MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

Deep neural networks (DNNs) are vulnerable to adversarial attack which is maliciously implemented by adding human-imperceptible perturbation to images and thus leads to incorrect prediction. Existing studies have proposed various methods to detect the new adversarial attacks. However, new attack methods keep evolving constantly and yield new adversarial examples to bypass the existing detectors. It needs to collect tens of thousands samples to train detectors, while the new attacks evolve much more frequently than the high-cost data collection. Thus, this situation leads the newly evolved attack samples to remain in small scales. To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples. Specifically, the learning consists of a double-network framework: a task-dedicated network and a master network which alternatively learn the detection capability for either seen attack or a new attack. To validate the effectiveness of our approach, we construct the benchmarks with few-shot-fashion protocols based on three conventional datasets, i.e. CIFAR-10, MNIST and Fashion-MNIST. Comprehensive experiments are conducted on them to verify the superiority of our approach with respect to the traditional adversarial attack detection methods.Comment: 10 pages, 2 figures, accepted as the conference paper of Proceedings of the 27th ACM International Conference on Multimedia (MM'19

The Meshfree Radial Point Interpolation Method (RPIM) for Wave Propagation Dynamics in Non-Homogeneous Media

This work presents a novel simulation approach to couple the meshfree radial point interpolation method (RPIM) with the implicit direct time integration method for the transient analysis of wave propagation dynamics in non-homogeneous media. In this approach, the RPIM is adopted for the discretization of the overall space domain, while the discretization of the time domain is completed by employing the efficient Bathe time stepping scheme. The dispersion analysis demonstrates that, in wave analysis, the amount of numerical dispersion error resulting from the discretization in the space domain can be suppressed at a very low level when the employed nodal support domain of the interpolation function is adequately large. Meanwhile, it is also mathematically shown that the amount of numerical error resulting from the time domain discretization is actually a monotonically decreasing function of the non-dimensional time domain discretization interval. Consequently, the present simulation approach is capable of effectively handling the transient analysis of wave propagation dynamics in non-homogeneous media, and the disparate waves with different speeds can be solved concurrently with very high computation accuracy. This numerical feature makes the present simulation approach more suitable for complicated wave analysis than the traditional finite element approach because the waves with disparate speeds always cannot be concurrently solved accurately. Several numerical tests are given to check the performance of the present simulation approach for the analysis of wave propagation dynamics in non-homogeneous media

Direction-Finding Study of a 1.7 mm Diameter Towed Hydrophone Array Based on UWFBG

This paper investigates a 1.7 mm diameter ultra-weak fiber Bragg grating (UWFBG) hydrophone towed array cable for acoustic direction finding. The mechanism of the underwater acoustic waves received by this integrated-coating sensitizing optical cable is deduced, and it is shown that the amplitude of its response varies with the direction of the sound wave. An anechoic pool experiment is carried out to test the performance of such a hydrophone array. The test array is a selection of six sensing fibers, each of which is coiled into 9 cm diameter fiber ring suspended in the water to receive acoustic signals. An average sensitivity of −141.2 dB re rad/μPa at frequencies from 2.5 kHz to 6.3 kHz was achieved, validating the detection of the azimuth of underwater acoustic waves. The ultra-thin towing cable system, with free structure, high sensitivity, and underwater target-detection capability has demonstrated great potential for future unmanned underwater vehicle (UUV) applications

Lithium-Ion Battery Prognostics with Hybrid Gaussian Process Function Regression

The accurate prognostics of lithium-ion battery state of health (SOH) and remaining useful life (RUL) have great significance for reducing the costs of maintenance. The methods based on the physical models cannot perform satisfactorily as the systems become more and more complex. With the development of digital acquisition and storage technology, the data of battery cells can be obtained. This makes the data-driven methods get more and more attention. In this paper, to overcome the problem that the trend fitting deteriorates rapidly when test data are far from the training data for multiple-step-ahead estimation, a prognostic method fusing the wavelet de-noising (WD) method and the hybrid Gaussian process function regression (HGPFR) model for predicting the RUL of the lithium-ion battery is proposed. Gaussian process regression (GPR) is a typical representative for the Bayesian structure with non-parameter expression and uncertainty presentation. In this case, the effects on predictive results are compared and analyzed using the proposed method and the HGPFR model with different lengths of training data. Besides, in consideration of the degradation characteristics for the lithium-ion battery data set, the selections of the wavelet de-noising method are performed with corresponding experimental analyses. Furthermore, we set the hype-parameter for the mean function and co-variance function, and then develop a method for parameter optimization to make the proposed model suitable for the data. Moreover, a numerical simulation based on the data repository of Department of Engineering Science (DES) university of Oxford and Center for Advanced Life Cycle Engineering (CALCE) of University of Maryland is carried out, and the results are analyzed. For the data repository, an accuracy of 2.2% is obtained compared with the same value of 6.7% for the HGPFR model. What is more, the applicability and stability are verified with the prognostic results by the proposed method

Pretreatment of Ultra-Weak Fiber Bragg Grating Hydrophone Array Based on Cubic Spline Interpolation Using Intensity Compensation

The demodulation algorithm based on 3 × 3 coupler in a fiber-optic hydrophone array has gained extensive attention in recent years. The traditional method uses a circulator to construct the normal path-match interferometry; however, the problem of increasing the asymmetry of the three-way signal to be demodulated is easily overlooked. To provide a solution, we report a pretreatment method for hydrophone array based on 3 × 3 coupler demodulation. We use cubic spline interpolation to perform nonlinear fitting to the reflected pulse train and calculate the peak-to-peak values of the single pulse to determine the light intensity compensation coefficient of the interference signal, so as to demodulate the corrected three-way interference signal. For experimental verification, ultra-weak fiber Bragg gratings (uwFBGs) with reflectivity of −50 dB are applied to construct a hydrophone array with 800 sensors, and a vibratory liquid column method is set up to generate a low-frequency hydroacoustic signal. Compared to the traditional demodulation algorithm based on a 3 × 3 coupler, the pretreatment method can improve the consistency of interference signals. The Lissajous figures show that cubic spline interpolation can improve the accuracy of monopulse peak seeking results by about 1 dB, and intensity compensation can further lead to a much lower noise density level for the interference pulse amplitude—specifically, more than 7 dB at 5~50 Hz—and the signal-to-noise ratio is improved by approximately 10 dB at 10 Hz. The distinct advantages of the proposed pretreatment method make it an excellent candidate for a hydrophone array system based on path-match interferometry

Ultrathin interferometric hydrophone towed line array based on uwFBG

In order to improve the suitability of the fiber hydrophone towing line array, we propose an interferometric hydrophone towed line array with a diameter of 1.7 mm. The line array is an integration of sensitization and package, embedding grating sensors in the composite materials of Kevlar and polyurethane in an additional pultrusion process. The theory and experiment indicate that polymer cladding of pultrusion is an effective way to improve phase sensitivity, increasing mechanical strength and decreasing cable diameter simultaneously. Then, a hydroacoustic detection system, with a quasi-distributed ultra-weak fiber Bragg grating towed line array, based on unbalanced interference is established and its phase sensitivities are tested experimentally. The result is measured by the vibration liquid column method and compared with a standard piezoelectric underwater acoustic detector. Over the frequency range of 200–2000 Hz, the system has a good amplitude–frequency response. We obtain an average phase sound pressure sensitivity of about −147.96 dB (re 1 rad/μPa) and a relative flatness response of 3 dB. The experimental results show that this system provides the possibility of an integrated hydrophone towed linear array with high adaptability and reliability

Multiple-Octave-Spanning Vibration Sensing Based on Simultaneous Vector Demodulation of 499 Fizeau Interference Signals from Identical Ultra-Weak Fiber Bragg Gratings Over 2.5 km

Multi-point vibration sensing at the low frequency range of 0.5–100 Hz is of vital importance for applications such as seismic monitoring and underwater acoustic imaging. Location-resolved multi-point sensing using a single fiber and a single demodulation system can greatly reduce system deployment and maintenance costs. We propose and demonstrate the demodulation of a fiber-optic system consisting of 500 identical ultra-weak Fiber Bragg gratings (uwFBGs), capable of measuring the amplitude, frequency and phase of acoustic signals from 499 sensing fibers covering a total range of 2.5 km. For demonstration purposes, we arbitrarily chose six consecutive sensors and studied their performance in detail. Using a passive demodulation method, we interrogated the six sensors simultaneously, and achieved a high signal-to-noise ratio of 22.1 dB, excellent linearity, phase sensitivity of around 0.024 rad/Pa, and a dynamic range of about 38 dB. We demonstrated a frequency response flatness of <1.2 dB in the range of 0.5–100 Hz. Compared to the prior state-of-the-art demonstration using a similar method, we have increased the sensing range from 1 km to 2.5 km, and increased the frequency range from 0.4 octaves to 7.6 octaves, in addition to achieving sensing in the very challenging low-frequency range of 0.5–100 Hz

Integrative Expression and Prognosis Analysis of DHX37 in Human Cancers by Data Mining

DHEA-Box Helicase 37 (DHX37) is a putative RNA helicase. It is involved in various RNA secondary structure alteration processes, including translation, nuclear splicing, and ribosome assembly. It is reported to be associated with the neurodevelopmental disorder with brain anomalies, and a recent study suggests that DHX37 is a functional regulator of CD8 T cells. Dysregulation of the CD8 T cell function is closely related to defective antitumor immune responses. In the present study, we investigated the expression, mutation, and prognostic role of DHX37 in human cancers, mainly by mining publicly available datasets. Our results suggested that DHX37 was significantly upregulated in 17 kinds of tumors. Mutations including deletions, insertions, and substitutions of DHX37 were widely detected. Besides, the expression of DHX37 was negatively correlated with immune-related genes PD-L1, RGS16, and TOX, and it was positively associated with TIM3, LAG3, and NCOR2. Through biofunctional analysis, we observed that DHX37 was significantly enriched in cancer-related pathways such as cell cycle, DNA replication, mismatch repair, RNA degradation, and RNA polymerase. In conclusion, the study explored the significance of DHX37 in human cancers. DHX37 may serve as a potential target for cancer immunotherapy

Landscape Dynamics of the Mu Us Sandy Land Based on Multi-Source Remote Sensing Images

This study meticulously investigates landscape alterations within the Mu Us Sandy Land, a critical region for desertification control in China. The research dissects the dynamic characteristics and inter-conversion of landscape elements across eleven distinct periods by employing multi-source remote sensing imagery spanning 1963 to 2020, alongside visual interpretation, random forest classification, and the desertification difference index (DDI). The analysis uncovers significant landscape transformations within the Mu Us Sandy Land over the past six decades, following a precise chronological sequence. A pivotal shift occurred around 1986, characterized by opposing trends within fixed and shifting sandy land. The earlier stage (pre-1986) witnessed a substantial decrease (66.9%) in the fixed sandy land area, accompanied by a corresponding rise (38.7%) in shifting sandy land. Conversely, the later stage (post-1986) era exhibited a remarkable increase (309.7%) in fixed sandy land, alongside a significant decline (78.9%) in shifting sand land coverage. This study identifies two stages of landscape transformation: a pre-1986 phase dominated by the conversion of fixed sandy land to semi-fixed sandy land and a post-1986 reversal toward shifting sand land into fixed sandy land. These sequential transformations have shaped the landscape pattern alterations observed in the Mu Us Sandy Land since 1963. The dramatic landscape improvements observed after 1986 can be primarily attributed to the implementation and continued investment in large-scale ecological restoration projects. This study’s findings, which reveal the intricate landscape dynamics and their implications for ecosystem management, provide a scientific foundation for refining and formulating comprehensive strategies to control desertification and manage the Mu Us Sandy Land’s unique ecosystem