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PurposeThis paper seeks to report the results of a study, which investigated the use of the internet by political parties and individual candidates in Scotland as part of their campaign for election to the UK Parliament in 2010.Design/methodology/approachThree methodologies were used in gathering data: the content of the web sites of 18 parties and 12 candidates was analysed in order to identify the ways in which participation by the Scottish electorate was encouraged via the provision of information and of opportunities for interaction, debate and feedback; the extent to which parties and candidates adopted and used social media, such as Facebook and Twitter, during the campaign was investigated and measured; and using e‐mail, Facebook and Twitter, a series of enquiries based around topical campaign and policy issues was directed at parties and candidates to measure the speed and extent of response, as well as any efforts made towards the creation of an ongoing relationship with potential voters.FindingsParty and candidate web sites were being used extensively for information provision, income generation and the recruitment of members and volunteers. However, Scottish political actors were reluctant to encourage online contact and debate, and were unwilling to answer contentious policy questions online. Social media applications were adopted by a significant number of parties and candidates, but were used primarily for the one‐way flow of information to known associates and party activists.Originality/valueThis study forms part of an ongoing series of investigations by the authors, which has examined the use of the internet by political parties and candidates during parliamentary election campaigns in Scotland. These are the only such studies which have looked specifically at the Scottish political arena.

This paper proposes a method for remote sensing based land cover/land use classification of urban areas. The method consists of the following four main stages: feature extraction, feature coding, feature selection and classification. In the feature extraction stage, statistical, textural and Gabor features are computed within local image windows of different sizes and orientations to provide a wide variety of potential features for the classification. Then the features are encoded and normalized by means of the Self-Organizing Map algorithm. For feature selection a CART (Classification and Regression Trees) based algorithm was developed to select a subset of features for each class within the classification scheme at hand. The selected subset of features is not attached to any specific classifier. Any classifier capable of representing possible skewed and multi-modal feature distributions can be employed, such as multi-layer perceptron (MLP) or k-nearest neighbor (k-NN). The paper reports experiments in land cover/land use classification with the Landsat TM and ERS-1 SAR images gathered over the city of Lisbon to show the potentials of the proposed method.

The ConTraffic system aims to assist authorities detect illicit cargo transported in maritime containers. To this end the system collects information on the trips of containers and then it detects anomalous trips using a number of techniques. In this paper we provide an overview of ConTraffic and the various anomaly detection techniques used or under development., JRC.G.4-Maritime affairs

An artificial neural network based on the multilayer-perceptron model has been used to classify two-date multispectral SPOT High Resolution Visible (HRV) imagery on a test site in the Departement Ardeche, France. A large network consisting of 98 nodes was trained successfully to classify 20 land-cover classes. A ground dataset comprising 1881 pixels was used to verify the accuracy of the classifier. The average accuracy achieved over all classes in the verification dataset was 81 per cent, exceeding the performance of a maximum-likelihood classifier by 28 per cent.

The topographic maps of 50 patients suffering from migraine with or without aura were compared to the brain maps of 20 normal controls and 20 patients with tension-type headaches. Only the migraine group showed a significant decrement of alpha rhythm power, during rest with eyes closed, at the posterior areas of the brain, and a significant increment of alpha power at the same regions during IPS at 20 c/sec.

The article describes how to eliminate the false positives generated by the basic model of an fast automatic algorithm for fishing areas control and vessel detection.

Statistical, textural and Gabor features were extracted from integrated multitemporal multispectral TM data and ERS-1 SAR imagery for urban land use mapping. The computed features are first normalised using the SOM algorithm and then a decision tree algorithm is applied for feature selection. The classification procedure was carried out with a multilayer perceptron, trained with the resilient backpropagation algorithm. The authors' results demonstrate the potential of the proposed methodology.

This paper describes a verification on a specific satellite image classification task that MLP networks perform a useful encoding of feature vectors in their last hidden layer which can be used as an ideal input for an LVQ network. The potential use of hybrid MLP/LVQ networks to improve the performance in a real-world complex classification task is thus demonstrated.

The Kohonen Maps (KM) connectionist model is a noteworthy alternative to traditional techniques for unsupervised data analysis. Unfortunately, it suffers the flaw of providing solutions that are sensitive to the initial random weight settings. A methodology for picking a seemingly suitable prototype among many maps is proposed.

Multilayer feed-forward perceptron networks have been used to classify high resolution remotely-sensed satellite data for land cover mapping. Experiments on a test area in southern France using multitemporal multispectral images from the SPOT-1 satellite have demonstrated the potential of neural networks for discriminating large numbers of ground cover classes. An average classification accuracy of the order of 84% has been obtained for 20 classes.

Artificial neural network models constitute an emerging technology for information processing that can already be credited with some convincing achievements. With the pragmatic purpose to show how — and not why — neural nets work, an overview of the main static and dynamic features of the principal connectionist models is provided.

In a survey of 29 hydrocephalic children treated by ventriculoatrial shunt (Holter valve) with a follow-up of 4 years, EEG records before the operation and at least once a year thereafter, the authors can support the view that an epileptogenic focus has developed around the place of insertion of the ventricular catheter in 19 cases, leading to epileptic seizures in 17 up to now. Thus the incidence of convulsions in this particular group of patients is 0.59 (17/29), the limits of confidence 95% being 0.39–0.76. The irritative abnormalities occur usually during the second year after the operation and the delay for the onset of clinical seizures is variable. The age at operation seems to influence the occurrence of the epileptogenic scar. The type of hydrocephalus and especially the presence of an associated cerebral focal lesion can be of importance in the development of clinical seizures.

The physical conditions of a reference system (Steam Generator of a Pressurized Water Reactor) can be represented as states of a multivariate stochastic dynamic model. A set of statistical supports to ”assist“ the operator in the interaction with the system is proposed. Results show that the applied recursive techniques for the identification of linear parametric models are powerful in the capture of the system behaviour. State identificators may play an important role to ”confirm“ or to ”refuse” an operator diagnosis. Either the on line comparison between observed and preidentified states or the rupture analysis enable diagnoses to be inferred as support to decision.

Summary Twenty-six cases of “benign epilepsy of childhood” with Rolandic spikes, thoroughly studied clinically and electroencephalographically, were compared with 26 patients with petit mal or petit mal and grand mal seizures. Absences could be detected in a fair number of children with “benign epilepsy.” Rolandic spikes and MU rhythms were found almost exclusively in patients having convulsions, whether focal or generalized. Rolandic spikes associated with MU rhythms and bilaterally synchronous or asynchronous discharges of spikes or of spike-and-slow-waves seem, therefore, to be the features of an epilepsy whose clinical manifestations (absences or convulsions) may depend on the psycho-biophysiological background. REsume 26 cas d' “Epilepsie benigne de L'enfance avec pointes Rolandiques” ont eteetudies du point de vue clinique et electroencephalographique, ils sont comparees a 26 observations de patients presentant des crises petit mal, ou petit mal et grand mal associees. Les absences petit mal electrocliniques sont frequentes chez les sujets porteurs d'une epilepsie benigne de L'enfance. Les pointes Rolandiques et les rythmes MU sont exclusivement enregistres chez les patients presentant des crises convulsives focales ou et generalisees. L'association pointes Rolandiques, rythme MU, decharges bilaterales de pointes ou de pointes ondes, synchrones ou asynchrones, semble caracteristique des epilepsies benignes dont la forme convulsive ou nonconvulsive depend des conditions psycho-biophysiologiques actuelles. ZUSAMMEnfassung 26 vollstandig klinisch und elektroencephalographisch untersuchte Falle von kindlicher benigner Epilepsie mit Rolandischen spikes, wurden mit 26 Kindern mit Petit-Mai oder Petit-Mal und Grand-Mal verglichen. In einer betrachtlichen Anzahl von Kindern mit benigner Epilepsie konnten Absencen beobachtet werden. Rolandische spikes und MU-Rhythmen wurden fast ausschliesslich bei Patienten mit fokalen oder generalisierten Anfallen gefunden. Das gemeinsame Auftreten von Rolandischen spikes, MU-Rhythmen und bilateral synchronen oder asynchronen Entladungen von spikes oder spike-slow-waves scheinen somit Zeichen einer Epilepsie zu sein, deren klinische Manifestation (Absencen oder Krampfanfalle) vom psycho-biophysiologischem Hintergrund abhangen. RESUMEN Se han comparado 26 casos de “epilepsyia benigna del nino con puntas Rolandicas,” concienzudamente estudiados clinica y electroencefalograficamente con 26 enfermos que padecian episodios de petit-mal o ataques de gran mal asociados a petit-mal. Se recogieron ausencias en un considerable numero de ninos con “epilepsyia benigna.” Puntas Rolandicas y ritmos MU se encontraron exclusivamente con convulsiones, ya fueran focales o generalizadas. La asociacion de puntas Rolandicas, ritmos MU y descargas bilaterales sincronas o asincronas, de puntas o punta-onda lenta parece ser un hallazgo de las epilepsyias cuyas manifestaciones clinicas (ausencias o convulsiones) pueden depender de un fondo psico-biofisiologico.