Construction of an index of information from clinical practice in Radiology and Imaging Diagnosis based on text mining and thesaurus

Objective To construct a Portuguese language index of information on the practice of diagnostic radiology in order to improve the standardization of the medical language and terminology. Materials and Methods A total of 61,461 definitive reports were collected from the database of the Radiology Information System at Hospital das Clínicas – Faculdade de Medicina de Ribeirão Preto (RIS/HCFMRP) as follows: 30,000 chest x-ray reports; 27,000 mammography reports; and 4,461 thyroid ultrasonography reports. The text mining technique was applied for the selection of terms, and the ANSI/NISO Z39.19-2005 standard was utilized to construct the index based on a thesaurus structure. The system was created in *html. Results The text mining resulted in a set of 358,236 (n = 100%) words. Out of this total, 76,347 (n = 21%) terms were selected to form the index. Such terms refer to anatomical pathology description, imaging techniques, equipment, type of study and some other composite terms. The index system was developed with 78,538 *html web pages. Conclusion The utilization of text mining on a radiological reports database has allowed the construction of a lexical system in Portuguese language consistent with the clinical practice in Radiology.

JXTA anonymity through a replicated message-based approach

JXTA is a mature set of open protocols, with morethan 10 years of history, that enable the creation and deployment of peer-to-peer (P2P) networks, allowing the execution of services in a distributed manner. Throughout its lifecycle, ithas slowly evolved in order to appeal a broad set of different applications. Part of this evolution includes providing basic security capabilities in its protocols in order to achieve some degree of message privacy and authentication. However, undersome contexts, more advanced security requirements should be met, such as anonymity. There are several methods to attain anonymity in generic P2P networks. In this paper, we proposehow to adapt a replicated message-based approach to JXTA, by taking advantage of its idiosyncracies and capabilities.

Split message-based anonymity for JXTA applications

JXTA is an open peer-to-peer (P2P) protocols specification that, in its about 10 years of history, has slowly evolved to appeal to a broad set of applications. As part of this process,some long awaited security improvements have been included in the latest versions. However, under some contexts, even more advanced security requirements should be met, such as anonymity. Several approaches exist to deploy anonymity in P2P networks, but no perfect solution exists. Even though path-based approaches are quite popular, it is considered that, in dynamicgroups, using a split message-based one is better. In this work, we propose an anonymity service for JXTA using such approach. The proposal takes advantage JXTA's core services, in a manner so that it can be easily integrated to existing end applications and services.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

A Forwarding Cooperation Protocol for Plain and Cluster-based Ad Hoc Networks

Peer-reviewed

Extension and evaluation of JXTA protocols for supporting reliable P2P distributed computing

Peer-reviewed

Efficient Peer Selection in P2P JXTA-Based Platforms

Peer-reviewed

Collaborative group membership and access control for JXTA

Peer-reviewed

Towards the Construction of a Multi-agent Approach for Discovering the Meaning of Natural Language Collaborative Conversations

Peer-reviewed

Individual differences in control of language interference in late bilinguals are mainly related to general executive abilities

Background: Recent research based on comparisons between bilinguals and monolinguals postulates that bilingualism enhances cognitive control functions, because the parallel activation of languages necessitates control of interference. In a novel approach we investigated two groups of bilinguals, distinguished by their susceptibility to cross-language interference, asking whether bilinguals with strong language control abilities ('non-switchers") have an advantage in executive functions (inhibition of irrelevant information, problem solving, planning efficiency, generative fluency and self-monitoring) compared to those bilinguals showing weaker language control abilities ('switchers"). Methods: 29 late bilinguals (21 women) were evaluated using various cognitive control neuropsychological tests [e.g., Tower of Hanoi, Ruff Figural Fluency Task, Divided Attention, Go/noGo] tapping executive functions as well as four subtests of the Wechsler Adult Intelligence Scale. The analysis involved t-tests (two independent samples). Non-switchers (n = 16) were distinguished from switchers (n = 13) by their performance observed in a bilingual picture-naming task. Results: The non-switcher group demonstrated a better performance on the Tower of Hanoi and Ruff Figural Fluency task, faster reaction time in a Go/noGo and Divided Attention task, and produced significantly fewer errors in the Tower of Hanoi, Go/noGo, and Divided Attention tasks when compared to the switchers. Non-switchers performed significantly better on two verbal subtests of the Wechsler Adult Intelligence Scale (Information and Similarity), but not on the Performance subtests (Picture Completion, Block Design). Conclusions: The present results suggest that bilinguals with stronger language control have indeed a cognitive advantage in the administered tests involving executive functions, in particular inhibition, self-monitoring, problem solving, and generative fluency, and in two of the intelligence tests. What remains unclear is the direction of the relationship between executive functions and language control abilities.

LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

Peer-reviewed

Secure logarithmic audio watermarking scheme based on the human auditory system

Peer-reviewed

UDDI palvelurekisterin merkitys Web palveluissa

Tietojärjestelmien integraatio on nykypäivänä tärkeä osa alue yritysten toiminnassa ja kilpailukyvyn ylläpitämisessä. Palvelukeskeinen arkkitehtuuri ja Web palvelut on uusi joustava tapa tehdä tietojärjestelmien välinen integraatio. Web palveluiden yksi ydinkomponentti on UDDI, Universal Description, Discovery and Integration. UDDI toimii palvelurekisterin tavoin. UDDI määrittää tavan julkaista, löytää ja ottaa käyttöön Web palveluja. Web palveluja voidaan hakea UDDI:sta erilaisin kriteerein, kuten esimerkiksi palvelun sijainnin, yrityksen nimen ja toimialan perusteella. UDDI on myös itsessään Web palvelu, joka perustuu XML kuvauskieleen ja SOAP protokollaan. Työssä paneudutaan tarkemmin UDDI:in. UDDI:ta käsitellään tarkemmin myös teknisesti. Oleellinen osa UDDI:ta on ollut julkaisijoiden ja käyttäjien mielestä tietoturvan puute, joka on rajoittanut huomattavasti UDDI:n käyttöä ja käyttöönottamista. Työssä tarkastellaankin tarkemmin juuri tietoturvaan liittyviä asioita ja ratkaisuja sekä myös UDDI:n merkitystä yrityksille.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Self-assessment of individual differences in language switching

Language switching is omnipresent in bilingual individuals. In fact, the ability to switch languages (code switching) is a very fast, efficient, and flexible process that seems to be a fundamental aspect of bilingual language processing. In this study, we aimed to characterize psychometrically self-perceived individual differences in language switching and to create a reliable measure of this behavioral pattern by introducing a bilingual switching questionnaire. As a working hypothesis based on the previous literature about code switching, we decomposed language switching into four constructs: (i) L1 switching tendencies (the tendency to switch to L1; L1-switch); (ii) L2 switching tendencies (L2-switch); (iii) contextual switch, which indexes the frequency of switches usually triggered by a particular situation, topic, or environment; and (iv) unintended switch, which measures the lack of intention and awareness of the language switches. A total of 582 SpanishCatalan bilingual university students were studied. Twelve items were selected (three for each construct). The correlation matrix was factor-analyzed using minimum rank factor analysis followed by oblique direct oblimin rotation. The overall proportion of common variance explained by the four extracted factors was 0.86. Finally, to assess the external validity of the individual differences scored with the new questionnaire, we evaluated the correlations between these measures and several psychometric (language proficiency) and behavioral measures related to cognitive and attentional control. The present study highlights the importance of evaluating individual differences in language switching using self-assessment instruments when studying the interface between cognitive control and bilingualism.