On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems

The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier structure and the parameters of RBF kernels are determined using a particle swarm optimization algorithm based on the criterion of minimizing the leave-one-out misclassification rate. The experimental results on both simulated and real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

Influencing energy efficient occupant behavior through improved building and control design

There is growing pressure on the construction industry to deliver energy efficient, sustainable buildings but there is evidence to suggest that, in practice, designs regularly fail to achieve the anticipated levels of in-use energy consumption. One of the key factors behind this discrepancy is the behavior of the building occupants. This paper explores how insights from experimental psychology could potentially be used to reduce the gap between the predicted and actual energy performance of buildings. It demonstrates why traditional methods to engage with the occupants are not always successful and proposes a model for a more holistic approach to this issue. The paper concludes that achieving energy efficiency in buildings is not solely a technological issue and that the construction industry needs to adopt a more user-centred approach.

Codon and mRNA sequence optimization of microdystrophin transgenes improves expression and physiological outcome in dystrophic mdx mice following AAV2/8 gene transfer

Duchenne muscular dystrophy is a fatal muscle-wasting disorder. Lack of dystrophin compromises the integrity of the sarcolemma and results in myofibers that are highly prone to contraction-induced injury. Recombinant adenoassociated virus (rAAV)-mediated dystrophin gene transfer strategies to muscle for the treatment of Duchenne muscular dystrophy (DMD) have been limited by the small cloning capacity of rAAV vectors and high titers necessary to achieve efficient systemic gene transfer. In this study, we assess the impact of codon optimization on microdystrophin (ΔAB/R3-R18/ΔCT) expression and function in the mdx mouse and compare the function of two different configurations of codon-optimized microdystrophin genes (ΔAB/R3-R18/ΔCT and ΔR4-R23/ΔCT) under the control of a muscle-restrictive promoter (Spc5-12). Codon optimization of microdystrophin significantly increases levels of microdystrophin mRNA and protein after intramuscular and systemic administration of plasmid DNA or rAAV2/8. Physiological assessment demonstrates that codon optimization of ΔAB/R3-R18/ΔCT results in significant improvement in specific force, but does not improve resistance to eccentric contractions compared with noncodon-optimized ΔAB/ R3-R18/ΔCT. However, codon-optimized microdystrophin ΔR4-R23/ΔCT completely restored specific force generation and provided substantial protection from contraction-induced injury. These results demonstrate that codon optimization of microdystrophin under the control of a muscle-specific promoter can significantly improve expression levels such that reduced titers of rAAV vectors will be required for efficient systemic administration.

Evolution of immune systems: specificity and autoreactivity

Multicellularity evolved well before 600 million years ago, and all multicellular animals have evolved since then with the need to protect against pathogens. There is no reason to expect their immune systems to be any less sophisticated than ours. The vertebrate system, based on rearranging immunoglobulin-superfamily domains, appears to have evolved partly as a result of chance insertion of RAG genes by horizontal transfer. Remarkably sophisticated systems for expansion of immunological repertoire have evolved in parallel in many groups of organisms. Vaccination of invertebrates against commercially important pathogens has been empirically successful, and suggests that the definition of an adaptive and innate immune system should no longer depend on the presence of memory and specificity, since these terms are hard to define in themselves. The evolution of randomly-created immunological repertoire also carries with it the potential for generating autoreactive specificities and consequent autoimmune damage.While invertebrates may use systems analogous to ours to control autoreactive specificities, they may have evolved alternative mechanisms which operate either at the level of individuals-within-populations rather than cells-within-individuals, by linking self-reactive specificities to regulatory pathways and non-self-reactive to effector pathways.

Mobile-to-mobile MIMO transmit-receive diversity systems: analysis and performance in three-dimensional double-correlated channels

Mobile-to-mobile (M-to-M) communications are expected to play a crucial role in future wireless systems and networks. In this paper, we consider M-to-M multiple-input multiple-output (MIMO) maximal ratio combining system and assess its performance in spatially correlated channels. The analysis assumes double-correlated Rayleigh-and-Lognormal fading channels and is performed in terms of average symbol error probability, outage probability, and ergodic capacity. To obtain the receive and transmit spatial correlation functions needed for the performance analysis, we used a three-dimensional (3D) M-to-M MIMO channel model, which takes into account the effects of fast fading and shadowing. The expressions for the considered metrics are derived as a function of the average signal-to-noise ratio per receive antenna in closed-form and are further approximated using the recursive adaptive Simpson quadrature method. Numerical results are provided to show the effects of system parameters, such as distance between antenna elements, maximum elevation angle of scatterers, orientation angle of antenna array in the x–y plane, angle between the x–y plane and the antenna array orientation, and degree of scattering in the x–y plane, on the system performance. Copyright © 2011 John Wiley & Sons, Ltd.