Separation and extraction of bridge dynamic strain data (in Chinese)

Through comparing the measured data of dynamic strains due to loading and temperature by the strain gauge and temperature sensor at the same location, the information in the strain data was divided into three parts in the frequency domain by using the defined index named PSD (power spectra density)- ratio. The three parts are dominated respectively by temperature varying, stresses and noises and can be distinguished from the determined values of the separatirix frequencies. Then a simple algorithm was developed to separate the three types of information, and to extract the strain caused mainly by structural stresses. As an application of the proposed method, the influence of strain deformation and noises. As an application of the proposed method, the influence of strain deformation and noises on the fatigue assessment was investigated based on the separated data. The results show that, the determined values of separatrix frequencies are valuable for the monitoring data from other bridges. The algorithm is a multi resolution and hierarchical method, which has been validated as a simple and effective method for data analyses, and is suitable for the compression and pre-processing of the great amount monitoring data and easy to be integrated in the SHM's (structural health monitoring)software system. The strain due to temperature varying attributes only a little to the errors of fatigue assessment. However, the noises or random disturbance existed in the monitoring data have much responsibility for the errors, the main reason is that the random disturbance shifts the real strain/stress amplitude picked up by real structural stress or strain

Reply to Kok and Dwyer

Letter (Correspondence)postprin

Spin-transfer switching and low-field precession in exchange-biased spin valve nano-pillars

Using a three-dimensional focused-ion beam lithography process we have fabricated nanopillar devices which show spin transfer torque switching at zero external magnetic fields. Under a small in-plane external bias field, a field-dependent peak in the differential resistance versus current is observed similar to that reported in asymmetrical nanopillar devices. This is interpreted as evidence for the low-field excitation of spin waves which in our case is attributed to a spin-scattering asymmetry enhanced by the IrMn exchange bias layer coupled to a relatively thin CoFe fixed layer.Comment: 11 pages, 4 figures. To appear in APL, April 200

Transmission of hand, foot and mouth disease and its potential driving factors in Hong Kong

published_or_final_versio

Multi-agent coalition formation in power transmission planning

Deregulation and restructuring have become unavoidable trends to the power industry recently in order to increase its efficiency, to reduce operation costs, or to provide customers better services. The once centralized system planning and management must be remodeled to reflect the changes in the market environment. We have proposed and developed a multi-agent based system to assist players, such as, owners of power generation stations, owners of transmission lines, and groups of consumers, in the same market to select partners to form coalitions. The system provides users with a cooperation plan and its associated cost allocation plan for the users to support their decision making process. Bilateral Shapley Value (BSV) was selected as the theoretical foundation to develop the system. The multi-agent system was developed by the combination of IDEAS and Tcl/Tk.published_or_final_versio

Direct Multifield Volume Ray Casting of Fiber Surfaces

Multifield data are common in visualization. However, reducing these data to comprehensible geometry is a challenging problem. Fiber surfaces, an analogy of isosurfaces to bivariate volume data, are a promising new mechanism for understanding multifield volumes. In this work, we explore direct ray casting of fiber surfaces from volume data without any explicit geometry extraction. We sample directly along rays in domain space, and perform geometric tests in range space where fibers are defined, using a signed distance field derived from the control polygons. Our method requires little preprocess, and enables real-time exploration of data, dynamic modification and pixel-exact rendering of fiber surfaces, and support for higher-order interpolation in domain space. We demonstrate this approach on several bivariate datasets, including analysis of multi-field combustion data

Association of lower total bilirubin level with statin usage: the United States National Health and Nutrition Examination Survey 1999–2008

OBJECTIVE: A low circulating level of bilirubin is associated with increased cardiovascular risk. As statins can stimulate heme oxygenase-1 (HO-1), which increases bilirubin production, we investigated whether statins in routine use increase total bilirubin levels in subjects at high cardiovascular risk. METHODS: Data from 3290 subjects with self-reported history of hypercholesterolemia, diabetes, or cardiovascular diseases in the United States National Health and Nutrition Examination Survey (NHANES) 1999-2008 were analyzed. RESULTS: Subjects taking statins (n = 1156) had lower total bilirubin levels than those not taking any lipid-lowering medication (n = 2134) after adjusting for age, sex, race/ethnicity, and survey period (adjusted mean = 0.699 vs 0.729 mg/dl respectively, P=0.001). The association remained significant after adjusting for more covariates (P = 0.002), but was attenuated after further adjusting for glycosylated hemoglobin, insulin resistance index, and low-density lipoprotein (LDL) cholesterol (P = 0.043). The use of lovastatin, rosuvastatin, and cerivastatin was associated with lower total bilirubin levels in the full adjustment model (P < 0.05). CONCLUSION: The use of statins was associated unexpectedly with lower total bilirubin levels. This could be explained at least partly by the effect of statins on glycemia and LDL cholesterol. Our results do not suggest that the anti-oxidant and anti-inflammatory effects of statins are due to HO-1 induction and increased serum bilirubin levels.postprin

Offline EEG-based driver drowsiness estimation using enhanced batch-mode active learning (EBMAL) for regression

© 2016 IEEE. There are many important regression problems in real-world brain-computer interface (BCI) applications, e.g., driver drowsiness estimation from EEG signals. This paper considers offline analysis: given a pool of unlabeled EEG epochs recorded during driving, how do we optimally select a small number of them to label so that an accurate regression model can be built from them to label the rest? Active learning is a promising solution to this problem, but interestingly, to our best knowledge, it has not been used for regression problems in BCI so far. This paper proposes a novel enhanced batch-mode active learning (EBMAL) approach for regression, which improves upon a baseline active learning algorithm by increasing the reliability, representativeness and diversity of the selected samples to achieve better regression performance. We validate its effectiveness using driver drowsiness estimation from EEG signals. However, EBMAL is a general approach that can also be applied to many other offline regression problems beyond BCI

Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)

© 1993-2012 IEEE. One big challenge that hinders the transition of brain-computer interfaces (BCIs) from laboratory settings to real-life applications is the availability of high-performance and robust learning algorithms that can effectively handle individual differences, i.e., algorithms that can be applied to a new subject with zero or very little subject-specific calibration data. Transfer learning and domain adaptation have been extensively used for this purpose. However, most previous works focused on classification problems. This paper considers an important regression problem in BCI, namely, online driver drowsiness estimation from EEG signals. By integrating fuzzy sets with domain adaptation, we propose a novel online weighted adaptation regularization for regression (OwARR) algorithm to reduce the amount of subject-specific calibration data, and also a source domain selection (SDS) approach to save about half of the computational cost of OwARR. Using a simulated driving dataset with 15 subjects, we show that OwARR and OwARR-SDS can achieve significantly smaller estimation errors than several other approaches. We also provide comprehensive analyses on the robustness of OwARR and OwARR-SDS

Age-specific seriousness of avian influenza A(H7N9) in the second-wave epidemic in China

Poster Presentations 2 - Diseases at the Interface of Humans, Wildlife and Other Animals: no. 23.049PURPOSE: In spring 2013, a novel avian influenza A(H7N9) emerged in China causing more than 130 human infections mostly in the eastern provinces. The hospital fatality risk of A(H7N9) were about 35% and caused severe illness especially in older patients. In winter 2013-14, a second wave of A(H7N9) began with higher burden in the southern provinces in China. We estimated the relative risk of serious illness of patients aged 65 or above in the second wave of A(H7N9) epidemic, accounting for potential age-specific differences in poultry exposure …published_or_final_versio