Spoken document retrieval experiments with IR-n system

This paper describes the first participation of IR-n system at Spoken Document Retrieval, focusing on the experiments we made before participation and showing the results we obtained. IR-n system is an Information Retrieval system based on passages and the recognition of sentences to define them. So, the main goal of this experiment is to adapt IR-n system to the spoken document structure by means of the utterance splitter and the overlapping passage technique allowing to match utterances and sentences.

The role of statistical and semantic features in single-document extractive summarization

This paper reports on the further results of the ongoing research analyzing the impact of a range of commonly used statistical and semantic features in the context of extractive text summarization. The features experimented with include word frequency, inverse sentence and term frequencies, stopwords filtering, word senses, resolved anaphora and textual entailment. The obtained results demonstrate the relative importance of each feature and the limitations of the tools available. It has been shown that the inverse sentence frequency combined with the term frequency yields almost the same results as the latter combined with stopwords filtering that in its turn proved to be a highly competitive baseline. To improve the suboptimal results of anaphora resolution, the system was extended with the second anaphora resolution module. The present paper also describes the first attempts of the internal document data representation.

Assessment of CO2 adsorption capacity on activated carbons by a combination of batch and dynamic tests

In this work, batch and dynamic adsorption tests are coupled for an accurate evaluation of CO2 adsorption performance for three different activated carbons obtained from olives stones by chemical activation followed by physical activation with CO2 at varying times, i.e. 20, 40 and 60 h. Kinetic and thermodynamic CO2 adsorption tests from simulated flue-gas at different temperature and CO2 pressure are carried out both in batch (a manometric equipment operating with pure CO2) and dynamic (a lab-scale fixed-bed column operating with CO2/N2 mixture) conditions. The textural characterization of the activated carbon samples shows a direct dependence of both micropore and ultramicropore volume on the activation time, hence AC60 has the higher contribution. The adsorption tests conducted at 273 and 293 K showed that, when CO2 pressure is lower than 0.3 bar, the lower the activation time the higher CO2 adsorption capacity and a ranking ωeq(AC20)>ωeq(AC40)>ωeq(AC60) can be exactly defined when T= 293 K. This result can be likely ascribed to a narrower pore size distribution of the AC20 sample, whose smaller pores are more effective for CO2 capture at higher temperature and lower CO2 pressure, the latter representing operating conditions of major interest for decarbonation of a flue-gas effluent. Moreover, the experimental results obtained from dynamic tests confirm the results derived from the batch tests in terms of CO2 adsorption capacity. It is important to highlight that the adsorption of N2 on the synthesized AC samples can be considered negligible. Finally, the importance of a proper analysis of characterization data and adsorption experimental results is highlighted for a correct assessment of CO2 removal performances of activated carbons at different CO2 pressure and operating temperature.

A new betweenness centrality measure based on an algorithm for ranking the nodes of a network

We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical values. Numerical values summarizing the information are associated to each of the nodes by means of a data matrix. After running the adapted PageRank algorithm, a ranking of the nodes is obtained, according to their importance in the network. This classification is the starting point for applying an algorithm based on the random-walk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the ranking-betweenness centrality proposed, performing some comparisons with other classical centrality measures.

Analyzing the commercial activities of a street network by ranking their nodes: a case study in Murcia, Spain

Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

Chanca silver mine financial document,

One list of costs related to the mine. In Spanish.