Knowledge based cloud FE simulation of sheet metal forming processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions

Tracking advanced persistent threats in critical infrastructures through opinion dynamics

Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and cor- respondingly deploy accurate response procedures. Advanced Persistent Threat Detection Traceability Opinion Dynamics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

New insights provided by myofibril mechanics in inherited cardiomyopathies

Cardiomyopathies represent a heterogeneous group of cardiac disorders that perturb cardiac contraction and/or relaxation, and can result in arrhythmias, heart failure, and sudden cardiac death. Based on morphological and functional differences, cardiomyopathies have been classified into hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and restrictive cardiomyopathy (RCM). It has been well documented that mutations in genes encoding sarcomeric proteins are associated with the onset of inherited cardiomyopathies. However, correlating patient genotype to the clinical phenotype has been challenging because of the complex genetic backgrounds, environmental influences, and lifestyles of individuals. Thus, “scaling down” the focus to the basic contractile unit of heart muscle using isolated single myofibril function techniques is of great importance and may be used to understand the molecular basis of disease-causing sarcomeric mutations. Single myofibril bundles harvested from diseased human or experimental animal hearts, as well as cultured adult cardiomyocytes or human cardiomyocytes derived from induced pluripotent stem cells, can be used, thereby providing an ideal multi-level, cross-species platform to dissect sarcomeric function in cardiomyopathies. Here, we will review the myofibril function technique, and discuss alterations in myofibril mechanics, which are known to occur in sarcomeric genetic mutations linked to inherited HCM, DCM, and RCM, and describe the therapeutic potential for future target identification

Investigation of the AODV and the SDWCA QoS handling at different utilisation levels in adaptive clustering environments

A simulation study using NS2 simulator using two main routing protocols with specific design parameters has been carried out to investigate the QoS main parameters such as throughput, delay, Jitter, Control Overhead, Number of packets, number of packets dropped and the rating overheads. The traffic is made of CBR slow video traffic. From the result it is noted that the SDWCA routing protocol outperforms the AODV routing protocols in the throughput, the delay and the jitter issues at different loading levels

A comparison of low- versus standard-dose bridging alteplase in acute ischemic stroke mechanical thrombectomy using indirect methods

Background: Whether low-dose alteplase is similar to standard-dose bridging alteplase prior to endovascular mechanical thrombectomy in patients with acute ischemic stroke (AIS) remains uncertain. Aims: The aim of this study was to compare the efficacy and safety outcomes of low- versus standard-dose bridging alteplase therapy (BT) in patients with acute ischemic stroke (AIS) who are eligible for intravenous thrombolysis (IVT) within 4.5 h after onset. Methods: We conducted an indirect comparison of low- versus standard-dose bridging alteplase before mechanical thrombectomy in AIS of current available clinical randomized controlled trials (RCTs) that compared direct mechanical thrombectomy treatment (dMT) to BT. Primary efficacy outcomes were functional independence and excellent recovery defined as a dichotomized modified Rankin Scale (mRS) 0–2 and 0–1 at 90 days. Safety outcomes included symptomatic intracranial hemorrhage (sICH) and any intracranial hemorrhage (ICH). Results: We included six RCTs of 2334 AIS patients in this analysis, including one trial using low-dose bridging alteplase (n = 103) and five trials using standard-dose bridging alteplase (n = 1067) against a common comparator (dMT). Indirect comparisons of low- to standard-dose bridging alteplase yielded an odds ratio (OR) of 0.84 (95% CI 0.47–1.50) for 90-day mRS 0–2, 1.18 (95% CI 0.65–2.12) for 90-day mRS 0–1, 1.21 (95% CI 0.44–3.36) for mortality, and 1.11 (95% CI 0.39–3.14) for successful recanalization. There were no significant differences in the odds for sICH (OR 1.05, 95% CI 0.32–3.41) or any ICH (OR 1.71, 95% CI 0.94–3.10) between low- and standard-dose bridging alteplase. Conclusion: Indirect evidence shows that the effects of low- and standard-dose bridging alteplase are similar for key efficacy and safety outcomes. Due to the wide confidence intervals, larger randomized trials comparing low- and standard-dose alteplase bridging therapy are required

A novel test method for continuous nonlinear biaxial tensile deformation of sheet metals by bulging with stepped-dies

In this paper, a novel test method named bulging with stepped-dies is proposed to overcome the difficulty of traditional test methods in realizing continuous nonlinear loading paths from initial yield up to fracture on a sheet metal. To achieve this aim, the section shape of a stepped-die cavity is varied with increasing depth. During bulging with a stepped-die, the stress state at the pole of bulging area of the sheet changes continuously with the increase in bulging height, which results in a specific nonlinear loading path. A theoretical model is established to calculate the stress components at the pole based on the assumption that the bulged surface near the pole was approximated by a rotational ellipsoid. Bulging experiments with three different stepped-dies are performed by using ST16 steel sheet. Stress and strain paths up to fracture and equivalent stress-strain curves at the pole are analyzed and compared with the results of bulging with elliptical dies. It is shown that continuous nonlinear loading paths can be effectively realized through bulging with stepped-dies and the stress ratio at the pole changes from 0.5 up to 2.0 at most in one bulging experiment. The feasibility of the novel test method is validated successfully. And the experimental data obtained are useful to determine constitutive and forming limit models suitable for complex loading conditions

Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays

During sleep and awake rest, the hippocampus replays sequences of place cells that have been activated during prior experiences. These have been interpreted as a memory consolidation process, but recent results suggest a possible interpretation in terms of reinforcement learning. The Dyna reinforcement learning algorithms use off-line replays to improve learning. Under limited replay budget, a prioritized sweeping approach, which requires a model of the transitions to the predecessors, can be used to improve performance. We investigate whether such algorithms can explain the experimentally observed replays. We propose a neural network version of prioritized sweeping Q-learning, for which we developed a growing multiple expert algorithm, able to cope with multiple predecessors. The resulting architecture is able to improve the learning of simulated agents confronted to a navigation task. We predict that, in animals, learning the world model should occur during rest periods, and that the corresponding replays should be shuffled.Comment: Living Machines 2018 (Paris, France

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa