Towards a Robust WiFi-based Fall Detection with Adversarial Data Augmentation

Recent WiFi-based fall detection systems have drawn much attention due to their advantages over other sensory systems. Various implementations have achieved impressive progress in performance, thanks to machine learning and deep learning techniques. However, many of such high accuracy systems have low reliability as they fail to achieve robustness in unseen environments. To address that, this paper investigates a method of generalization through adversarial data augmentation. Our results show a slight improvement in deep learning-systems in unseen domains, though the performance is not significant.Comment: Will appear in Proceedings of the 54th Annual Conference on Information Sciences and Systems (CISS2020

Context-driven Policies Enforcement for Edge-based IoT Data Sharing-as-a-Service

Sharing real-time data originating from connected devices is crucial to real-world intelligent Internet of Things (IoT) applications, i.e., based on artificial intelligence/machine learning (AI/ML). Such IoT data sharing involves multiple parties for different purposes and is usually based on data contracts that might depend on the dynamic change of IoT data variety and velocity. It is still an open challenge to support multiple parties (aka tenants) with these dynamic contracts based on the data value for their specific contextual purposes.This work addresses these challenges by introducing a novel dynamic context-based policy enforcement framework to support IoT data sharing (on-Edge) based on dynamic contracts. Our enforcement framework allows IoT Data Hub owners to define extensible rules and metrics to govern the tenants in accessing the shared data on the Edge based on policies defined with static and dynamic contexts. We have developed a proof-of-concept prototype for sharing sensitive data such as surveillance camera videos to illustrate our proposed framework. The experimental results demonstrated that our framework could soundly and timely enforce context-based policies at runtime with moderate overhead. Moreover, the context and policy changes are correctly reflected in the system in nearly real-time.acceptedVersio

Nonlinear static and transient isogeometric analysis of functionally graded microplates based on the modified strain gradient theory

The objective of this study is to develop an effective numerical model within the framework of an isogeometric analysis (IGA) to investigate the geometrically nonlinear responses of functionally graded (FG) microplates subjected to static and dynamic loadings. The size effect is captured based on the modified strain gradient theory with three length scale parameters. The third-order shear deformation plate theory is adopted to represent the kinematics of plates, while the geometric nonlinearity is accounted based on the von Kármán assumption. Moreover, the variations of material phrases through the plate thickness follow the rule of mixture. By using Hamilton’s principle, the governing equation of motion is derived and then discretized based on the IGA technique, which tailors the non-uniform rational B-splines (NURBS) basis functions as interpolation functions to fulfil the C2-continuity requirement. The nonlinear equations are solved by the Newmark’s time integration scheme with Newton-Raphson iterative procedure. Various examples are also presented to study the influences of size effect, material variations, boundary conditions and shear deformation on the nonlinear behaviour of FG microplates

Helminth eggs die-off and nutrients : human excreta storage experiment

Are the current practices of handling human excreta for agricultural purposes by farmers in Vietnam good enough?This study set up an excreta storage experiment to research how to inactivate Ascaris lumbricoides eggs and stillmaintain the nutrient value of human excreta

Urocortin 2 Gene Transfer Improves Glycemic Control and Reduces Retinopathy and Mortality in Murine Insulin Deficiency.

Type 1 diabetes affects 20 million patients worldwide. Insulin is the primary and commonly the sole therapy for type 1 diabetes. However, only a minority of patients attain the targeted glucose control and reduced adverse events. We tested urocortin 2 gene transfer as single-agent therapy for insulin deficiency using two mouse models. Urocortin 2 gene transfer reduced blood glucose for months after a single intravenous injection, through increased skeletal muscle insulin sensitivity, increased insulin release in response to glucose stimulation, and increased plasma insulin levels before and during euglycemic clamp. The combined increases in both insulin availability and sensitivity resulted in improved glycemic indices-events that were not anticipated in these insulin-deficient models. In addition, urocortin 2 gene transfer reduced ocular manifestations of long-standing insulin deficiency such as vascular leak and improved retinal function. Finally, mortality was reduced by urocortin 2 gene transfer. The mechanisms for these beneficial effects included increased activities of AMP-activated protein kinase and Akt (protein kinase B) in skeletal muscle, increased skeletal muscle glucose uptake, and increased insulin release. These data suggest that urocortin 2 gene transfer may be a viable therapy for new onset type 1 diabetes and might reduce insulin needs in later stage disease

A New Approach and Tool in Verifying Asynchronous Circuits

Research in asynchronous circuit approach has been carried out recently when asynchronous circuits are presented more widely in electronic systems. As they are more important in human life, their correctness should be considered carefully. Although there are some EDA tools for design and synthesis of asynchronous circuits, they are lack of methods for verifying the correctness of the produced circuits. In this work, we are about to propose a verification method and apply it in making a new version of the PAiD tool that can enable engineers to design, synthesize and verify asynchronous circuits. Experiments in verifying circuits have been also provided in this work

Ultra-wide Spectral Bandwidth and Enhanced Absorption in a Metallic Compound Grating Covered by Graphene Monolayer

Graphene, a two-dimensional monatomic layer of carbon material, has demonstrated as a good candidate for applications of ultrafast photodetectors, transistors, transparent electrodes, and biosensing. Recently, many studies have shown that using metallic deep gratings could enhance the absorptance of graphene of 2.3% up to 80% in the near infrared region for applications in photon detection. This paper presents utilizing a nanograting structure, namely, a compound metallic grating could greatly enhance the absorptance of graphene to 100% and widen its spectral bandwidth to 600 nm, which are greater than those of previous work. The study also showed that the absorptance spectrum is insensitive to angles of incidence. Furthermore, the proposed graphene-covered compound grating might bring a lot of benefits for graphene designs-based optical and optoelectronic devices