Intrusion Detection and Prevention (IDPS) is a critical cybersecurity task that involves monitoring network traffic for malicious activity and taking appropriate action to stop it. However, insufficient training data or improperly chosen thresholds often limit the accuracy of such systems, resulting in high false positive rates. To improve the accuracy of an IDPS, blockchain technology can be used. Blockchain technology provides a secure, decentralized, immutable ledger that can track suspicious activity over time and identify intrusions globally. Security teams can use blockchain technology to create immutable records of suspicious activity, give users visibility into the system, and improve the accuracy of intrusion detection systems. In this paper, we propose a novel methodology to improve the accuracy of blockchain-based intrusion detection and prevention systems, which is based on combining different intrusion detection algorithms and using a blockchain-integrated architecture. Our experimental results show that the proposed system significantly increases the accuracy while reducing the false positive rate, opening up new opportunities for the development of highly accurate networks.
There can be numerous electronic components on a given PCB, making the task of visual inspection to detect defects very time-consuming and prone to error, especially at scale. There has thus been significant interest in automatic PCB component detection, particularly leveraging deep learning. However, deep neural networks typically require high computational resources, possibly limiting their feasibility in real-world use cases in manufacturing, which often involve high-volume and high-throughput detection with constrained edge computing resource availability. As a result of an exploration of efficient deep neural network architectures for this use case, we introduce PCBDet, an attention condenser network design that provides state-of-the-art inference throughput while achieving superior PCB component detection performance compared to other state-of-the-art efficient architecture designs. Experimental results show that PCBDet can achieve up to 2× inference speed-up on an ARM Cortex A72 processor when compared to an EfficientNet-based design while achieving ∼2-4% higher mAP on the FICS-PCB benchmark dataset.
To improve the detection rate of pulmonary nodules in early lung cancer screening, a low-dose CT pulmonary nodule detection algorithm based on 3D CNN-CapsNet (3D convolution neural network and capsule network) was presented. However, the convolution kernel size of the traditional CNN is relatively simple at each layer, and it is difficult to obtain more abundant features, which is not effective for medical images with a hierarchical structure and does not fully consider the spatial information of medical sequence data. CapsNet is a new network architecture that can be used to classify, using a group of neurons as a capsule to replace the traditional neural networks, it may be made to the attribute information and spatial feature extraction. The network structure we designed includes FCN and CapsNet. First, the convolution kernels of different sizes are used to extract features at different scales. Then enter the initial feature map to obtain the first part into the designed CapsNet to get the final classification result. Through the experimental verification of the ELCAP database, the nodule detection rate is 95.19%, the sensitivity is 92.31%, the specificity is 98.08% and the F1-score is 0.95 which are much better than other baseline methods.
The target and sea clutter Doppler domains frequently overlap due to the frequent passage of slow ship targets through the sea clutter zone. In this letter, a novel sea clutter suppression method is suggested as a solution to this issue, whose key is a novel singular value zeroing criterion guided by the search results of two-dimensional spectral peaks. Verified by simulations, the method proposed can improve signal-to-clutter ratio (SCR) from -8 dB to 41 dB in the frequency domain and be more effective than the conventional SVD-FRFT method in and improved SVD-FRFT method in .
As detection technology continually advances, the survivability of targets on the battlefield is significantly challenged. Therefore, microwave absorbers with stealth capabilities have become a focal point of research in modern military science. To address the issues of narrow bandwidth and complex structures in existing absorbers, we propose a model for an ultra-wideband absorber based on a hybrid structure. In this study, we design, manufacture, and characterize a polarization-insensitive ultra-wideband absorber (PIUWA), which demonstrates impressive absorptivity of over 90% across a range of 4-24.53GHz (a fractional bandwidth of 144%). This is achieved by inducing multiple resonance peaks within the hybrid structure. Moreover, the subwavelength periodicity of the PIUWA theoretically contributes to its angular stability under full-wave polarizations. We observed that absorption performance remains stable under incident conditions within 45 degrees. Furthermore, the operational mechanism of the PIUWA is elucidated through an equivalent circuit model, with design validity confirmed via experimental measurements. This study paves the way for the design and fabrication of ultra-wideband microwave absorbers that offer high absorptivity, robust angular stability, and simpler assembly processes, thereby broadening the potential for application in other absorber types.
This work is mainly to describe the phenomenon at low frequency in my previous publication. In this paper, the impact of the magnetostriction mechanism is taken into consideration for the main idea. The axisymmetric FEM model of the spiral-coil EMAT is established to implement the simulation. With the help of the simulation, it is demonstrated that the directivity of ultrasonic wave can be manipulated by frequency. And it is found that the direction of Lorentz force that dominates in the rail varies with time, but the magnetostrictive force compels the ultrasonic wave mainly generated by the Lorentz force to the axis. This describes well that the power of two combined mechanisms is greater than that of only the Lorentz-force mechanism at low frequency.
We propose and experimentally demonstrate an on-chip all-optical multicasting (AOM) for 40 Gbit/s mode-division-multiplexed quadrature phase-shift keying (MDM-QPSK) signals based on a parallel dispersion-engineered multimode nonlinear silicon waveguide. Five dual-mode multicast wavelengths are successfully obtained on the generate idlers, and the power penalties of all the multicast channels are less than 1.1 dB at the bit error rate (BER) of 3.8×10-3. The dual-mode AOM scheme has the potential to promote the ability of optical cross-connect in practical hybrid multiplexed networks including MDM channels.
In this letter, we introduce a design of virtual guarded SiPMs fabricated in a standard 0.35 μm standard complementary metal oxide semiconductor (CMOS) process. We compare the performance of these virtual guarded cells (VGC) to that of conventional cells with real guard rings, referred to as physical guarded cells (PGC). Specifically, we evaluate the photon detection efficiency (PDE) of both types of SiPMs. Our results demonstrate that the VGC SiPM outperforms the PGC SiPM, exhibiting a true PDE of (22.5 ± 0.5) %, which is significantly higher than the PDE of (10.9 ± 0.3) % obtained for the PGC SiPM. The superior PDE of the VGC SiPM is attributed to a larger active or photosensitive area due to the virtual guard rings and a thinner n-layer in the photosensitive region.
An improved coot optimization algorithm is proposed for wireless sensor networks (WSNs) coverage optimization. To monitor the interest field and obtain the valid data, a wireless sensor network coverage model is established. The population is initialized with cubic map and opposition-based learning strategy. The leader population is reversely learned dimension by dimension, so as to improve the diversity of the population and the global optimization ability of the algorithm. The simplex method is introduced to optimize the local exploration of the population. The experimental results show that the enhanced coot optimization algorithm for coverage optimization in wireless sensor networks can reduce energy consumption and improve network coverage.
In this paper, we investigate the application of Hybrid Representation in Wide-Angle Synthetic Aperture Radar (WASAR) imaging, addressing the challenges of achieving sparse representation in the presence of complex electromagnetic scattering characteristics and highly anisotropic targets. We utilize a Convolutional Neural Network (CNN) to represent two-dimensional data within the same subaperture, while employing dictionary learning for sparse representation across different subapertures. Convolutional Neural Networks (CNNs) excel at learning spatial hierarchies and local dependencies in two-dimensional data, but require a large amount of training data. Isotropic targets within subapertures can be used for training with conventional SAR data, whereas anisotropic targets present challenges in obtaining training samples. To address this, a dictionary for different subapertures is generated from measurements using dictionary learning, eliminating the need for additional training data. By integrating these methods, we propose a novel approach, Hybrid-WASAR, which incorporates two regularization terms into WASAR imaging and employs the Alternating Direction Method of Multipliers (ADMM) to iteratively solve the imaging model. Compared to traditional WASAR imaging techniques, Hybrid-WASAR not only enhances the accuracy of the reconstructed target backscatter coefficients, but also effectively reduces sidelobes and noise, resulting in a significant improvement in overall imaging quality.
In this letter, a novel model for broadband power amplifier (PA) linearization is proposed, namely Attention Mechanism based Bidirectional Long Short-term Memory network (AM-BiLSTM). In order to verify the linearization performance of the AM-BiLSTM model, a 100MHz bandwidth 5G new radio (5G NR) signal is employed to test the sub-6G PA operating at 2.6-GHz. The experimental results show that the adjacent channel power ratio (ACPR) of the PA with AM-BiLSTM can be improved by 24dB which is 6-dB better than the generalized memory polynomial (GMP) and 3-dB better than the Chebyshev polynomials LSTM (CP-LSTM) in ref. Therefore, the proposed AM-BiLSTM is very effective for the linearization of broadband PA.
A common 400V dc bus for industrial motor drives advantageously allows the use of high-performance 600V power semiconductor technology in the inverter drive converter stages and to lower the rated power of the supplying rectifier system. Ideally, this supplying rectifier system features unity power factor operation, bidirectional power flow and nominal power operation in the three-phase and the single-phase grid. This paper introduces a novel bidirectional universal single-/three-phase-input unity power factor differential ac-dc converter suitable for the above mentioned requirements: The basic operating principle and conduction states of the proposed topology are derived and discussed in detail. Then, the main power component voltage and current stresses are determined and simulation results in PLECS are provided. The concept is verified by means of experimental measurements conducted in both three-phase and single-phase operation with a 6kW prototype system employing a switching frequency of 100 kHz and 1200V SiC power semiconductors.
In this letter, an analytical method for the beampattern synthesis of symmetric nonuniform array is proposed. This method consists of two steps. In the first step, it acquires a real symmetric excitation by the convex optimization method to attain a pencil beam. In the second step, it superposes the pencil beams pointing in different directions to synthesize the prescribed beampattern. Numerical results are provided to verify the effectiveness of the proposed method.
Using Jensen's inequality and integration by parts, we derive some tight upper bounds on the Gaussian Q-function. The tightness of the bounds obtained by Jensen's inequality can be improved by increasing the number of exponential terms, and one of them is invertible. We obtain a piece-wise upper bound and show its application in the analysis of the symbol error probability of various modulation schemes in different channel models.
A broadband heterogeneous circularly polarized (CP) dipole antenna with a backed cavity is presented in this letter. The proposed antenna consists of a pair of rotational symmetric short-circuited heterogeneous branches and a Γ-shaped feed structure. Each branch is designed to be axe-shaped so that the antenna can achieve a broad 3dB axial ratio (AR) bandwidth. The coupled feeding method assures the antenna is wideband, and the shorting-to-the-ground technique miniaturizes the lateral dimensions of the antenna. The profile of the proposed antenna is around 0.16λL (λL denotes the wavelength of the lower bound frequency). The introduction of a back cavity effectively enhances the boresight gain and improves the isolation level if the antenna is used to form an array. Finally, the design is prototyped, and the measurement results agree well with the simulation. The fractal -10 dB S11 bandwidth and 3dB AR bandwidths are 54.3% (2.74-4.78 GHz) and 45.9% (3.15-5.03 GHz), respectively. The antenna’s efficiency exceeds 91.5% over the target frequency band.
Radar forward-looking imaging is gaining significance due to its convenience in various applications like battlefield reconnaissance, target surveillance and precision guidance. Although synthetic aperture radar (SAR) techniques are commonly used to achieve high azimuth resolution, they suffer from limitations in forward-looking area due to the poor Doppler resolution and the “left-right” ambiguity problem. In recent years, generative adversarial networks (GANs), a common deep learning approach that produces excellent results in image motion blur removal, has been extensively used. This letter proposes building an end-to-end forward-looking imaging network using GAN to produce high-resolution images, which increases the efficiency and quality of imaging. Compared to conventional forward-looking imaging methods such as the deconvolution-based methods, this algorithm eliminates the design and iterative processes of the observation matrix. Simulated and real radar data verified that this approach offers robust recovery and better performance.
We propose criteria for recess etching to fabricate T-gate used in InGaAs HEMTs. By patterning additional rectangular pads on the source and drain metals in the e-beam lithography step, it is possible to measure the drain-to-source resistance (Rds) and current (Ids). the ratio (Γ) of before and after etching for each Rds and Ids can be used as criteria to determine the point in time to stop etching. By performing recess etching with Γ= 1.97 for Rds and Γ= 0.38 for Ids on an epiwafer having cap doping concentration of 2= 1019 cm−3 and channel indium content of 0.7, we have fabricated InGaAs mHEMT device showing gm,max= 1603 mS/mm and ft= 290 GHz at Lg= 124 nm. The criteria presented can be applied to InGaAs HEMTs with various epitaxial structures.
This letter proposes an instantaneous frequency tracking method to extend the dynamic range for heterodyne fiber optic hydrophones (FOHs). They are used directly to compensate for large signal amplitudes. The working principle is discussed, and simulations are conducted. The simulations achieve at least 20 dB dynamic range improvement.