ActiveSelfHAR: Incorporating Self Training into Active Learning to Improve Cross-Subject Human Activity Recognition

Deep learning-based human activity recognition (HAR) methods have shown great promise in the applications of smart healthcare systems and wireless body sensor network (BSN). Despite their demonstrated performance in laboratory settings, the real-world implementation of such methods is still hindered by the cross-subject issue when adapting to new users. To solve this issue, we propose ActiveSelfHAR, a framework that combines active learning's benefit of sparsely acquiring data with actual labels and self- training's benefit of effectively utilizing unlabeled data to enable the deep model to adapt to the target domain, i.e., the new users. In this framework, the model trained in the last iteration or the source domain is first utilized to generate pseudo labels of the target-domain samples and construct a self-training set based on the confidence score. Second, we propose to use the spatio-temporal relationships among the samples in the non-self-training set to augment the core set selected by active learning. Finally, we combine the self-training set and the augmented core set to fine-tune the model. We demonstrate our method by comparing it with state-of-the-art methods on two IMU-based datasets and an EMG-based dataset. Our method presents similar HAR accuracies with the upper bound, i.e. fully supervised fine-tuning with less than 1\% labeled data of the target dataset and significantly improves data efficiency and time cost. Our work highlights the potential of implementing user-independent HAR methods into smart healthcare systems and BSN

Attribute-based encryption for cloud computing access control: A survey

National Research Foundation (NRF) Singapore; AXA Research Fun

Investigation of the Cofiring Process of Raw or Torrefied Bamboo and Masson Pine by Using a Cone Calorimeter

Cofiring characteristics of raw or torrefied bamboo and masson pine blends with different blend ratios were investigated by cone calorimetry, and its ash performance from cofiring was also determined by a YX-HRD testing instrument, X-ray fluorescence, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Results showed that bamboo and masson pine had the different physicochemical properties. Torrefaction improved fuel performances, resulting in a more stable cofiring process. It also decreased the heat release rate, total heat release, and total suspended particulates of fuels, especially CO2 and CO release. Masson pine ash mainly included CaO, SiO2, Fe2O3, K2O, and Al2O3. Bamboo ash was mainly composed of K2O, SiO2, MgO, and SO3. There were different melting temperatures and trends between different samples. The synergistic reaction of ash components was found during the cofiring process. The surface morphology of blend ash changed with the variation of bamboo or masson pine content

A new dependable exchange protocol

Abstract As electronic transaction becomes common practice in real-world business, its dependability develops into a major concern, especially in critical transactions, e.g., electronic payment and electronic contract signing. Many recent fair-exchange protocols can recover the transaction from network failures; however, few can survive local system failures. In this paper, we propose a new Dependable Exchange Protocol. With proper convertible signature scheme and message logging method, the exchange protocol provides a recovery method for network and local system failures. To the best of our knowledge, this protocol is the first fault-tolerant exchange protocol in the context of offline TTP and asynchronous channels

Actuarial Model Assumptions for Australian Inflation, Equity Returns, and Interest Rates

Though actuaries have developed several types of stochastic investment models for inflation, stock market returns, and interest rates, there are two commonly used in practice: autoregressive time series models with normally distributed errors, and autoregressive conditional heteroscedasticity (ARCH) models. ARCH models are particularly suited when there is heteroscedasticity in inflation and interest rate series. In such cases nonnormal residuals are found in the empirical data. This paper examines whether Australian univariate inflation and interest rate data are consistent with autoregressive time series and ARCH model assumptions

Reduced SV2A and GABAA_A receptor levels in the brains of type 2 diabetic rats revealed by [18^{18}F]SDM-8 and [18^{18}F]flumazenil PET

PURPOSE: Type 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimer's disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2 A (SV2A), γ-aminobutyric acid type A (GABA$_A$) receptor, amyloid-β, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats. Methods: Positron emission tomography (PET) using [$^{18}$F]SDM-8 (SV2A), [$^{18}$F]flumazenil (GABA$_A$ receptor), [$^{18}$F]florbetapir (amyloid-β), [$^{18}$F]PM-PBB3 (tau), and [$^{18}$F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and SpragueDawley (SD) rats. Immunofluorescence staining, Thioflavin S staining, proteomic profiling and pathway analysis were performed on the brain tissues of ZDF and SD rats. Results: Reduced cortical [$^{18}$F]SDM-8 uptake and cortical and hippocampal [$^{18}$F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. The regional uptake of [$^{18}$F]florbetapir and [$^{18}$F]PM-PBB3 was comparable in the brains of 12-month-old ZDF and SD rats. Immunofluorescence staining revealed Thioflavin S-negative, phospho-tau-positive inclusions in the cortex and hypothalamus in the brains of ZDF rats and the absence of amyloid-beta deposits. The level of GABA$_A$ receptors was lower in the cortex of ZDF rats than SD rats. Proteomic analysis further demonstrated that, compared with SD rats, synaptic-related proteins and pathways were downregulated in the hippocampus of ZDF rats. Conclusion: These findings provide in vivo evidence for regional reductions in SV2A and GABA$_A$ receptor levels in the brains of aged T2DM ZDF rats