An advanced meshless method for time fractional diffusion equation

Recently, because of the new developments in sustainable engineering and renewable energy, which are usually governed by a series of fractional partial differential equations (FPDEs), the numerical modelling and simulation for fractional calculus are attracting more and more attention from researchers. The current dominant numerical method for modeling FPDE is Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings including difficulty in simulation of problems with the complex problem domain and in using irregularly distributed nodes. Because of its distinguished advantages, the meshless method has good potential in simulation of FPDEs. This paper aims to develop an implicit meshless collocation technique for FPDE. The discrete system of FPDEs is obtained by using the meshless shape functions and the meshless collocation formulation. The stability and convergence of this meshless approach are investigated theoretically and numerically. The numerical examples with regular and irregular nodal distributions are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. It is concluded that the present meshless formulation is very effective for the modeling and simulation of fractional partial differential equations

Fabrication of a high sensitive Ag-nanoparticle substrate and its application to the detection of toxic substances

Surface Enhanced Raman Scattering (SERS) is typically observed with the substrate in a liquid medium and it has been proposed as a promising technique for detecting low levels of pollutants in liquids. A technique is presented for self-assembly to immobilize Ag nanoparticles (Ag-NPs), with diameters ranging from 100 to 800nm on a solid support. Experimental results have been obtained through experiments using Ag-NPs active substrates to detect Rhodamine 6G (R6G) and crystal violet in the deionized water. Further, the SERS spectrum and Raman spectrum of phoxim were also measured, showing the enhancement in the performance of the active substrate as a result

TDLAS Detection of propane and butane gas over the near-infrared wavelength range from 1678nm to 1686nm

It is important in the petrochemical industry that there are high sensitivity, high accuracy, low-power consumption and intrinsically safe methods for the detection of propane, butane and their gas mixtures, to provide early warning of potential explosion hazards during both storage and transportation of oil and gas. This paper proposes a 'proof of principle' method for the detection of propane and butane using a Tunable Diode Laser Absorption Spectroscopy (TDLAS) technique over the near-infrared wavelength range from 1678nm to 1686nm. This method is relatively inexpensive to implement and is thus more practical, compared with detection methods using wavelengths further into the infra-red, near 3.3μm. The minimum detectable concentration was found to be low as 300ppm for propane or butane. Importantly, the relative measurement errors were all below 3% LEL, which meets the requirements from the petrochemical and oil-gas storage and transportation industries for a field-based system for monitoring of combustible gases

Enhanced Raman Detection System based on a Hollow-core Fiber Probe design

This paper focus on an enhanced Raman-based detection probe and its performance evaluated. The probe employs a hollow-core fiber design to allow liquid micro-sample to be analyzed. The hollow-core fiber is used both to transmit the light signal used to excite the sample and to collect the Raman scattering signal received from the micro-sample under analysis. In order to maximize the performance of the system, various parameters have been studied experimentally, including the diameter and the height of the liquid sample in the probe. The aim has been optimizing both as a means to enhance the Raman scattering signal received from the liquid sample. As a result, a Raman-based detection probe using a reflector approach was developed and evaluated. This design enabling a greater area for interaction with the sample to be formed and to concentrate the excitation light into it. This then increases the efficiency of the light-liquid interaction and improves the collection efficiently of the forward Raman scattering light signal. With the use of this design, the detected Raman scattering signal was increased by a factor of 103~104 over what otherwise would be achieved. A key feature is that with the use of a hollow-core fiber to collect the liquid sample, only a very small volume is needed, making this well suited to practical applications where limited amounts of material are available e.g. biofluids or high value liquids. The system designed and evaluated thus provides the basis of an effective all-fiber Raman-based detection system, capable of being incorporated into portable analysis equipment for rapid detection and in-the-field use

Localization of fermionic fields on braneworlds with bulk tachyon matter

Recently, Pal and Skar in [arXiv:hep-th/0701266] proposed a mechanism to arise the warped braneworld models from bulk tachyon matter, which are endowed with a thin brane and a thick brane. In this framework, we investigate localization of fermionic fields on these branes. As in the 1/2 spin case, the field can be localized on both the thin and thick branes with inclusion of scalar background. In the 3/2 spin extension, the general supergravity action coupled to chiral supermultiplets is considered to produce the localization on both the branes as a result.Comment: 9 pages, no figure

Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks

This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could be a serious malware vulnerability when deploying a smart surveillance system utilizing face detectors. We show that existing adversarial perturbation methods are not effective to perform such an attack, especially when there are multiple faces in the input image. This is because the adversarial perturbation specifically generated for one face may disrupt the adversarial perturbation for another face. In this paper, we call this problem the Instance Perturbation Interference (IPI) problem. This IPI problem is addressed by studying the relationship between the deep neural network receptive field and the adversarial perturbation. As such, we propose the Localized Instance Perturbation (LIP) that uses adversarial perturbation constrained to the Effective Receptive Field (ERF) of a target to perform the attack. Experiment results show the LIP method massively outperforms existing adversarial perturbation generation methods -- often by a factor of 2 to 10.Comment: to appear ECCV 2018 (accepted version