Preventing pollution attacks in multi-source network coding

Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipients receive linear combinations of packets. Network coded systems are vulnerable to pollution attacks where a single malicious node floods the network with bad packets and prevents the receiver from decoding correctly. Cryptographic defenses to these problems are based on homomorphic signatures and MACs. These proposals, however, cannot handle mixing of packets from multiple sources, which is needed to achieve the full benefits of network coding. In this paper we address integrity of multi-source mixing. We propose a security model for this setting and provide a generic construction.

University of Glasgow (qirdcsuog) at TREC Crowdsourcing 2011 : TurkRank-network-based worker ranking in crowdsourcing

For TREC Crowdsourcing 2011 (Stage 2) we propose a networkbased approach for assigning an indicative measure of worker trustworthiness in crowdsourced labelling tasks. Workers, the gold standard and worker/gold standard agreements are modelled as a network. For the purpose of worker trustworthiness assignment, a variant of the PageRank algorithm, named TurkRank, is used to adaptively combine evidence that suggests worker trustworthiness, i.e., agreement with other trustworthy co-workers and agreement with the gold standard. A single parameter controls the importance of co-worker agreement versus gold standard agreement. The TurkRank score calculated for each worker is incorporated with a worker-weighted mean label aggregation.

Bayesian imputation of non-chosen attribute values in revealed preference surveys

Obtaining attribute values of non-chosen alternatives in a revealed preference context is challenging because non-chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non-chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non-chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non-chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non-chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones.

Mechanical influences on endothelial cell network formation in vitro

While both the restoration of the blood supply and an appropriate local mechanical environment are critical for uneventful bone healing, their influence on each other remains unclear. Human bone fracture haematomas (<72h post-trauma) were cultivated for 3 days in fibrin matrices, with or without cyclic compression. Conditioned medium from these cultures enhanced the formation of vessel-like networks by HMEC-1 cells, and mechanical loading further elevated it, without affecting the cells’ metabolic activity. While haematomas released the angiogenesis-regulators, VEGF and TGF-β1, their concentrations were not affected by mechanical loading. However, direct cyclic stretching of the HMEC-1 cells decreased network formation. The appearance of the networks and a trend towards elevated VEGF under strain suggested physical disruption rather than biochemical modulation as the responsible mechanism. Thus, early fracture haematomas and their mechanical loading increase the paracrine stimulation of endothelial organisation in vitro, but direct periodic strains may disrupt or impair vessel assembly in otherwise favourable conditions.

Introduction to the special issue on next generation network architectures, protocols, theory, systems and applications

This special issue of Networking Science focuses on Next Generation Network (NGN) that enables the deployment of access independent services over converged fixed and mobile networks. NGN is a packet-based network and uses the Internet protocol (IP) to transport the various types of traffic (voice, video, data and signalling). NGN facilitates easy adoption of distributed computing applications by providing high speed connectivity in a converged networked environment. It also makes end user devices and applications highly intelligent and efficient by empowering them with programmability and remote configuration options. However, there are a number of important challenges in provisioning next generation network technologies in a converged communication environment. Some preliminary challenges include those that relate to QoS, switching and routing, management and control, and security which must be addressed on an urgent or emergency basis. The consideration of architectural issues in the design and pro- vision of secure services for NGN deserves special attention and hence is the main theme of this special issue.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

Entrepreneurial network development as a sign of business emergence

This study aims to explain the entrepreneurial processes as developments of entrepreneurial networks. As a theoretical framework, this study adopts the theory of experimentally organized economy and competence blocs. As suggested by this theory, entrepreneurs select profitable innovations and commercialise them. Through logistic regressions on the subjective and objective dependent variables, we find that nascent firms’ various activities to network customers, innovators, investors, and employees are positively associated with the business emergence. This study identifies the roles of entrepreneurs and the other actors in the entrepreneurial processes.

Calibration functions for estimating soil moisture from GPR dielectric constant measurements

Ground-penetrating radar (GPR) is widely used for assessment of soil moisture variability in field soils. Because GPR does not measure soil water content directly, it is common practice to use calibration functions that describe its relationship with the soil dielectric properties and textural parameters. However, the large variety of models complicates the selection of the appropriate function. In this article an overview is presented of the different functions available, including volumetric models, empirical functions, effective medium theories, and frequency-specific functions. Using detailed information presented in summary tables, the choice for which calibration function to use can be guided by the soil variables available to the user, the frequency of the GPR equipment, and the desired level of detail of the output. This article can thus serve as a guide for GPR practitioners to obtain soil moisture values and to estimate soil dielectric properties.

Macroscopic fundamental diagram for Brisbane, Australia: empirical findings on network partitioning and incident detection

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow, and the existence with dynamic features was confirmed in congested urban network in downtown Yokohama with real data set. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. However, limited works have been reported on real world example from signalised arterial network. This paper fuses data from multiple sources (Bluetooth, Loops and Signals) and presents a framework for the development of the MFD for Brisbane, Australia. Existence of the MFD in Brisbane arterial network is confirmed. Different MFDs (from whole network and several sub regions) are evaluated to discover the spatial partitioning for network performance representation. The findings confirmed the usefulness of appropriate network partitioning for traffic monitoring and incident detections. The discussion addressed future research directions.

A new distributed control strategy to coordinate multiple dstatcoms in LV network

Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.

Calibration and validation of wearable monitors

Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.

Calibration of the biotrainer pro activity monitor in children

The unique physical and movement characteristics of children necessitate the development of accelerometer equations and cut points that are population specific. The purpose of this study is to develop an ecologically valid cut point for the Biotrainer Pro monitor that reflects a threshold for moderate-intensity physical activity in elementary school children. A sample of 30 children (ages 8-12) wore a Biotrainer monitor while completing a series of 7 movement tasks (calibration phase) and while participating in an organized group activity (cross-validation phase). Videotapes from each session were processed using a computerized direct-observation technique to provide a criterion measure of physical activity. Analyses involved the use of mixed-model regression and receiver operator characteristic (ROC) curves. The results indicated that a cut point of 4 counts/min provides the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of activity as inactivity). Results with the cross-validation data demonstrated that this value yielded the best overall kappa (.58) and a high classification agreement (84%) for activity determination. The specificity of 93% demonstrates that the proposed cut point can accurately detect activity; however, the lower sensitivity value of 61% suggests that some minutes of activity might be incorrectly classified as inactivity. The cut point of 4 counts/min provides an ecologically valid cut point to capture physical activity in children using the Biotrainer Pro activity monitor.

Calibration and evaluation of an objective measure of physical activity in pre-school children

Background The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings. Methods While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reli-ability = 0.91 to 0.98). Results Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001). Conclusions The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.