Variability of Millennial-Scale Trends in the Geomagnetic Axial Dipole

The historical trend in the axial dipole is sufficient to reverse the field in less than 2 kyr. Assessing the prospect of an imminent polarity reversal depends on the probability of sustaining the historical trend for long enough to produce a reversal. We use a stochastic model to predict the variability of trends for arbitrary time windows. Our predictions agree well with the trends computed from paleomagnetic models. Applying these predictions to the historical record shows that the current trend is likely due to natural variability. Furthermore, an extrapolation of the current trend for the next 1 to 2 kyr is highly unlikely. Instead, we compute the trend and time window needed to reverse the field with a specified probability. We find that the dipole could reverse in the next 20 kyr with a probability of 2%

Design and Development of an Airblast Atomiser for the KAVERI engine and the sectoral combustor tests

This report deals with the design and development of an airblast atomiser for application in the KAVERI engine. Five atomisers of the chosen design were fabricated and tested at ambient conditions to determine the fuel spray SMD, patternation, cone angle and atomiser flow number. The atomiser performance parameters specified were achieved and hot tests carried out in the 90° combustor sector. The combustor pressure loss, exit temperature distribution, ignition and stability limits were evaluate

The Organic Research Centre; Elm Farm Bulletin 84 July 2006

Regular bulletin with technical updates of the Organic Advisory Service Issue contains: Battling on for Avian Flu preventive vaccination; Organic Colombian Blacktail eggs; UK Co-existence - GMOand non-GMO crops; Aspects of Poultry Behaviour; CAP in the service of biodiversity; Seeing the Wood, the Trees and the Catch 22; Beware of organic market "statistics"; A central role in energy review

Research Paper on Basic of Artificial Neural Network

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, s uch as pattern recognition o r data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well. This paper gives overview of Artificial Ne ural Network, working & training of ANN. It also explain the application and advantages of ANN

Elm Farm Organic Research Centre Bulletin 83 April 2006

Regular bulleting with technical updates from Organic Advisory Service Issue contains: Testing for Tolerance - a pragmatic view GM Debate Vaccination nation - to jab or not to jab Future shape of OCIS Evolutionary wheat makes the grade? NIAB tracks health of organic cereal seed Stopping erosion of soil quality - the organic way Care needed to halt butterfly collapse Aspects of poultry behaviour: How free range is free range? On choosing an organic wheat A local education challenge New Wakelyns Science Building Organic vegetable market growt

Multi-competence and first language attrition

Introduction The multi-competence approach views bilingual development as a wholistic process that impacts not only on the linguistic system which is being acquired but on other languages that are already established in the mind/brain (Cook 2012). This perspective implies that the process commonly referred to as first language attrition - the changes to linguistic skills or language proficiency under conditions of reduced use - should be seen as an essential component of this wider picture. The assumption that bilingual development ‘involves the whole mind of the speaker, not simply their first language (L1) or their second’ (Cook 2012, p. 3768) puts developments and changes which occur in the first language while another is being learned or used on an equal footing with the development of the language that is being acquired. This status of processes of change in the first language, however, is not reflected in present-day linguistic research, with investigations of and insights into L1 attrition still lagging far behind the multitude of studies of second language (L2) development. The present contribution will give an overview of research in the field of first language attrition in a migration setting, and try to integrate those findings into the overall multi-competence framework. We would like to point out that, despite the fact that the term attrition is often perceived to imply negative connotations or collocations (cf. war of attrition), we do not use it here with any evaluative implication. On the contrary, in the same way that multi-competence approaches aim to consider L2 users in their own right and deny a special status to the native speaker on the assumption that ‘it is the users’ own language that matters’ (Cook 2012, p. 1), the variety used by the attriter is not to be seen as inferior, reduced or deteriorated: it is simply a system which coexists in the mind/brain, and thus within a larger ‘language supersystem’ with another (possibly dominant) language. We thus feel that, while the original label attrition may have been somewhat unfortunately and inappropriately chosen, it has become such an established term in the intervening years (with more than 5,000 hits on Google Scholar) that it would be counterproductive to change the nomenclature at this point

An Efficient Polynomial-based Filtering Against False Data Injection Attack in CPNS

Cyber Physical Network System (CPNS) is gaining lot of attention in many applications like, transportation networks, vehicular networks, life-critical applications and many more. Hence, the system needs to be protected from various kinds of attacks that degrade the system’s performance. There are many different types of attacks that are possible on cyber physical systems, among them false data injection attack is a serious threat to the system’s security. In this type of attack, the adversary compromises sensor nodes, inject false data and send them to the controller through compromised nodes. This makes the controller to estimate wrong system states which leads to various serious issues. Therefore, the false data must be filtered out before it reaches the sink. If all the false data flow towards the controller then it will be bottle neck to filter all the false data and this could paralyze the network. To resolve this issue many filtering schemes have been developed in the past, all use Message Authentication Codes (MACs) for report endorsement and en-route filtering. But they are not suitable for CPNS because of static routes and lack resilience to the number of compromised nodes. Hence, an enhanced scheme has been proposed which uses polynomials instead of MAC for report endorsement and also uses bloom filtering along with en-route filtering. Hence, this achieves high resilience to the number of compromised nodes and achieves high filtering efficiency