Multiple map hypotheses for planning and navigating in non-stationary environments

This paper presents a method to enable a mobile robot working in non-stationary environments to plan its path and localize within multiple map hypotheses simultaneously. The maps are generated using a long-term and short-term memory mechanism that ensures only persistent configurations in the environment are selected to create the maps. In order to evaluate the proposed method, experimentation is conducted in an office environment. Compared to navigation systems that use only one map, our system produces superior path planning and navigation in a non-stationary environment where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Maternal feeding self-efficacy and fruit and vegetable intakes in infants. Results from the SAIDI study

Adequate consumption of fruits and vegetables (FV) is a characteristic of a healthy diet but remains a challenge in nutrition interventions. This cross-sectional study explored the multi-directional relationships between maternal feeding self-efficacy, parenting confidence, child feeding behaviour, exposure to new food and FV intake in a cohort of 277 infants. Mothers with healthy infants weighing ≥2500 g and ≥37 weeks gestation were recruited post-natally from 11 South Australian hospitals. Socio-demographic datawere collected at recruitment. At 6 months postnatal, infantswereweighed and measured, andmothers completed a questionnaire exploring their perceptions of child feeding behaviour and child exposure to newfoods. The questionnaire also included the Short Temperament Scale for Infants, Kessler 10 to measure maternal psychological distress and 5 items measuring maternal feeding self-efficacy. The number of occasions and variety of FV (number of subgroups within food groups) consumed by infants were estimated from a 24-hour dietary recall and 2 days food record. Structural equation modellingwas performed using Mplus version 6.11. Median (IQR) variety scores were 2 (1–3) for fruit and 3 (2–5) for vegetable intake. The most popular FV consumed were apple (n = 108, 45.0%) and pumpkin (n = 143, 56.3%). None of the variables studied predicted the variety of child fruit intake. Parenting confidence, exposure to new foods and child feeding behaviourwere indirectly related to child vegetable intake through maternal feeding self-efficacy while total number of children negatively predicted child vegetable variety (p < 0.05). This highlights the need for addressing antecedents of maternal feeding self-efficacy and the family eating environment as key strategies towards development of healthy eating in children.

A Combined Renormalization Group-Multiple Scale Method for Singularly Perturbed Problems

This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

Analysis of albumin-associated peptides and proteins from ovarian cancer patients

Albumin binds low–molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low–molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n= 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. Methods Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. Results In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. Conclusion Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.

Multiple modular additions and crossword puzzle attack on NLSv2

NLS is a stream cipher which was submitted to the eSTREAM project. A linear distinguishing attack against NLS was presented by Cho and Pieprzyk, which was called Crossword Puzzle (CP) attack. NLSv2 is a tweak version of NLS which aims mainly at avoiding the CP attack. In this paper, a new distinguishing attack against NLSv2 is presented. The attack exploits high correlation amongst neighboring bits of the cipher. The paper first shows that the modular addition preserves pairwise correlations as demonstrated by existence of linear approximations with large biases. Next, it shows how to combine these results with the existence of high correlation between bits 29 and 30 of the S-box to obtain a distinguisher whose bias is around 2^−37. Consequently, we claim that NLSv2 is distinguishable from a random cipher after observing around 2^74 keystream words.

Towards a multiple-goal pursuit and multilevel view of continuing information technology usage : a process model integration and a research agenda

The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

Origins of Australian Football: Victoria's Early History. Volume 2 : A golden era begins : Football in 'Marvellous Melbourne', 1877 to 1885

This is the second volume of a five volume series that describes, assesses, and analyses football in Victoria during the nineteenth century. This volume looks at the cultural contexts of the sport in the late 1870s and early 1880s, describes the important matches played, and provides a full statistical account of this time period. This book is the first comprehensive discussion of the early period in Australian football's development.

Beliefs about infant regulation, early infant behaviors and maternal postnatal depressive symptoms

Background: Young infants may have irregular sleeping and feeding patterns. Such regulation difficulties are known correlates of maternal depressive symptoms. Parental beliefs regarding their role in regulating infant behaviours also may play a role. We investigated the association of depressive symptoms with infant feeding/sleeping behaviours, parent regulation beliefs, and the interaction of the two. Method: In 2006, 272 mothers of infants aged up to 24 weeks completed a questionnaire about infant behaviour and regulation beliefs. Participants were recruited from general medical practices and child health clinics in Brisbane, Australia. Depressive symptomology was measured using the Edinburgh Postnatal Depression Scale (EPDS). Other measures were adapted from the ALSPAC study. Results: Regression analyses were run controlling for partner support, other support, life events, and a range of demographic variables. Maternal depressive symptoms were associated with infant sleeping and feeding problems but not regulation beliefs. The most important infant predictor was sleep behaviours with feeding behaviours accounting for little additional variance. An interaction between regulation beliefs and sleep behaviours was found. Mothers with high regulation beliefs were more susceptible to postnatal depressive symptoms when infant sleep behaviours were problematic. Conclusion: Mothers of young infants who expect greater control are more susceptible to depressive symptoms when their infant presents challenging sleep behaviour.

Offspring of mothers fed a high fat diet display hepatic cell cycle inhibition and associated changes in gene expression and DNA methylation

The association between an adverse early life environment and increased susceptibility to later-life metabolic disorders such as obesity, type 2 diabetes and cardiovascular disease is described by the developmental origins of health and disease hypothesis. Employing a rat model of maternal high fat (MHF) nutrition, we recently reported that offspring born to MHF mothers are small at birth and develop a postnatal phenotype that closely resembles that of the human metabolic syndrome. Livers of offspring born to MHF mothers also display a fatty phenotype reflecting hepatic steatosis and characteristics of non-alcoholic fatty liver disease. In the present study we hypothesised that a MHF diet leads to altered regulation of liver development in offspring; a derangement that may be detectable during early postnatal life. Livers were collected at postnatal days 2 (P2) and 27 (P27) from male offspring of control and MHF mothers (n = 8 per group). Cell cycle dynamics, measured by flow cytometry, revealed significant G0/G1 arrest in the livers of P2 offspring born to MHF mothers, associated with an increased expression of the hepatic cell cycle inhibitor Cdkn1a. In P2 livers, Cdkn1a was hypomethylated at specific CpG dinucleotides and first exon in offspring of MHF mothers and was shown to correlate with a demonstrable increase in mRNA expression levels. These modifications at P2 preceded observable reductions in liver weight and liver:brain weight ratio at P27, but there were no persistent changes in cell cycle dynamics or DNA methylation in MHF offspring at this time. Since Cdkn1a up-regulation has been associated with hepatocyte growth in pathologic states, our data may be suggestive of early hepatic dysfunction in neonates born to high fat fed mothers. It is likely that these offspring are predisposed to long-term hepatic dysfunction.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.