A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification

$k$ Nearest Neighbors ($k$NN) is one of the most widely used supervised learning algorithms to classify Gaussian distributed data, but it does not achieve good results when it is applied to nonlinear manifold distributed data, especially when a very limited amount of labeled samples are available. In this paper, we propose a new graph-based $k$NN algorithm which can effectively handle both Gaussian distributed data and nonlinear manifold distributed data. To achieve this goal, we first propose a constrained Tired Random Walk (TRW) by constructing an $R$-level nearest-neighbor strengthened tree over the graph, and then compute a TRW matrix for similarity measurement purposes. After this, the nearest neighbors are identified according to the TRW matrix and the class label of a query point is determined by the sum of all the TRW weights of its nearest neighbors. To deal with online situations, we also propose a new algorithm to handle sequential samples based a local neighborhood reconstruction. Comparison experiments are conducted on both synthetic data sets and real-world data sets to demonstrate the validity of the proposed new $k$NN algorithm and its improvements to other version of $k$NN algorithms. Given the widespread appearance of manifold structures in real-world problems and the popularity of the traditional $k$NN algorithm, the proposed manifold version $k$NN shows promising potential for classifying manifold-distributed data.Comment: 32 pages, 12 figures, 7 table

Mapping temporal variables into the NeuCube for improved pattern recognition, predictive modelling, and understanding of stream data.

This paper proposes a new method for an optimized mapping of temporal variables, describing a temporal stream data, into the recently proposed NeuCube spiking neural network architecture. This optimized mapping extends the use of the NeuCube, which was initially designed for spatiotemporal brain data, to work on arbitrary stream data and to achieve a better accuracy of temporal pattern recognition, a better and earlier event prediction and a better understanding of complex temporal stream data through visualization of the NeuCube connectivity. The effect of the new mapping is demonstrated on three bench mark problems. The first one is early prediction of patient sleep stage event from temporal physiological data. The second one is pattern recognition of dynamic temporal patterns of traffic in the Bay Area of California and the last one is the Challenge 2012 contest data set. In all cases the use of the proposed mapping leads to an improved accuracy of pattern recognition and event prediction and a better understanding of the data when compared to traditional machine learning techniques or spiking neural network reservoirs with arbitrary mapping of the variables.Comment: Accepted by IEEE TNNL

Insulin-like growth factor I promotes cord blood T cell maturation through monocytes and inhibits their apoptosis in part through interleukin-6

<p>Abstract</p> <p>Background</p> <p>The functional immaturity of T cells contributes to the susceptibility of neonates to infections and the less severe graft-versus-host disease associated with cord blood (CB) transplantation. We have previously reported that insulin-like growth factor – I (IGF-I) promotes the phytohaemagglutinin (PHA)-induced CB T cell maturation and inhibits their apoptosis in mononuclear cell (MC) culture. We hypothesized that the effects of IGF-I may be mediated by accessory cells and soluble factors.</p> <p>Results</p> <p>This study showed that the kinetics of PHA-induced maturation in purified CD3+ T cell was delayed compared to that in CBMC. The addition of autologous CD14+ monocytes increased T cell maturation and potentiated the effect of IGF-I. The addition of IL-6 had no effect on CB T cell maturation but it reduced PHA-induced apoptosis significantly. We further demonstrated that the neutralisation of IL-6 in CBMC culture partially abrogated the anti-apoptotic effect of IGF-1 on T cells. The anti-apoptotic effect of IL-6 was not mediated via the reduction of Fas expression in T cell subsets.</p> <p>Conclusion</p> <p>Our results suggested that the maturation effect of IGF-1 is partially mediated by monocytes and the anti-apoptotic effect in part via IL-6. Further investigation is needed to explore the therapeutic use of IGF-I in enhancing neonatal immunity.</p