pinecone/core-2020-05-10-deduplication huggingface dataset:
A functional density-based nonparametric approach for statistical calibration

International audienceIn this paper a new nonparametric functional method is introduced for predicting a scalar random variable $Y$ from a functional random variable $X$. The resulting prediction has the form of a weighted average of the training data set, where the weights are determined by the conditional probability density of $X$ given $Y$, which is assumed to be Gaussian. In this way such a conditional probability density is incorporated as a key information into the estimator. Contrary to some previous approaches, no assumption about the dimensionality of $\mathbb{E}(X|Y=y)$ is required. The new proposal is computationally simple and easy to implement. Its performance is shown through its application to both simulated and real data
Communication and trust in the bounded confidence model

The communication process in a situation of emergency is discussed within the
Scheff theory of shame and pride. The communication involves messages from
media and from other persons. Three strategies are considered: selfish (to
contact friends), collective (to join other people) and passive (to do
nothing). We show that the pure selfish strategy cannot be evolutionarily
stable. The main result is that the community structure is statistically
meaningful only if the interpersonal communication is weak.Comment: 6 pages, 5 figures, RevTeX, for ICCCI-201
Modelling fim expression in Escherichia coli K12

Fimbriae are structures in Escherichia coli, the expression of which is controlled by the fim operon. Understanding this expression is important because the fimbriae are important virulence factors.\ud
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This expression can be studied using targeted mutations to the DNA, which can be used to disable binding or transcription of a protein. How- ever, this can be problematic as only the net effect is observed. Turning off expression of a protein may enhance fim expression, but deactivating this protein may also repress another protein that functions as an activator of fim expression. The net result may be that fim expression goes down, so it would seem at first glance that the disabled protein was an activator of fim expression and not a repressor.\ud
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In order to understand this complex network of interactions, an agent based model of fim expression has been created. The subject of this paper is to introduce this model and to use it to disambiguate between a number of hypotheses about this system. Parameters such as binding probability will be optimised using a genetic algorithm. The final model and parameters show a good match to experimental data
Approximating Multi-Objective Hyper-Heuristics for Solving 2D Irregular Cutting Stock Problems

This article presents a method based on the multi-objective
evolutionary algorithm NSGA-II to approximate hyper-heuristics for solving irregular 2D cutting stock problems under multiple objectives. In this case, additionally to the traditional objective of minimizing the number of sheets used to fit a finite number of irregular pieces, the time required to perform the placement task is also minimized, leading to a bi-objective minimization problem with a tradeoff between the number of sheets and the time required for placing all pieces. We solve this problem using multi-objective hyper-heuristics (MOHHs), whose main idea consists of finding a set of simple heuristics which can be combined to find a general solution for a wide range of problems, where a single heuristic is applied depending on the current condition of the problem, instead of applying a unique single heuristic during the whole placement process. The MOHHs are approximated after going through a learning process by mean of the NSGA-II, which evolves combinations of condition-action rules producing at the end a set of Pareto-optimal MOHHs. We tested the approximated MMOHHs on several sets of benchmark problems, having outstanding results for most of the cases.status: publishe
New instruments and technologies for Cultural Heritage survey: full integration between point clouds and digital photogrammetry

In the last years the Geomatic Research Group of the Politecnico di Torino faced some new research topics about new instruments for point cloud generation (e.g. Time of Flight cameras) and strong integration between multi-image matching techniques and 3D Point Cloud information in order to solve the ambiguities of the already known matching algorithms. ToF cameras can be a good low cost alternative to LiDAR instruments for the generation of precise and accurate point clouds: up to now the application range is still limited but in a near future they will be able to satisfy the most part of the Cultural Heritage metric survey requirements. On the other hand multi-image matching techniques with a correct and deep integration of the point cloud information can give the correct solution for an "intelligent" survey of the geometric object break-lines, which are the correct starting point for a complete survey. These two research topics are strictly connected to a modern Cultural Heritage 3D survey approach. In this paper after a short analysis of the achieved results, an alternative possible scenario for the development of the metric survey approach inside the wider topic of Cultural Heritage Documentation is reporte
Formal Verification of Tokeneer Behaviours Modelled in fUML Using CSP

Much research work has been done on formalizing UML diagrams, but less has focused on using this formalization to analyze the dynamic behaviours between formalized components. In this paper we propose using a subset of fUML (Foundational Subset for Executable UML) as a semi-formal language, and formalizing it to the process algebraic specification language CSP, to make use of FDR as a model checker. Our formalization includes modelling the asynchronous communication framework used within fUML. This allows different interpretations of the communications model to be evaluated. To illustrate the approach, we use the modelling of the Tokeneer ID Station specifications into fUML, and formalize them in CSP to check if the model is deadlock free
Dynamic privacy management in pervasive sensor networks

This paper describes the design and implementation of a dynamic privacy management system aimed at enabling tangible privacy control and feedback in a pervasive sensor network. Our work began with the development of a potentially invasive sensor network (with high resolution video, audio, and motion tracking capabilities) featuring different interactive applications that created incentive for accepting this network as an extension of people’s daily social space. A user study was then conducted to evaluate several privacy management approaches – an active badge system for both online and on-site control, on/off power switches for physically disabling the hardware, and touch screen input control. Results from a user study indicated that an active badge for on-site privacy control is the most preferable method among all provided options. We present a set of results that yield insight into the privacy/benefit tradeoff from various sensing capabilities in pervasive sensor networks and how privacy settings and user behavior relate in these environments.Things That Think Consortiu
Merging business process models

This paper addresses the following problem: given two or more business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from an arbitrary collection of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back from which original model(s) does a given element in the merged model come from. The algorithm has been prototyped and tested against process models taken from several application domains
Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time
Scalable XML Collaborative Editing with Undo short paper

International audienceCommutative Replicated Data-Type (CRDT) is a new class of algorithms that ensures scalable consistency of replicated data. It has been successfully applied to collaborative editing of texts without complex concurrency control. In this paper, we present a CRDT to edit XML data. Compared to existing approaches for XML collaborative editing, our approach is more scalable and handles all the XML editing aspects : elements, contents, attributes and undo. Indeed, undo is recognized as an important feature for collaborative editing that allows to overcome system complexity through error recovery or collaborative conflict resolution
Measuring software systems scalability for proactive data center management

The current trend of increasingly larger Web-based applications makes scalability the key challenge when developing, deploying, and maintaining data centers. At the same time, the migration to the cloud computing paradigm means that each data center hosts an increasingly complex mix of applications, from multiple owners and in constant evolution. Unfortunately, managing such data centers in a cost-effective manner requires that the scalability properties of the hosted workloads to be accurately known, namely, to proactively provision adequate resources and to plan the most economical placement of applications. Obviously, stopping each of them and running a custom benchmark to asses its scalability properties is not an option.
In this paper we address this challenge with a tool to measure the software scalability regarding CPU availability, towards being able to predict its behavior in face of varying resources and an increasing workload. This tool does not depend on a particular application and relies only on Linux's SystemTap probing infrastructure. We validate the approach first using simulation and then in an actual system. The resulting better prediction of scalability properties should allow improved (self-) management practices.Partially funded by PT Inovação S.A
On the expressiveness and trade-offs of large scale tuple stores

Proceedings of On the Move to Meaningful Internet Systems (OTM)Massive-scale distributed computing is a challenge at our doorstep. The current exponential growth of data calls for massive-scale capabilities of storage and processing. This is being acknowledged by several major Internet players embracing the cloud computing model and offering first generation distributed tuple stores. Having all started from similar requirements, these systems ended up providing a similar service: A simple tuple store interface, that allows applications to insert, query, and remove individual elements. Further- more, while availability is commonly assumed to be sustained by the massive scale itself, data consistency and freshness is usually severely hindered. By doing so, these services focus on a specific narrow trade-off between consistency, availability, performance, scale, and migration cost, that is much less attractive to common business needs. In this paper we introduce DataDroplets, a novel tuple store that shifts the current trade-off towards the needs of common business users, pro- viding additional consistency guarantees and higher level data process- ing primitives smoothing the migration path for existing applications. We present a detailed comparison between DataDroplets and existing systems regarding their data model, architecture and trade-offs. Prelim- inary results of the system's performance under a realistic workload are also presented
Scalable transactions in the cloud: partitioning revisited

Lecture Notes in Computer Science, 6427Cloud computing is becoming one of the most used paradigms to deploy highly available and scalable systems. These systems usually demand the management of huge amounts of data, which cannot be solved with traditional nor replicated database systems as we know them. Recent solutions store data in special key-value structures, in an approach that commonly lacks the consistency provided by transactional guarantees, as it is traded for high scalability and availability. In order to ensure consistent access to the information, the use of transactions is required. However, it is well-known that traditional replication protocols do not scale well for a cloud environment. Here we take a look at current proposals to deploy transactional systems in the cloud and we propose a new system aiming at being a step forward in achieving this goal. We proceed to focus on data partitioning and describe the key role it plays in achieving high scalability.This work has been partially supported by the Spanish Government under grant TIN2009-14460-C03-02 and by the Spanish MEC under grant BES-2007-17362 and by project ReD Resilient Database Clusters (PDTC/EIA-EIA/109044/2008)
Fadip: Lightweight publish/subscribe for mobile ad hoc networks

Publish/Subscribe is an interesting communication paradigm because it fosters a high degree of decoupling between the communicating parties and provides the ability to communicate in an asynchronous way. Publish/Subscribe systems have been extensively studied for wired networks but designing a Publish/Subscribe system for mobile ad hoc networks is still a challenge. In this paper we propose a lightweight Publish/ Subscribe system for mobile ad hoc networks which uses a limited gossip mechanism to match the published messages with the subscriptions. The goal of this work is to reduce the number of exchanged messages used for communication and maintenance while keeping an acceptable delivery ratio. Experimental results show that Fadip achieves an acceptable delivery ratio even in high mobility rates.status: publishe
LiFTinG: Lightweight Freerider-Tracking Protocol in Gossip

International audienceThis paper presents LiFTinG, the first protocol to detect freeriders, including colluding ones, in gossip-based content dissemination systems with asymmetric data exchanges. LiFTinG relies on nodes tracking abnormal behaviors by cross-checking the history of their previous interactions, and exploits the fact that nodes pick neighbors at random to prevent colluding nodes from covering up each others' bad actions. We present a methodology to set the parameters of LiFTinG based on a theoretical analysis. In addition to simulations, we report on the deployment of LiFTinG on PlanetLab. In a 300-node system, where a stream of 674 kbps is broadcast, LiFTinG incurs a maximum overhead of only 8% while providing good results: for instance, with 10% of freeriders decreasing their contribution by 30%, LiFTinG detects 86% of the freeriders after only 30 seconds and wrongfully expels only a few honest nodes
Tourist trip planning functionalities: state-of-the-art and future

When tourists visit a city or region, they cannot visit every point of interest available, as they are constrained in time and budget. Tourist recommender applications help tourists by presenting a personal selection. Providing adequate tour scheduling support for these kinds of applications is a daunting task for the application developer. The objective of this paper is to demonstrate how existing models from the field of Operations Research (OR) fit this scheduling problem, and enable a wide range of tourist trip planning functionalities. Using the Orienteering Problem (OP) and its extensions to model the tourist trip planning problem, allows to deal with a vast number of practical planning problems
Personalized tourist route generation

When tourists are at a destination, they typically search for information in the Local Tourist Organizations. There, the staff determines the profile of the tourists and their restrictions. Combining this information with their up-to-date knowledge about the local attractions and public transportation, they suggest a personalized route for the tourist agenda. Finally, they fine tune up this route to better fit tourists' needs. We present an intelligent routing system to fulfil the same task. We divide this process in three steps: recommendation, route generation and route customization. We focus on the last two steps and analyze them. We model the tourist planning problem, integrating public transportation, as the Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) and we present an heuristic able to solve it on real-time. Finally, we show the prototype which generates and customizes routes in real-time
Incrementally Discovering Testable Specifications from Program Executions

The Pro Test project(1) is an EU FP7 project to develop techniques that improve the testing and verification of concurrent and distributed software systems. One of the four main work packages is concerned with the automated identification of specifications that could serve as a suitable basis for testing; this is currently a tedious and error-prone manual task that tends to be neglected in practice. This paper describes how this problem has been addressed in the Pro Test project. It describes a technique that uses test executions to refine the specification from which they are generated. It shows how the technique has been implemented and applied to real Erlang systems. It also describes in detail the major challenges that remain to be addressed in future work.Peer-reviewedPost-print8th International Symposium on Formal Methods for Components and Objects, Eindhoven, NETHERLANDS, 4-6 November 200
A comparison of word similarity measures for noun compound disambiguation

Noun compounds occur frequently in many languages, and the problem of semantic disambiguation of these phrases has many potential applications in natural language processing and other areas. One very common approach to this problem is to define a set of semantic relations which capture the interaction between the modifier and the head noun, and then attempt to assign one of these semantic relations to each compound. For example, the compound phrase flu virus could be assigned the semantic relation causal (the virus causes the flu); the relation for desert wind could be location (the wind is located in the desert). In this paper we investigate methods for learning the correct semantic relation for a given noun compound by comparing the new compound to a training set of hand-tagged instances, using the similarity of the words in each compound. The main contribution of this paper is to directly compare distributional and knowledge-based word similarity measures for this task, using various datasets and corpora. We find that the knowledge based system provides a much better performance when adequate training data is available
A quick tour of the VeriFast program verifier

This paper describes the main features of VeriFast, a sound and modular program verifier for C and Java. VeriFast takes as input a number of source files annotated with method contracts written in separation logic, inductive data type and fixpoint definitions, lemma functions and proof steps. The verifier checks that (1) the program does not perform illegal operations such as dividing by zero or illegal memory accesses and (2) that the assumptions described in method contracts hold in each execution.

Although VeriFast supports specifying and verifying deep data structure properties, it provides an interactive verification experience as verification times are consistently low and errors can be diagnosed using its symbolic debugger. VeriFast and a large number of example programs are available online at: http://www.cs.kuleuven.be/~bartj/verifast.status: publishe
Liberal Typing for Functional Logic Programs

We propose a new type system for functional logic programming which is more liberal than the classical Damas-Milner usually adopted, but it is also restrictive enough to ensure type soundness. Starting from Damas-Milner typing of expressions we propose a new notion of well-typed program that adds support for type-indexed functions, existential types, opaque higher-order patterns and generic functions-as shown by an extensive collection of examples that illustrate the possibilities of our proposal. In the negative side, the types of functions must be declared, and therefore types are checked but not inferred. Another consequence is that parametricity is lost, although the impact of this flaw is limited as "free theorems" were already compromised in functional logic programming because of non-determinism
When two is better than one : a study of ranking paradigms and their integrations for subtopic retrieval

In this paper, we consider the problem of document ranking in a non-traditional retrieval task, called subtopic retrieval. This task involves promoting relevant documents that cover many subtopics of a query at early ranks, providing thus diversity within the ranking. In the past years, several approaches have been proposed to diversify retrieval results. These approaches can be classified into two main paradigms, depending upon how the ranks of documents are revised for promoting diversity. In the first approach subtopic diversification is achieved implicitly, by choosing documents that are different from each other, while in the second approach this is done explicitly, by estimating the subtopics covered by documents. Within this context, we compare methods belonging to the two paradigms. Furthermore, we investigate possible strategies for integrating the two paradigms with the aim of formulating a new ranking method for subtopic retrieval. We conduct a number of experiments to empirically validate and contrast the state-of-the-art approaches as well as instantiations of our integration approach. The results show that the integration approach outperforms state-of-the-art strategies with respect to a number of measures
Attack--Defense Trees and Two-Player Binary Zero-Sum Extensive Form
  Games Are Equivalent - Technical Report with Proofs

Attack--defense trees are used to describe security weaknesses of a system
and possible countermeasures. In this paper, the connection between
attack--defense trees and game theory is made explicit. We show that
attack--defense trees and binary zero-sum two-player extensive form games have
equivalent expressive power when considering satisfiability, in the sense that
they can be converted into each other while preserving their outcome and their
internal structure.Comment: Added link to springerlink; Proceedings of GameSec 201