This paper introduces an adaptive, energy-aware and distributed fault-tolerant topologycontrol algorithm, namely the Adaptive Disjoint Path Vector (ADPV) algorithm, for heterogeneous wireless sensor networks. In this heterogeneous model, we have resource-rich supernodes as well as ordinary sensor nodes that are supposed to be connected to the supernodes. Unlike the static alternative Disjoint P...

We develop a method that completely characterizes the global dynamics of models with multiple subpopulations are weakly interconnected. The is applied on two classes subpopulations: an epidemic model involves host species and vector patchy vector-borne model. consists main steps: reducing system using tools large scale systems studying auxiliary related original system. developed determines und...

Future wireless applications will take advantage of rapidly deployable, self-configuring multihop ad hoc networks. Because of the difficulty of obtaining IEEE 802.11 feedback about link connectivity in real networks, many multihop ad hoc networks utilize hello messages to determine local connectivity. This paper uses an implementation of the Ad hoc On-demand Distance Vector (AODV) routing proto...

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Deter...

Idiopathic normal pressure hydrocephalus (iNPH) is characterized by a clinical triad (gait disturbance, dementia, and urinary incontinence), and by radiological findings of enlarged ventricles reflecting disturbance of central spinal fluid circulation. A diagnosis of iNPH is sometimes challenging, and the pathophysiological mechanisms underlying the clinical symptoms of iNPH remain largely unkn...

Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tracts in the CNS, specifically in the brain. The automatic fiber tract mapping p...

The contribution of this paper, is the integration of network mobility (NEMO) and ad hoc networking (MANET) approaches in realized heterogeneous environment. The experimented prototype system applies existing Mobility support for IPv6 (MIPv6), NEMO, Ad hoc On-demand Distance Vector (AODV) routing protocol, and IEEE 802.11b Wireless LAN (WLAN) technologies to enable end-toend connectivity of a m...

Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine lear...

SUMMARY Predicting disulfide connectivity precisely helps towards the solution of protein structure prediction. In this study, a descriptor derived from the sequential distance between oxidized cysteines (denoted as DOC) is proposed. An approach using support vector machine (SVM) method based on weighted graph matching was further developed to predict the disulfide connectivity pattern in prote...

Dublin City University (DCU) took part in the Web Track (small task) in TREC-9. Our experiments were based on evaluating a number of connectivity analysis algorithms that we hoped would produce a marked improvement over a baseline Vector Space model system. Our connectivity experiments are all based on non-iterative post-query algorithms, which rerank a set of documents returned from content-on...