Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

What Went Wrong With the Mate-Tricks After-School Program, Which Increased Antisocial Behavior and Child/Parent Conflict?

This paper draws from an independent RCT evaluation on a behavior based afterschool intervention for called Mate-Tricks for 9-10 year old children and their families (N=592). This paper explores practical and theoretical issues that may have contributed to a range of iatrogenic effects found by the evaluation. To do this the paper focuses on key practical implementation factors such as: program exposure; engagement; and program quality. The paper also relates these results to popular theories of social development, including social interdependence theory. Finally, the paper discusses what the results suggest about the impact of cooperative/competitive goal structures in child and parent interventions of this type.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.

International order flows: Explaining equity and exchange rate returns

Macroeconomic models of equity and exchange rate returns perform poorly at high frequencies. The proportion of daily returns that these models explain is essentially zero. Instead of relying on macroeconomic determinants, we model equity price and exchange rate behavior based on a concept from microstructure – order flow. The international order flows are derived from belief changes of different investor groups in a two-country setting. We obtain a structural relationship between equity returns, exchange rate returns and their relationship to home and foreign equity market order flow. To test the model we construct daily aggregate order flow data from 800 million equity trades in the U.S. and France from 1999 to 2003. Almost 60% of the daily returns in the S&P100 index are explained jointly by exchange rate returns and aggregate order flows in both markets. As predicted by the model, daily exchange rate returns and order flow into the French market have significant incremental explanatory power for the daily S&P returns. The model implications are also validated for intraday returns.

Intrusion Detection System for Network Security in Synchrophasor Systems

Synchrophasor systems will play a crucial role in next generation Smart Grid monitoring, protection and control. However these systems also introduce a multitude of potential vulnerabilities from malicious and inadvertent attacks, which may render erroneous operation or severe damage. This paper proposes a Synchrophasor Specific Intrusion Detection System (SSIDS) for malicious cyber attack and unintended misuse. The SSIDS comprises a heterogeneous whitelist and behavior-based approach to detect known attack types and unknown and so-called ‘zero-day’ vulnerabilities and attacks. The paper describes reconnaissance, Man-in-the-Middle (MITM) and Denial-of-Service (DoS) attack types executed against a practical synchrophasor system which are used to validate the real-time effectiveness of the proposed SSIDS cyber detection method.

Multi-Attribute SCADA-Specific Intrusion Detection System for Power Networks

The increased interconnectivity and complexity of supervisory control and data acquisition (SCADA) systems in power system networks has exposed the systems to a multitude of potential vulnerabilities. In this paper, we present a novel approach for a next-generation SCADA-specific intrusion detection system (IDS). The proposed system analyzes multiple attributes in order to provide a comprehensive solution that is able to mitigate varied cyber-attack threats. The multiattribute IDS comprises a heterogeneous white list and behavior-based concept in order to make SCADA cybersystems more secure. This paper also proposes a multilayer cyber-security framework based on IDS for protecting SCADA cybersecurity in smart grids without compromising the availability of normal data. In addition, this paper presents a SCADA-specific cybersecurity testbed to investigate simulated attacks, which has been used in this paper to validate the proposed approach.

Synchronous Islanding Control in the Presence of Hydro-electric Generation

This paper introduces a novel load sharing algorithm to enable island synchronization. The system model used for development is based on an actual system for which historical measurement and fault data is available and is used to refine and test the algorithms performance and validity. The electrical system modelled is selected due to its high-level of hydroelectric generation and its history of islanding events. The process of developing the load sharing algorithm includes a number of steps. Firstly, the development of a simulation model to represent the case study accurately - this is validated by way of matching system behavior based on data from historical island events. Next, a generic island simulation is used to develop the load sharing algorithm. The algorithm is then tested against the validated simulation model representing the case study area selected. Finally, a laboratory setup is described which is used as validation method for the novel load sharing algorithm.

Burnout and behavior-related health risk factors:results from the population-based Finnish Health 2000 study

To explore the relationship between burnout and behavior-related health risk factors.

Viscous behavior of imidazolium-based ionic liquids

The viscosity of four imidazolium-based ionic liquids is analyzed as a function of pressure and temperature. Experimental measurements were carried out using an electromagnetic moving piston viscometer in the 303-353 K and 0.1-70 MPa ranges on synthesized ultrapure samples, and compared with available literature data. Molecular dynamics simulations were used to analyze the fluids' dynamic properties from a nanoscopic viewpoint, with special attention paid to self-diffusion coefficients and dynamic viscosity. Simulated properties are in excellent agreement with experimental results in spite of the glasslike dynamics of some of the studied fluids. © 2013 American Chemical Society.

Effect of a Web-Based Behavior Change Program on Weight Loss and Cardiovascular Risk Factors in Overweight and Obese Adults at High Risk of Developing Cardiovascular Disease:Randomized Controlled Trial

BACKGROUND: Web-based programs are a potential medium for supporting weight loss because of their accessibility and wide reach. Research is warranted to determine the shorter- and longer-term effects of these programs in relation to weight loss and other health outcomes.

OBJECTIVE: The aim was to evaluate the effects of a Web-based component of a weight loss service (Imperative Health) in an overweight/obese population at risk of cardiovascular disease (CVD) using a randomized controlled design and a true control group.

METHODS: A total of 65 overweight/obese adults at high risk of CVD were randomly allocated to 1 of 2 groups. Group 1 (n=32) was provided with the Web-based program, which supported positive dietary and physical activity changes and assisted in managing weight. Group 2 continued with their usual self-care (n=33). Assessments were conducted face-to-face. The primary outcome was between-group change in weight at 3 months. Secondary outcomes included between-group change in anthropometric measurements, blood pressure, lipid measurements, physical activity, and energy intake at 3, 6, and 12 months. Interviews were conducted to explore participants' views of the Web-based program.

RESULTS: Retention rates for the intervention and control groups at 3 months were 78% (25/32) vs 97% (32/33), at 6 months were 66% (21/32) vs 94% (31/33), and at 12 months were 53% (17/32) vs 88% (29/33). Intention-to-treat analysis, using baseline observation carried forward imputation method, revealed that the intervention group lost more weight relative to the control group at 3 months (mean -3.41, 95% CI -4.70 to -2.13 kg vs mean -0.52, 95% CI -1.55 to 0.52 kg, P<.001), at 6 months (mean -3.47, 95% CI -4.95 to -1.98 kg vs mean -0.81, 95% CI -2.23 to 0.61 kg, P=.02), but not at 12 months (mean -2.38, 95% CI -3.48 to -0.97 kg vs mean -1.80, 95% CI -3.15 to -0.44 kg, P=.77). More intervention group participants lost ≥5% of their baseline body weight at 3 months (34%, 11/32 vs 3%, 1/33, P<.001) and 6 months (41%, 13/32 vs 18%, 6/33, P=.047), but not at 12 months (22%, 7/32 vs 21%, 7/33, P=.95) versus control group. The intervention group showed improvements in total cholesterol, triglycerides, and adopted more positive dietary and physical activity behaviors for up to 3 months verus control; however, these improvements were not sustained.

CONCLUSIONS: Although the intervention group had high attrition levels, this study provides evidence that this Web-based program can be used to initiate clinically relevant weight loss and lower CVD risk up to 3-6 months based on the proportion of intervention group participants losing ≥5% of their body weight versus control group. It also highlights a need for augmenting Web-based programs with further interventions, such as in-person support to enhance engagement and maintain these changes.

Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

Species boundaries and phylogenetic relationships within the green algal genus Codium (Bryopsidales) based on plastid DNA sequences

Despite the potential model role of the green algal genus Codium for studies of marine speciation and evolution, there have been difficulties with species delimitation and a molecular phylogenetic framework was lacking. In the present study, 74 evolutionarily significant units (ESUs) are delimited using 227 rbcL exon 1 sequences obtained from specimens collected throughout the genus' range. Several morpho-species were shown to be poorly defined, with some clearly in need of lumping and others containing pseudo-cryptic diversity. A phylogenetic hypothesis of 72 Codium ESUs is inferred from rbcL exon 1 and rps3-rp/16 sequence data using a conventional nucleotide substitution model (GTR + Gamma + I), a codon position model and a covariotide (covarion) model, and the fit of a multitude of substitution models and alignment partitioning strategies to the sequence data is reported. Molecular clock tree rooting was carried out because out-group rooting was probably affected by phylogenetic bias. Several aspects of the evolution of morphological features of Codium are discussed and the inferred phylogenetic hypothesis is used as a framework to study the biogeography of the genus, both at a global scale and within the Indian Ocean. (c) 2007 Elsevier Inc. All rights reserved.

Incorporation of multiwalled carbon nanotubes to acrylic based bone cements: Effects on mechanical and thermal properties

Polymethyl methacrylate (PMMA) bone cement–multiwalled carbon nanotube (MWCNT) nanocomposites with a weight loading of 0.1% were prepared using 3 different methods of MWCNT incorporation. The mechanical and thermal properties of the resultant nanocomposite cements were characterised in accordance with the international standard for acrylic resin cements. The mechanical properties of the resultant nanocomposite cements were influenced by the type of MWCNT and method of incorporation used. The exothermic polymerisation reaction for the PMMA bone cement was significantly reduced when thermally conductive functionalised MWCNTs were added. This reduction in exotherm translated in a decrease in thermal necrosis index value of the respective nanocomposite cements, which potentially could reduce the hyperthermia experienced in vivo. The morphology and degree of dispersion of the MWCNTs in the PMMA matrix at different scales were analysed using scanning electron microscopy. Improvements in mechanical properties were attributed to the MWCNTs arresting/retarding crack propagation through the cement by providing a bridging effect into the wake of the crack, normal to the direction of crack growth. MWCNT agglomerations were evident within the cement microstructure, the degree of these agglomerations was dependent on the method used to incorporate the MWCNTs into the cement.