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Experimental set-up of DC PEV charging station supported by open and interoperable communication technologies
No full textThis paper is focused on a laboratory smart power architecture designed to experiment fast charging and V2G operations for road electric and plug-in hybrid vehicles. The analysed power configuration is based on a DC bus architecture, which presents the main advantage of an easy integration of renewable energy sources and buffered storage systems. The energy management of this system is supported by open and interoperable communication technologies, which adopts Open Charge Point Protocol (OCPP) as network communication and application protocol. This allows the PEV charge point to exchange data and commands with any central management system over the Internet with the goal of ensuring truly interoperability and scalability. Furthermore, both short- and long-range wireless communication technologies are supported, which facilitates easy integration into existing communication infrastructures
A matter of words: NLP for quality evaluation of Wikipedia medical articles
No full textAutomatic quality evaluation of Web information is a task with many fields of applications and of great relevance, especially in critical domains, like the medical one. We move from the intuition that the quality of content of medical Web documents is affected by features related with the specific domain. First, the usage of a specific vocabulary (Domain Informativeness); then, the adoption of specific codes (like those used in the infoboxes of Wikipedia articles) and the type of document (e.g., historical and technical ones). In this paper, we propose to leverage specic domain features to improve the results of the evaluation of Wikipedia medical articles. We rely on Natural Language Processing (NLP) and dictionaries-based techniques in order to extract the biomedical concepts in a text. The results of our experiments confirm that, by considering domain-oriented features, it is possible to obtain sensible improvements with respect to existing solutions, mainly for those articles that other approaches have less correctly classified
Editorial: repetitive Structures in Biological Sequences: algorithms and applications
No full textRepetitive structures in biological sequences are emerging as an active focus of research and the unifying concept of ?repeatome? (the ensemble of knowledge associated with repeating structures in genomic/proteomic data) has been recently proposed in order to highlight several converging trends
Multidimensional range queries on hierarchical Voronoi overlays
No full textThe definition of a support for multi-attribute range queries is mandatory for highly distributed systems. Even if several solutions have been proposed in the last decade, most of them do not meet the requirements of recent platforms, like IoT or smart cities. The paper presents an approach that builds a multidimensional Voronoi graph by exploiting the attributes of the objects published by a node. Our solution overcomes the curse of dimensionality issue affecting Voronoi Tessellations in high dimensional spaces by defining a Voronoi hierarchy. The paper formally defines the structure, analysis the complexity of the operations and presents experimental results
Information diffusion in distributed OSN: The impact of trusted relationships
No full textDistributed Online Social Networks (DOSN) are a valid alternative to OSN based on peer-to-peer communications. Without centralised data management, DOSN must provide the users with higher level of control over their personal information and privacy. Thus, users may wish to restrict their personal network to a limited set of peers, depending on the level of trust with them. This means that the effective social network (used for information exchange) may be a subset of the complete social network, and may present different structural patterns, which could limit information diffusion. In this paper, we estimate the capability of DOSN to diffuse content based on trust between social peers. To have a realistic representation of a OSN friendship graph, we consider a large-scale Facebook network, from which we estimate the trust level between friends. Then, we consider only social links above a certain threshold of trust, and we analyse the potential capability of the resulting graph to spread information through several structural indices. We test four possible thresholds, coinciding with the definition of personal social circles derived from sociology and anthropology. The results show that limiting the network to "active social contacts" leads to a graph with high network connectivity, where the nodes are still well-connected to each other, thus information can potentially cover a large number of nodes with respect to the original graph. On the other hand, the coverage drops for more restrictive assumptions. Nevertheless the re-insertion of a single excluded friend for each user is sufficient to obtain good coverage (i.e., always higher than 40 %) even in the most restricted graphs. We also analyse the potential capability of the network to spread information (i.e., network spreadability), studying the properties of the social paths between any pairs of users in the graph, which represent the effective channels traversed by information. The value of contact frequency between pairs of users determines a decay of trust along the path (the higher the contact frequency the lower the decay), and a consequent decay in the level of trustworthiness of information traversing the path. We show that selecting the link to re-insert in the network with probability proportional to its level of trust is the best re-insertion strategy, as it leads to the best connectivity/spreadability combination
Bioinspired Security Analysis of Wireless Protocols
No full textFraglets represent an execution model for communication protocols that resembles the chemical reactions in living organisms. The strong connection between their way of transforming and reacting and formal rewriting systems makes a fraglet program amenable to automatic verification. Grounded on past work, this paper investigates feasibility of adopting fraglets as model for specifying security protocols and analysing their properties. In particular, we give concrete sample analyses over a secure RFID protocol, showing evolution of the protocol run as chemical dynamics and simulating an adversary trying to circumvent the intended steps. The results of our analysis confirm the effectiveness of the cryptofraglets framework for the model and analysis of security properties and eventually show its potential to identify and uncover protocol flaws
Protein complex prediction for large protein protein interaction networks with the Core&Peel
No full textBackgroundBiological networks play an increasingly important role in the exploration of functional modularity and cellular organization at a systemic level. Quite often the first tools used to analyze these networks are clustering algorithms. We concentrate here on the specific task of predicting protein complexes (PC) in large protein-protein interaction networks (PPIN). Currently, many state-of-the-art algorithms work well for networks of small or moderate size. However, their performance on much larger networks, which are becoming increasingly common in modern proteome-wise studies, needs to be re-assessed.Results and discussionWe present a new fast algorithm for clustering large sparse networks: Core&Peel, which runs essentially in time and storage O(a(G)m+n) for a network G of n nodes and m arcs, where a(G) is the arboricity of G (which is roughly proportional to the maximum average degree of any induced subgraph in G). We evaluated Core&Peel on five PPI networks of large size and one of medium size from both yeast and homo sapiens, comparing its performance against those of ten state-of-the-art methods. We demonstrate that Core&Peel consistently outperforms the ten competitors in its ability to identify known protein complexes and in the functional coherence of its predictions. Our method is remarkably robust, being quite insensible to the injection of random interactions. Core&Peel is also empirically efficient attaining the second best running time over large networks among the tested algorithms.ConclusionsOur algorithm Core&Peel pushes forward the state-of the-art in PPIN clustering providing an algorithmic solution with polynomial running time that attains experimentally demonstrable good output quality and speed on challenging large real networks
The car as an ambient sensing platform
No full textIn recent years, cars have evolved from purely mechanical to veritable cyber-physical systems that generate large amounts of real-time data. This data is instrumental to the proper working of the vehicle itself, but makes them amenable to a multitude of other uses. For instance, GPS information has recently been used for a large number of mobility studies in the academic community [1]?[5], as well as to feed traffic apps such as Google TrafficTM and WazeTM. This use of vehicle data is already having a profound impact in science, industry, economy, and society at large. Now, imagine than instead of accessing one single source of vehicle-generated data (GPS), one can access the entire wealth of data exchanged on the Controller Area Network (CAN) bus in near real-time ? amounting to over 4,000 signals sampled at high frequency, corresponding to a few Gigabytes of data per hour. What would be the implications, opportunities, and challenges sparked by this transition
Effects of frequency and regularity in an integrative model of word storage and processing
No full textConsiderable evidence has accrued on the role of paradigms as both theoretical and cognitive structures regimenting the way words are processed and acquired. The evidence supports a view of the lexicon as an emergent integrative system, where word forms are concurrently and competitively stored as repeatedly successful processing patterns, and on-line processing crucially depends on the internal organisation of stored patterns. In spite of converging evidence in this direction, little efforts have been put so far into providing detailed, algorithmic models of the interaction between lexical token frequency, paradigm frequency, and paradigm regularity in word processing and acquisition. Here we propose a neuro-computational account of the frequency/regularity interaction, and discuss some of its theoretical implications by analysing experimental results in the computational framework of Temporal Self-Organising Maps. Detailed quantitative analysis shows that the model provides a unitary explanatory framework bringing together insights from neighbour family effects on word recognition and production, evidence from family size effects in serial lexical access and paradigm-based dynamics in lexical acquisition
Journal of Limnology Vol. 75 (s1)
No full textProceedings of the 6th National Congress of Limnology. Guest Editors: Javier Alcocer (Facultad de Estudios Superiores Iztacala, Universidad Nacional Aut?noma de M?xico, Ciudad de Mexico); Mart?n Merino-Ibarra (Instituto de Ciencias del Mar y Limnolog?a, Universidad Nacional Aut?noma de M?xico, Ciudad de Mexico); Elva Escobar-Briones (Instituto de Ciencias del Mar y Limnolog?a, Universidad Nacional Aut?noma de M?xico, Ciudad de Mexico