amount of data, it is crucial to come up with solutions to expose heterogeneous databases as linked data. The xR2RML mapping language is an endeavor towards this goal: it is designed to map various types of databases to RDF, by flexibly adapting to heterogeneous query languages and data models while remaining free from any specific language. It extends R2RML, the W3C recommendation for the mapping of relational databases to RDF, and relies on RML for the handling of various data formats. In this paper we present xR2RML, we analyse data models of several modern databases as well as the format in which query results are returned , and we show how xR2RML translates any result data element into RDF, relying on existing languages such as XPath and JSONPath when necessary. We illustrate some features of xR2RML such as the generation of RDF collections and containers, and the ability to deal with mixed data formats. We also describe a real-world use case in which we applied xR2RML to build a SKOS thesaurus aimed at supporting studies on History of Zoology, Archaeozoology and Conservation Biology
A personalized and context-aware news offer for mobile devices

For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer
Side effects of school inspection : motivations and contexts for strategic responses.

This chapter introduces three categories of unintended consequences from school inspections: (1) intended strategic behaviour where schools manipulate the inspection assessment through window dressing, misrepresentation or gaming, (2) unintended strategic behaviour when schools narrow their educational practices as a result of the behaviour of the assessor and/or by the method of working used for the assessment, and (3) other types of consequences, such as stress, anxiety and increased workload. As many inspection systems use standardized student achievement tests to evaluate school output, a fourth category on unintended responses to high stakes testing will also be introduced.\ud
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The results from a recent systematic literature review will be used to provide evidence of responses in each of the four categories. The review shows that most studies present examples from England and previous case study work from Perryman (J Educ Policy 21(2):147–161, 2006) will therefore offer more in-depth views of how an English school responds strategically to school inspections. The final section of the chapter provides explanations of the conditions under which such responses may occur
Electrochemically gated graphene field-effect transistor for extracellular cell signal recording

This work presents an experimental characterization of electrochemically gated graphene field-effect transistors (EGFETs) to measure extracellular cell signals. The performance of the EGFETs was evaluated using cardiomyocytes cells. Extracellular signals with a peak value of 0.4 pico-amperes (pA) embedded in a noise level of 0.1 pA were recorded. Signals in current mode were compared with signals recorded as a voltage. Signals below 28 μV of magnitude can be detected in a noise floor of 7 μV with a signal-to-noise ratio of 4
Moments of flux in intermediary liability for copyright infringement

This chapter provides an overview of a recent shift in regulatory strategies to address copyright infringement toward enlisting the assistance of general purpose Internet Service Providers. In Australia, the High Court held in 2012 that iiNet, a general purpose ISP, had no legal duty to police what its subscribers did with their internet connections. We provide an overview of three recent developments in Australian copyright law since that decision that demonstrate an emerging shift in the way that obligations are imposed on ISPs to govern the actions of their users without relying on secondary liability. The first is a new privately negotiated industry code that introduces a 'graduated response' system that requires ISPs to pass on warnings to subscribers who receive allegations of infringement. The second involves a recent series of Federal Court cases where rightsholders made a partially successful application to require ISPs to hand over the identifying details of subscribers whose households are alleged to have infringed copyright. The third is a new legislative scheme that will require ISPs to block access to foreign websites that 'facilitate' infringement. We argue that these shifts represent a greater sophistication in approaches to enrolling general purpose intermediaries in the regulatory project. We also suggest that these shifts represent a potentially disturbing trend towards enforcement of copyright law in a way that does not provide strong safeguards for the legitimate constitutional due process interests of users. We conclude with a call for greater attention and research to better understand how intermediaries make decisions when governing the conduct of users, how those decisions may be influenced by both state and non-state actors, and how the rights of individuals to due process can be adequately protected
An (MI)LP-based Primal Heuristic for 3-Architecture Connected Facility
  Location in Urban Access Network Design

We investigate the 3-architecture Connected Facility Location Problem arising
in the design of urban telecommunication access networks. We propose an
original optimization model for the problem that includes additional variables
and constraints to take into account wireless signal coverage. Since the
problem can prove challenging even for modern state-of-the art optimization
solvers, we propose to solve it by an original primal heuristic which combines
a probabilistic fixing procedure, guided by peculiar Linear Programming
relaxations, with an exact MIP heuristic, based on a very large neighborhood
search. Computational experiments on a set of realistic instances show that our
heuristic can find solutions associated with much lower optimality gaps than a
state-of-the-art solver.Comment: This is the authors' final version of the paper published in:
  Squillero G., Burelli P. (eds), EvoApplications 2016: Applications of
  Evolutionary Computation, LNCS 9597, pp. 283-298, 2016. DOI:
  10.1007/978-3-319-31204-0_19. The final publication is available at Springer
  via http://dx.doi.org/10.1007/978-3-319-31204-0_1
Measuring diversity of socio-cognitively inspired ACO search

In our recent research, we implemented an enhancement of Ant Colony Optimization incorporating the socio-cognitive dimension of perspective taking. Our initial results suggested that increasing the diversity of ant population - introducing different pheromones, different species and dedicated inter-species relations - yielded better results. In this paper, we explore the diversity issue by introducing novel diversity measurement strategies for ACO. Based on these strategies we compare both classic ACO and its socio-cognitive variation
Dangerousness Metric for Gene Regulated Car Driving

In this paper, we show how a dangerousness metric can be used to modify the input of a gene regulatory network when plugged to a virtual car. In the context of the 2015 Simulated Car Racing Championship organized during GECCO 2015, we have developed a new cartography methodology able to inform the controller of the car about the incoming complexity of the track: turns (slipperiness, angle, etc.) and bumps. We show how this dangerousness metric improves the results of our controller and outperforms other approaches on the tracks used in the competition
Simulation of BPMN process models: current BPM tools capabilities

"The 2016 World Conference on Information Systems and Technologies (WorldCIST'16)"Nowadays, more and more organizations are using Business Process Management (BPM) to prepare themselves to deal, in an effective way, with the increasingly difficult conditions of modern markets. Essential to BPM is the collection of tools which support the operationalization of the business process concept – BPM tools. These tools deal with business process models, which have to be described with a suitable language. In the present, BPMN is considered the standard modeling language to describe business processes. Once a business process is modeled, a process simulation approach might be used in order to find its optimized version. Therefore, the simulation of business process models, such as those defined in BPMN, appears as an obvious way of improving processes. This paper advances work previously published by the authors regarding BPM tools capabilities in terms of the simulation of BPMN process models. In this context a platform to support the characterization of BPM tools regarding process simulation capabilities has been developed. This platform might be helpful to users who want to select the most adequate BPM tool regarding their simulation needs.info:eu-repo/semantics/publishedVersio
Business process modeling languages: a comparative framework

Underlying any Business Process Management (BPM) project is the need to represent business processes, using an appropriate language. In this paper, based on a thorough review of the relevant literature, we made a comparative analysis of five business process modeling languages, widely used in the context of BPM projects. The main objective is to understand the strengths and major limitations of each one, in order to draw a comparative perspective between them. For this purpose, we have created a comparative framework in which each one of the languages are characterized regarding a number of relevant criteria. Finally, a prototype specifically developed to support this framework, is presented. The purpose of this prototype is to assist users in choosing a suitable business process modeling language, according to their specific needs.info:eu-repo/semantics/publishedVersio
A personal assistant for health care professionals based on clinical protocols

Current tools to operationalize Computer-Interpretable Guidelines focus mainly on displaying recommendations rather than assisting health care professionals in their daily activities. Furthermore, their underlying models have limitations at the level of temporal representation that hinder the accurate depiction of clinical protocols in a few specific situations. This work identifies such situations and proposes a comprehensive temporal model based on OntologyWeb Language (OWL), along with a web-based tool that provides an alternative way to deploy and view clinical protocols. This is evaluated through a case study featuring a clinical protocol for the treatment of colon cancer. It was possible to observe that the model was able to represent the majority of temporal patterns, specially those with periodic events and temporal restrictions about the state of a patient.This work has been supported by FCT Fundacao para a Ciencia e Tecnologia within the Project Scope UID/CEC/00319/2013. The work of Tiago Oliveira is supported by a FCT grant with the reference SFRH/BD/85291/2012.info:eu-repo/semantics/publishedVersio
RetweetPatterns: Detection of Spatio-Temporal Patterns of Retweets

International audienceSocial media is strongly present in people's everyday life and Twitter is one example that stands out. The data within these types of services can be analyzed in order to discover useful knowledge. One interesting approach is to use data mining techniques to perceive hidden behaviours and patterns. The primary focus of this paper is the identification of patterns of retweets and to understand how information spreads over time in Twitter. The aim of this work lies in the adaptation of the GetMove tool, that is capable of extracting spatio-temporal pattern tra-jectories, and TweeProfiles, that identifies tweet profiles regarding several dimensions: spatial, temporal, social and content. We hope that the more flexible clustering strategy from TweeProfiles will enhance the results extracted by GetMove. We study the application of said mechanism to one case study and developed a visualization tool to interpret the results
Implementation of multiple criteria decision analysis approaches in the supplier selection process: a case study

Supplier evaluation and selection is recognized as a multiple criteria problem. Having considerable economic impact and influencing a competitive position of a buyer, supplier selection has been modelled by different multiple criteria decision analysis approaches. This case study focuses on the reported "relevance gap" between theoretical approaches to the supplier selection problem and practice. The research was conducted in a textile group, addressing a typical buying situation of a main raw material. The decision process was structured with weighted score, AHP and goal programming models. Three models elaborated have led to the very similar output, recognized as realistic and consistent by the decision makers. Acquired skills of multiple criteria decision analysis were considered as beneficial for supplier selection decisions.This work has been supported by FCT - Fundação para a Ciência e Tecnologia in the scope of the PEst-UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio
Multiple case study of the supplier selection decision process

The complex and important problem of the supplier selection has been modelled with the involvement and integration of different multiple criteria decision techniques. Nevertheless, there is little empirical evidence of the relevance of such approaches to the procurement practice. In order to overcome the relevance gap it is imperative to analyze the practical decision process in the procurement function. With this aim an exploratory multiple case study was undertaken, based on semi-structured interviews with senior procurement managers of eight Portuguese enterprises, and triangulation with previous research. The results suggest that supplier selection decisions tend to be based on the non-compensatory decision strategy (conjunctive decision rule) in the pre-selection stage, followed by the price bidding and qualitative analysis in the stage of final choice.This work has been supported by FCT – Fundação para a Ciência e Technologia within the Project Scope: PEst-OE/EEI/UI0319/2014.info:eu-repo/semantics/publishedVersio
Decision support in Big Data contexts: a business intelligence solution

In the last few years we all have witnessed an enormous growth in the production of data. According to some estimates, ninety percent of the existing world’s data was created over the past two years! Indeed, we are in the era of Big Data which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of smart devices, mobile applications, cloud computing, and social networks and, more recently, with the advent of the Internet of Things (IoT), data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data, which is the main purpose of Business Intelligence. In this paper we continue the presentation of an experiment in which data obtained from a NoSQL database (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.info:eu-repo/semantics/publishedVersio
Likelihood-free extensions for Bayesian sequentially designed experiments

When considering a Bayesian sequential design framework, sequential Monte Carlo (SMC) algorithms are a natural approach. However, these algorithms require the likelihood function to be evaluated. Therefore, they cannot be applied in cases where the likelihood is not available or is intractable. To overcome this limitation, we propose likelihood-free extensions of the standard SMC algorithm. We also investigate a specific simulation-based approximation of the likelihood known as the synthetic likelihood. The algorithms are applied and tested on a well-studied sequential design problem for estimating a non-linear function of linear regression parameters
Efficient design and evaluation of countermeasures against fault attacks using formal verification

This paper presents a formal verification framework and tool that evaluates the robustness of software countermeasures against fault-injection attacks. By modeling reference assembly code and its protected variant as automata, the framework can generate a set of equations for an SMT solver, the solutions of which represent possible attack paths. Using the tool we developed, we evaluated the robustness of state-of-the-art countermeasures against fault injection attacks. Based on insights gathered from this evaluation, we analyze any remaining weaknesses and propose applications of these countermeasures that are more robust
Behavior and path planning for the coalition of cognitive robots in
  smart relocation tasks

In this paper we outline the approach of solving special type of navigation
tasks for robotic systems, when a coalition of robots (agents) acts in the 2D
environment, which can be modified by the actions, and share the same goal
location. The latter is originally unreachable for some members of the
coalition, but the common task still can be accomplished as the agents can
assist each other (e.g. by modifying the environment). We call such tasks smart
relocation tasks (as the can not be solved by pure path planning methods) and
study spatial and behavior interaction of robots while solving them. We use
cognitive approach and introduce semiotic knowledge representation - sign world
model which underlines behavioral planning methodology. Planning is viewed as a
recursive search process in the hierarchical state-space induced by sings with
path planning signs reside on the lowest level. Reaching this level triggers
path planning which is accomplished by state of the art grid-based planners
focused on producing smooth paths (e.g. LIAN) and thus indirectly guarantying
feasibility of that paths against agent's dynamic constraints.Comment: As submitted to the 4th International Conference on Robot
  Intelligence Technology and Applications (RiTA-2015), Bucheon, Korea,
  December 14-16, 201
Cloud-based robots and intelligent space teleoperation tools

Despite an idea of robotic system teleoperation is a relatively old concept, here we present its enhancements heading to an interconnection of teleoperation and collecting relevant information from the environment where robots act. This environment should be an intelligent space featured with various devices and sensors, which allows to obtain, preprocess and stores data in the cloud. Those data should provide relevant information for teleoperator or directly for robots, which act autonomously. For this purpose, we developed cloud-based tools, named Telescope v2. It is a platform-independent system for remote monitoring and controlling various systems. In this paper, we introduce this system, its abilities, and compare it with its network-based ancestor, Telescope v1. We analyze measurements of latency and response time when our new system is used for teleoperation in different places equipped with various Internet bandwidths