Scalable XML Collaborative Editing with Undo short paper

Commutative 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

Abstract unordered and ordered trees CRDT

Trees are fundamental data structure for many areas of computer science and system engineering. In this report, we show how to ensure eventual consistency of optimistically replicated trees. In optimistic replication, the different replicas of a distributed system are allowed to diverge but should eventually reach the same value if no more mutations occur. A new method to ensure eventual consistency is to design Conflict-free Replicated Data Types (CRDT). In this report, we design a collection of tree CRDT using existing set CRDTs. The remaining concurrency problems particular to tree data structure are resolved using one or two layers of correction algorithm. For each of these layer, we propose different and independent policies. Any combination of set CRDT and policies can be constructed, giving to the distributed application programmer the entire control of the behavior of the shared data in face of concurrent mutations. We also propose to order these trees by adding a positioning layer which is also independent to obtain a collection of ordered tree CRDTs

Evolving Market Performance in Brazilian Futures Contracts Using Relative Efficiency

Marketing,

A fuzzy approach for the network congestion problem

In the recent years, the unpredictable growth of the Internet has moreover pointed out the congestion problem, one of the problems that historicallyha ve affected the network. This paper deals with the design and the evaluation of a congestion control algorithm which adopts a FuzzyCon troller. The analogyb etween Proportional Integral (PI) regulators and Fuzzycon trollers is discussed and a method to determine the scaling factors of the Fuzzycon troller is presented. It is shown that the Fuzzycon troller outperforms the PI under traffic conditions which are different from those related to the operating point considered in the design

Migration Profile MALI. 1.Structural Migration Profile 2. Flash Migration Profile (August - October 2016)

This publication reproduces the first new generation of Migration Profiles (on Mali). The Migration Profile aims of covering the current knowledge gaps on migration and development at regular, short intervals (3/6 months) and at a sub-national coverage, providing tailored and regular monitoring and ensuring comparability across countries. It links migration, development and humanitarian aspects as well as analyses on the EU strategic role vis-à-vis the third country, including its financial developmental and humanitarian aid support,to support the identification of relevant development priorities also in the short-medium term.JRC.E.6-Demography, Migration and Governanc

Salento Atmosphere and the Role of Movies

In this paper we show how cinema, due to the inherent strength of the images it produces, interacts or even interferes with the processes of place image building. The topic under discussion is then absolutely crucial to geography, being it the science of place. The author, starting by explaining the reciprocity (cycling) relation existing between cinema and place, analyzes by means of a qualitative approach the case of Salento and the creation of its “atmosphere” through cinematic images, taking into account those movies that most have contributed to it. Concerning film-induced tourism the author found that, from the supply side, the local tourism system did not still fully adapted itself to the new needs of this segment. However, there is a great potential for its development, since a latent demand seems to exist and the activities of Apulia Film Commission are greatly contributing to it.Nel presente lavoro si evidenzia come il cinema, grazie alla forza intrinseca delle immagini che produce, interagisce quando non interferisce con i processi di costruzione dell’immagine del luogo. L’argomento in discussione è quindi assolutamente cruciale per la disciplina geografica che si qualifica come scienza dei luoghi. L’autrice, partendo dall’illustrare la relazione circolare di reciprocità che lega cinema e territorio, analizza, attraverso un approccio qualitativo, il caso del Salento e della creazione della “atmosfera” del luogo a partire dalle immagini cinematografiche, prendendo in esame i film che più hanno contribuito alla formazione della stessa. Volgendo poi l’attenzione ad una delle più immediate implicazioni territoriali di tale processo, il cineturismo, l’autrice sottolinea come, dal lato dell’offerta, il sistema turistico locale non si sia ancora pienamente adattato alle esigenze di questo nuovo segmento. Emerge, tuttavia, un grande potenziale per lo sviluppo del settore: esiste, infatti, una domanda ancora in parte inespressa, destinata ad aumentare grazie all’attività dell’Apulia Film Commission, che moltiplica le immagini del territorio, attirando un grande interesse, anche mediatico, sul Salento

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

Lotte e problemi sociali in Cassio Dione

This article studies the way in which Dio deals with social issues in his Roman History. In particular, it examines the rise of the parvenus in Severan Rome, the problem of indebtedness of individual citizens and the state, the recurring phenomenon of banditry, famines and ‘hunger revolts’. The impression of the historian’s insensitivity to the needs of the most disadvantaged social classes is diminished by the analysis of his narrative concerning the struggle between patricians and plebeians in the archaic age, which Dio re-examines also in light of the problems of his time, and in which an unexpected attention to the motives of the poor emerges

Clickstream Data Analysis: A Clustering Approach Based on Mixture Hidden Markov Models

Nowadays, the availability of devices such as laptops and cell phones enables one to browse the web at any time and place. As a consequence, a company needs to have a website so as to maintain or increase customer loyalty and reach potential new customers. Besides, acting as a virtual point-of-sale, the company portal allows it to obtain insights on potential customers through clickstream data, web generated data that track users accesses and activities in websites. However, these data are not easy to handle as they are complex, unstructured and limited by lack of clear information about user intentions and goals. Clickstream data analysis is a suitable tool for managing the complexity of these datasets, obtaining a cleaned and processed sequential dataframe ready to identify and analyse patterns. Analysing clickstream data is important for companies as it enables them to under stand differences in web user behaviour while they explore websites, how they move from one page to another and what they select in order to define business strategies tar geting specific types of potential costumers. To obtain this level of insight it is pivotal to understand how to exploit hidden information related to clickstream data. This work presents the cleaning and pre-processing procedures for clickstream data which are needed to get a structured sequential dataset and analyses these sequences by the application of Mixture of discrete time Hidden Markov Models (MHMMs), a statisti cal tool suitable for clickstream data analysis and profile identification that has not been widely used in this context. Specifically, hidden Markov process accounts for a time varying latent variable to handle uncertainty and groups together observed states based on unknown similarity and entails identifying both the number of mixture components re lating to the subpopulations as well as the number of latent states for each latent Markov chain. However, the application of MHMMs requires the identification of both the number of components and states. Information Criteria (IC) are generally used for model selection in mixture hidden Markov models and, although their performance has been widely studied for mixture models and hidden Markov models, they have received little attention in the MHMM context. The most widely used criterion is BIC even if its performance for these models depends on factors such as the number of components and sequence length. Another class of model selection criteria is the Classification Criteria (CC). They were defined specifically for clustering purposes and rely on an entropy measure to account for separability between groups. These criteria are clearly the best option for our purpose, but their application as model selection tools for MHMMs requires the definition of a suitable entropy measure. In the light of these considerations, this work proposes a classification criterion based on an integrated classification likelihood approach for MHMMs that accounts for the two latent classes in the model: the subpopulations and the hidden states. This criterion is a modified ICL BIC, a classification criterion that was originally defined in the mixture model context and used in hidden Markov models. ICL BIC is a suitable score to identify the number of classes (components or states) and, thus, to extend it to MHMMs we de fined a joint entropy accounting for both a component-related entropy and a state-related conditional entropy. The thesis presents a Monte Carlo simulation study to compare selection criteria per formance, the results of which point out the limitations of the most commonly used infor mation criteria and demonstrate that the proposed criterion outperforms them in identify ing components and states, especially in short length sequences which are quite common in website accesses. The proposed selection criterion was applied to real clickstream data collected from the website of a Sicilian company operating in the hospitality sector. Data was modelled by an MHMM identifying clusters related to the browsing behaviour of web users which provided essential indications for developing new business strategies. This thesis is structured as follows: after an introduction on the main topics in Chapter 1, we present the clickstream data and their cleaning and pre-processing steps in Chapter 2; Chapter 3 illustrates the structure and estimation algorithms of mixture hidden Markov models; Chapter 4 presents a review of model selection criteria and the definition of the proposed ICL BIC for MHMMs; the real clickstream data analysis follows in Chapter 5