Exploiting side information in locality preserving projection

Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the data's local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance.

Ridge regression for two dimensional locality preserving projection

Two Dimensional Locality Preserving Projection (2D-LPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, 2D-PCA and LPP. However, the computational cost of 2D-LPP is high. This paper proposes a novel algorithm called Ridge Regression for Two Dimensional Locality Preserving Projection (RR- 2DLPP), which is an extension of 2D-LPP with the use of ridge regression. RR-2DLPP is comparable to 2DLPP in performance whilst having a lower computational cost. The experimental results on three benchmark face data sets - the ORL, Yale and FERET databases - demonstrate the effectiveness and efficiency of RR-2DLPP compared with other face recognition algorithms such as PCA, LPP, SR, 2D-PCA and 2D-LPP.

IaaS clouds vs. clusters for HPC: a performance study

The increasing amount of data collected in the fields of physics and bio-informatics allows researchers to build realistic, and therefore accurate, models/simulations and gain a deeper understanding of complex systems. This analysis is often at the cost of greatly increased processing requirements. Cloud computing, which provides on demand resources, can offset increased analysis requirements. While beneficial to researchers, adaption of clouds has been slow due to network and performance uncertainties. We compare the performance of cloud computers to clusters to make clear the advantages and limitations of clouds. Focus has been put on understanding how virtualization and the underlying network effects performance of High Performance Computing (HPC) applications. Collected results indicate that performance comparable to high performance clusters is achievable on cloud computers depending on the type of application run.

EST-PAC HPC - a web portal for high-throughput EST annotation and protein sequence prediction

Expressed Sequence Tags (ESTs) are short DNA sequences generated by sequencing the transcribed cDNAs coming from a gene expression. They can provide significant functional, structural and evolutionary information and thus are a primary resource for gene discovery. EST annotation basically refers to the analysis of unknown ESTs that can be performed by database similarity search for possible identities and database search for functional prediction of translation products. Such kind of annotation typically consists of a series of repetitive tasks which should be automated, and be customizable and amenable to using distributed computing resources. Furthermore, processing of EST data should be done efficiently using a high performance computing platform. In this paper, we describe an EST annotator, EST-PACHPC, which has been developed for harnessing HPC resources potentially from Grid and Cloud systems for high throughput EST annotations. The performance analysis of EST-PACHPC has shown that it provides substantial performance gain in EST annotation.

Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Reasons for referral to bone densitometry in men and women aged 20-49 years : population-based data

Introduction Osteoporosis poses a significant public health problem for ageing Australians. However, approximately 25 % of Australian adults aged 20–49 years have osteopenia, a precursor condition to osteoporosis. Despite this, little is known about bone density testing in this age group.

Methods Reasons for referral to dual energy X-ray absorptiometry (DXA) were examined in 2,264 patients aged 20–49 years, referred in 2001–2010 to the Geelong Bone Densitometry Service, Geelong Hospital, Victoria. Referral reasons were determined from clinical indication codes derived from patient records. Age, sex and bone mineral density (BMD) T scores were ascertained for each patient.

Results The most common reason for referral for women reflected glucocorticoid use, and for men reflected fracture. Compared to women, men were more likely to have been referred because of minimal trauma fracture or low BMD (41.7 versus 27.1 %, p < 0.001). No further differences were identified between the sexes, with similar numbers of referral observed for secondary osteoporosis, and monitoring of drug therapy. At the spine, and for all indications, men had a significantly greater BMD deficit compared to women (all p ≤ 0.002). After age adjustment, men who were tested due to fracture or glucocorticoid reasons had significantly greater BMD at the total hip (p ≤ 0.03). No further associations were seen after age adjustment between referral reason and BMD.

Conclusions Our study presents the first data examining reasons for referral to DXA among Australians aged 20–49 years. Understanding health service utilisation regarding bone health in young adults is fundamental to understanding future risk, informing effective public health messages and raising awareness of osteoporosis.

Impact of climate change on thermal comfort and energy performance in offices - a parametric study

This paper investigates the impact of climate change on comfort and energy performance in offices in relation to the influence of building design and occupants. It focuses on a typical cellular office room in the context of Athens, Greece, as input for a parametric study using the building simulation software EnergyPlus. Three different building design variations are combined with two different occupant scenarios and 4 different weather data sets for IPCC climate change scenario A2.

For naturally ventilated buildings adaptive thermal comfort is evaluated according to ASHRAE Standard 55 and EN 15251. For mixed mode context evaluation is focused on greenhouse gas emissions and peak heating / cooling loads. Results indicate significant impact of the climate change on thermal comfort, and deviations between both comfort models. Comparing climate change, building design and occupant scenarios indicates that building design is the predominant influence on thermal comfort, whereas occupants are the predominant influence on greenhouse gas emissions.

Caveolin-1 orchestrates the balance between glucose and lipid-dependent energy metabolism : implications for liver regeneration

Caveolin-1 (CAV1) is a structural protein of caveolae involved in lipid homeostasis and endocytosis. Using newly generated pure Balb/C CAV1 null (Balb/CCAV1−/−) mice, CAV1−/− mice from Jackson Laboratories (JAXCAV1−/−), and CAV1−/− mice developed in the Kurzchalia Laboratory (KCAV1−/−), we show that under physiological conditions CAV1 expression in mouse tissues is necessary to guarantee an efficient progression of liver regeneration and mouse survival after partial hepatectomy. Absence of CAV1 in mouse tissues is compensated by the development of a carbohydrate-dependent anabolic adaptation. These results were supported by extracellular flux analysis of cellular glycolytic metabolism in CAV1-knockdown AML12 hepatocytes, suggesting cell autonomous effects of CAV1 loss in hepatic glycolysis. Unlike in KCAV1−/− livers, in JAXCAV1−/− livers CAV1 deficiency is compensated by activation of anabolic metabolism (pentose phosphate pathway and lipogenesis) allowing liver regeneration. Administration of 2-deoxy-glucose in JAXCAV1−/− mice indicated that liver regeneration in JAXCAV1−/− mice is strictly dependent on hepatic carbohydrate metabolism. Moreover, with the exception of regenerating JAXCAV1−/− livers, expression of CAV1 in mice is required for efficient hepatic lipid storage during fasting, liver regeneration, and diet-induced steatosis in the three CAV1−/− mouse strains. Furthermore, under these conditions CAV1 accumulates in the lipid droplet fraction in wildtype mouse hepatocytes. Conclusion: Our data demonstrate that lack of CAV1 alters hepatocyte energy metabolism homeostasis under physiological and pathological conditions.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Enhancing RFID data quality and reliability

This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime.

High muscle mitochondrial volume and aerobic capacity in a small marsupial (Sminthopsis crassicaudata) reveals flexible links between energy-use levels in mammals

We investigated the muscle structure-function relationships that underlie the aerobic capacity of an insectivorous, small (~15?g) marsupial, Sminthopsis crassicaudata (Family: Dasyuridae), to obtain further insight into energy use patterns in marsupials relative to those in placentals, their sister clade within the Theria (advanced mammals). Disparate hopping marsupials (Suborder Macropodiformes), a kangaroo (Macropus rufus) and a rat-kangaroo (Bettongia penicillata), show aerobic capabilities as high as those of 'athletic' placentals. Equivalent muscle mitochondrial volumes and cardiovascular features support these capabilities. We examined S. crassicaudata to determine whether highly developed aerobic capabilities occur elsewhere in marsupials, rather than being restricted to the more recently evolved Macropodiformes. This was the case. Treadmill-trained S. crassicaudata attained a maximal aerobic metabolic rate (VO2,max or MMR) of 272ml O2min-1kg -1 (N=8), similar to that reported for a small (?20g), 'athletic' placental, Apodemus sylvaticus, 264ml O2min -1kg-1. Hopping marsupials have comparable aerobic levels when body mass variation is considered. Sminthopsis crassicaudata has a basal metabolic rate (BMR) about 75% of placental values but it has a notably large factorial aerobic scope (fAS) of 13, elevated fAS also features in hopping marsupials. The VO2,max of S. crassicaudata was supported by an elevated total muscle mitochondrial volume, which was largely achieved through high muscle mitochondrial volume densities, Vv(mt,f), the mean value being 14.0±1.33%. These data were considered in relation to energy use levels in mammals, particularly field metabolic rate (FMR). BMR is consistently lower in marsupials, but this is balanced by a high fAS, such that marsupial MMR matches that of placentals. However, FMR shows different mass relationships in the two clades, with the FMR of small (<, 125 g) marsupials, such as S. crassicaudata, being higher than that in comparably sized placentals, with the reverse applying for larger marsupials. The flexibility of energy output in marsupials provides explanations for this pattern. Overall, our data refute widely held notions of mechanistically closely linked relationships between body mass, BMR, FMR and MMR in mammals generally.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

A new energy efficient cluster-head and backup selection scheme in WSN

Despite significant advancements in wireless sensor networks (WSNs), energy conservation remains one of the most important research challenges. Proper organization of nodes (clustering) is one of the major techniques to expand the lifespan of the whole network through aggregating data at the cluster head. The cluster head is the backbone of the entire cluster. That means if a cluster head fails to accomplish its function, the received and collected data by cluster head can be lost. Moreover, the energy consumption following direct communications from sources to base stations will be increased. In this paper, we propose a type-2 fuzzy based self-configurable cluster head selection (SCCH) approach to not only consider the selection criterion of the cluster head but also present the cluster backup approach. Thus, in case of cluster failure, the system still works in an efficient way. The novelty of this protocol is the ability of handling communication uncertainty, which is an inherent operational aspect of sensor networks. The experiment results indicate SCCH performs better than other recently developed methods.