156,773 research outputs found
Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network
In recent years, wireless ad hoc sensor network becomes popular both in civil
and military jobs. However, security is one of the significant challenges for
sensor network because of their deployment in open and unprotected environment.
As cryptographic mechanism is not enough to protect sensor network from
external attacks, intrusion detection system needs to be introduced. Though
intrusion prevention mechanism is one of the major and efficient methods
against attacks, but there might be some attacks for which prevention method is
not known. Besides preventing the system from some known attacks, intrusion
detection system gather necessary information related to attack technique and
help in the development of intrusion prevention system. In addition to
reviewing the present attacks available in wireless sensor network this paper
examines the current efforts to intrusion detection system against wireless
sensor network. In this paper we propose a hierarchical architectural design
based intrusion detection system that fits the current demands and restrictions
of wireless ad hoc sensor network. In this proposed intrusion detection system
architecture we followed clustering mechanism to build a four level
hierarchical network which enhances network scalability to large geographical
area and use both anomaly and misuse detection techniques for intrusion
detection. We introduce policy based detection mechanism as well as intrusion
response together with GSM cell concept for intrusion detection architecture.Comment: 16 pages, International Journal of Network Security & Its
Applications (IJNSA), Vol.2, No.3, July 2010. arXiv admin note: text overlap
with arXiv:1111.1933 by other author
Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling
Shelf and coastal sea processes extend from the atmosphere through the water
column and into the sea bed. These processes are driven by physical, chemical,
and biological interactions at local scales, and they are influenced by
transport and cross strong spatial gradients. The linkages between domains and
many different processes are not adequately described in current model systems.
Their limited integration level in part reflects lacking modularity and
flexibility; this shortcoming hinders the exchange of data and model components
and has historically imposed supremacy of specific physical driver models. We
here present the Modular System for Shelves and Coasts (MOSSCO,
http://www.mossco.de), a novel domain and process coupling system
tailored---but not limited--- to the coupling challenges of and applications in
the coastal ocean. MOSSCO builds on the existing coupling technology Earth
System Modeling Framework and on the Framework for Aquatic Biogeochemical
Models, thereby creating a unique level of modularity in both domain and
process coupling; the new framework adds rich metadata, flexible scheduling,
configurations that allow several tens of models to be coupled, and tested
setups for coastal coupled applications. That way, MOSSCO addresses the
technology needs of a growing marine coastal Earth System community that
encompasses very different disciplines, numerical tools, and research
questions.Comment: 30 pages, 6 figures, submitted to Geoscientific Model Development
Discussion
Learning Behavioural Context
The original publication is available at www.springerlink.co
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SFF-Oriented Modeling and Process Planning of Functionally Graded Materials Using a Novel Equal Distance Offset Approach
This paper deals with the modeling and process planning of solid freeform fabrication
(SFF) of 3D functionally graded materials (FGMs). A novel approach of representation and
process planning of FGMs, termed as equal distance offset (EDO), is developed. In EDO, a
neutral arbitrary 3D CAD model is adaptively sliced into a series of 2D layers. Within each
layer, 2D material gradients are designed and represented via dividing the 2D shape into
several sub-regions enclosed by iso-composition contours. If needed, the material
composition gradient within each of sub-regions can be further determined by applying the
equal distance offset algorithm to each sub-region. Using this approach, an arbitrary-shaped
3D FGM object with linear or non-linear composition gradients can be represented and
fabricated via suitable SFF machines.Mechanical Engineerin
Medical imaging analysis with artificial neural networks
Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging
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