Search Results (333)

The aim of this study was to determine the connection between oscillations in operating pressure values and the appearance of various irregularities on machined surfaces. Such oscillations are a consequence of the high water pressure generated during abrasive water jet machining. Oscillations in the operating pressure values are periodic, namely due to the cyclic operation of the intensifier and the physical characteristics of water. One of the most common means of reducing this phenomenon is installing an attenuator in the hydraulic system or a phased intensifier system. The main hypothesis of this study was that the topography of a machined surface is directly influenced by the inability of the pressure accumulator to fully absorb water pressure oscillations. In this study, we monitored changes in hydraulic oil pressure values at the intensifier entrance and their connection with irregularities on the machined surface—such as waviness—when cutting aluminum AlMg3 of different thicknesses. Experimental research was conducted in order to establish this connection. Aluminum AlMg3 of different thicknesses—from 6 mm to 12 mm—was cut with different traverse speeds while hydraulic oil pressure values were monitored. The pressure signals thus obtained were analyzed by applying the fast Fourier transform (FFT) algorithm. We identified a single-sided pressure signal amplitude spectrum. The frequency axis can be transformed by multiplying inverse frequency data with traverse speed; in this way, a single-sided amplitude spectrum can be obtained, examined against the period in which striations are expected to appear (in millimeters). In the lower zone of the analyzed samples, striations are observed at intervals determined by the dominant hydraulic oil pressure harmonics, which are transferred to the operating pressure. In other words, we demonstrate how the machined surface topography is directly induced by water jet pressure frequency characteristics. Full article

Lightweight speech denoising models have made remarkable progress in improving both speech quality and computational efficiency. However, most models rely on long temporal windows as input, limiting their applicability in low-latency, real-time scenarios on edge devices. To address this challenge, we propose a lightweight hybrid module, Temporal Statistics Enhancement, Squeeze-and-Excitation-based Dual Convolutional Attention, and Band-wise Attention (TSE, SDCA, BA) Module. The TSE module enhances single-frame spectral features by concatenating statistical descriptors—mean, standard deviation, maximum, and minimum—thereby capturing richer local information without relying on temporal context. The SDCA and BA module integrates a simplified residual structure and channel attention, while the BA component further strengthens the representation of critical frequency bands through band-wise partitioning and differentiated weighting. The proposed model requires only 0.22 million multiply–accumulate operations (MMACs) and contains a total of 112.3 K parameters, making it well suited for low-latency, real-time speech enhancement applications. Experimental results demonstrate that among lightweight models with fewer than 200K parameters, the proposed approach outperforms most existing methods in both denoising performance and computational efficiency, significantly reducing processing overhead. Furthermore, real-device deployment on an improved hearing aid confirms an inference latency as low as 2 milliseconds, validating its practical potential for real-time edge applications. Full article

This study investigates the dynamic behavior of an articulated boom offshore crane under various load application laws. The following steps were taken to perform numerical simulations using the finite-element method (FEM): Definition of the model’s geometry, materials, and boundary conditions. The modal analyses reveal significant resonance frequencies in the direction of load application (payload). The crane’s displacement, velocity, and acceleration responses are closely related to load application laws, specifically the time required to reach the structure’s full payload (epsilon). It is highly correlated with the dynamic factor (maximum acceleration multiplied by payload), which has a wide range of effects on the structure, including the effects of overstress, overturning, buckling, and so on. The main findings reveal a very strong exponential correlation, allowing the dynamic effect to be estimated as a function of epsilon time. This is a useful tool for increasing the safety and reliability of offshore lifting operations. Full article

The existing multi-carrier composite modulation recognition methods have failed to effectively integrate inner and outer modulation characteristics, thereby limiting the potential for improving recognition performance under low signal-to-noise ratio (SNR) conditions. To address this issue, this paper proposes a multi-carrier composite signal modulation recognition algorithm based on a multi-dimensional time-frequency superimposed spectrum (MD-TFSS) with integrated inner and outer features, which can recognize composite modulation signals in the set {BPSK-PM, QPSK-PM, BPSK-QPSK-PM, BPSK-BPSK-PM, QPSK-QPSK-PM}. The proposed method constructs a dual spectrum through multiplying an inner modulation spectrum and a squared spectrum, then combines the inner modulation dual spectrum with the outer modulation time-frequency diagram in dual-channel mode to form MD-TFSS features. Based on the MD-TFSS, a blind recognition algorithm is implemented using the dual-channel input ECA-ResNet18 (DECA-ResNet18) incorporating the ECA attention mechanism. The proposed algorithm first converts the complex features of multi-carrier composite modulation signals into visually interpretable image features (including the quantity and concentration of bright spots and lines) through the MD-TFSS, achieving intuitive representation of multiple modulation characteristics. Meanwhile, the dual-channel input mechanism enables collaborative expression of outer modulation time-frequency diagram and inner modulation dual spectrum features, ensuring tight integration of inner and outer characteristics while avoiding feature isolation issues in traditional multi-diagram concatenation methods. Secondly, the DECA-ResNet18 network dynamically allocates weights through an adaptive regulation mechanism based on input feature differences, autonomously adjusting channel attention levels to effectively capture complementary characteristics from both inner and outer modulation features, thereby enhancing recognition accuracy and generalization capability for multi-carrier composite modulation signals. Theoretical analysis and simulation results demonstrate that, compared with the existing methods that use isolated outer and inner features or conventional multi-feature diagram construction approaches, the proposed algorithm achieves superior recognition performance under low SNR conditions. Additionally, DECA-ResNet18 demonstrates enhanced recognition performance for multi-carrier composite modulated signals compared to the traditional ResNet18. Full article

A linear frequency modulation (LFM) signal and its corresponding de-chirp operation are one of the basic methods for wideband radar signal processing, which can reduce the burden of the radar system sampling rate and is more suitable for large-bandwidth signal processing. More importantly, most existing methods against interrupted sampling repeater jamming (ISRJ) are based on time–frequency (TF) or frequency domain analysis of the de-chirped signal. However, the above anti-ISRJ methods cannot be directly applied to multiple-input multiple-output (MIMO) radar with multiple beams, because the angular waveform (AW) in mainlobe directions does not possess the TF properties of the LFM signal. Consequently, this work focuses on the co-optimization of transmit beampattern and AW similarity in wideband MIMO radar systems. Different from the existing works, which only concern the space–frequency pattern of the transmit waveform, we recast the transmit beampattern and AW expressions for wideband MIMO radar in a more compact form. Based on the compact expressions, a co-optimization model of the transmit beampattern and AWs is formulated where the similarity constraint is added to force the AW to share the TF properties of the LFM signal. An algorithm based on the alternating direction method of multipliers (ADMM) framework is proposed to address the aforementioned problem. Numerical simulations show that the optimized waveform can form the desired transmit beampattern and its AWs have similar TF properties and de-chirp results to the LFM signal. Full article

In this study, a novel improved ultra-wideband (UWB) antipodal Vivaldi antenna suitable for breast cancer detection via microwave imaging was designed. The antenna was made more directional by adding three pairs of nestings to the antenna fins by adding elliptical patches. The frequency operating range of the proposed antenna is UWB 3.6–13 GHz, its directivity is 11 dB, and its gain is 9.27 dB. The antenna is designed with FR4 dielectric material and dimensions of 34.6 mm × 33 mm × 1.6 mm. It was demonstrated that the bandwidth, gain, and directivity of the proposed antenna meet the requirements for UWB radar applications. The Vivaldi antenna was tested on an imaging system developed using the CST Microwave Studio (CST MWS) program. In CST MWS, a hemispherical heterogeneous breast model with a radius of 50 mm was created and a spherical tumor with a diameter of 0.9 mm was placed inside. A Gaussian pulse was sent through Vivaldi antennas and the scattered signals were collected. Then, adaptive Wiener filter and image formation algorithm delay-multiply-sum (DMAS) steps were applied to the reflected signals. Using these steps, the tumor in the breast model was scanned at high resolution. In the simulation application, the tumor in the heterogeneous phantom was detected and imaged in the correct position. A monostatic radar-based system was implemented for scanning a breast phantom in the prone position in an experimental setting. For experimental measurements, homogeneous (fat and tumor) and heterogeneous (skin, fat, glandular, and tumor) breast phantoms were produced according to the electrical properties of the tissues. The phantoms were designed as hemispherical with a diameter of 100 mm. A spherical tumor tissue with a diameter of 16 mm was placed in the phantoms produced in the experimental environment. The dynamic range of the VNA device used allowed us to image a 16 mm diameter tumor in the experimental setting. The developed microwave imaging system shows that it is suitable for the early-stage detection of breast cancer by scanning the tumor in the correct location in breast phantoms. Full article

We quantify the advantages of a recently proposed data processing technique to search for continuous gravitational wave (GW) signals from isolated rotating asymmetric neutron stars in data measured by ground-based GW interferometers. This technique relies on the symmetry of the motion around the Sun of an Earth-bound gravitational wave interferometer. By multiplying the measured data time series with a half-year time-shifted copy of it, we obtain two advantages: (i) the main Doppler phase modulation of a monochromatic gravitational wave signal is exactly removed, and (ii) the signal in the product data are located at twice the GW signal frequency. The first significantly reduces the size of the signal’s parameter space over which a search is to be performed. The second is advantageous at low frequencies; we find that, with currently available computer processing speeds, this technique is capable of achieving sensitivity that is comparable to or even better than coherent and other possibly non-coherent methods. Further, since our proposed method is implemented over a year-long data segment, it requires processing time comparable to the data acquisition time of currently available computers. Full article

The Number Theoretic Transform (NTT) is a cornerstone for efficient polynomial multiplication, which is fundamental to lattice-based cryptographic algorithms such as CRYSTALS-Kyber—a leading candidate in post-quantum cryptography (PQC). However, existing NTT accelerators often rely on integer multiplier-based modular reduction techniques, such as Barrett or Montgomery reduction, which introduce significant computational overhead and hardware resource consumption. These accelerators also lack optimization in unified architectures for forward (FNTT) and inverse (INTT) transformations. Addressing these research gaps, this paper introduces a novel, high-speed NTT accelerator tailored specifically for CRYSTALS-Kyber. The proposed design employs an innovative shift-add modular reduction mechanism, eliminating the need for integer multipliers, thereby reducing critical path delay and enhancing circuit frequency. A unified pipelined butterfly unit, capable of performing FNTT and INTT operations through Cooley–Tukey and Gentleman–Sande configurations, is integrated into the architecture. Additionally, a highly efficient data handling mechanism based on Register banks supports seamless memory access, ensuring continuous and parallel processing. The complete architecture, implemented in Verilog HDL, has been evaluated on FPGA platforms (Virtex-5, Virtex-6, and Virtex-7). Post place-and-route results demonstrate a maximum operating frequency of 261 MHz on Virtex-7, achieving a throughput of 290.69 Kbps—1.45× and 1.24× higher than its performance on Virtex-5 and Virtex-6, respectively. Furthermore, the design boasts an impressive throughput-per-slice metric of 111.63, underscoring its resource efficiency. With a 1.27× reduction in computation time compared to state-of-the-art single butterfly unit-based NTT accelerators, this work establishes a new benchmark in advancing secure and scalable cryptographic hardware solutions. Full article

Frequency agile radar (FAR) exhibits robust anti-jamming capabilities and a superior low probability of intercept performance due to its randomized carrier frequency (CF) and pulse repetition frequency (PRF) hopping sequences. The advent of compressed sensing (CS) theory has effectively addressed the coherent processing challenges of frequency agile signals. Nonetheless, the reconstructed results often suffer from elevated sidelobe levels, which lead to significant sparse recovery errors. The performance of sparse reconstruction is greatly influenced by the correlation between the dictionary matrix columns. Specifically, weaker correlation usually means better target detection performance and lower false alarm probability. Consequently, this paper adopts the maximum coherence coefficient (MCC) between the dictionary matrix columns as the cost function. In addition, in order to reduce the correlation of the dictionary matrix and improve the target detection performance, a genetic algorithm (GA) is employed to jointly optimize the CF hopping coefficients and PRFs of the FAR. The echo of optimized signals is subsequently reconstructed using the alternating direction method of multipliers (ADMM) algorithm. Simulation results demonstrate the effectiveness of the proposal. Full article

The authors of this study suggest an improvement to their recently released quadruple-diode boost regulator (QDBC), which may be used in two configurations: without or with a voltage multiplier unit (VMU). This voltage multiplier unit consists of two switch capacitors diagonally connected across two diodes, or vice versa. During each operational cycle, energy can be stored and released through the switch capacitive filters and inductive chokes, increasing voltage gain and decreasing output fluctuation. ANSOFT/SIMPLORER 7, PLECS 4.9.5, and SIMULINK 2021a are further used to simulate the proposed regulator’s linearized version to investigate its frequency response and stability. Hence, to improve the harmonic performance of the proposed regulator, the authors of this study used a delta modulation current regulator (DMCR), sometimes referred to as a variable bandwidth delta modulation current regulator. The findings show that the QDBC has, when using the DMCR, a voltage gain of $1+D/{(1-D)}^2$, an efficiency of 97%, and a shorter settling time of 0.04 s when compared to other DC-DC regulators (SEPIC, boost, and quadratic boost). Finally, to validate the theoretical analysis and simulation results of the proposed QDBC structure, a 250 W regulator prototype was built utilizing similar design exercise requirements. Full article

Background/Objectives: Heart failure is a very common disease, and its incidence is increasing. Echocardiography is a non-invasive tool frequently used in the diagnosis and risk stratification of heart failure. In our study, we aimed to evaluate the risk of all-cause mortality, hospitalization due to decompensated heart failure, and appropriate shocks in reduced ejection fraction patients (HFrEF) with an implantable cardioverter–defibrillator (ICD) according to a novel tissue Doppler echocardiographic parameter that reflects pulmonary capillary wedge pressure. Methods: A total of 320 HFrEF patients with ICD were included in the study between 1 February 2021 and 30 June 2023, from the cardiology outpatient clinic and cardiology ward. Using tissue Doppler, the peak systolic velocity (ST) at the free wall side of the tricuspid annulus and the peak systolic velocity (SM) at the lateral side of the mitral annulus were measured, and the ratio of ST to SM (ST/SM) was calculated. The inferior vena cava diameter (IVCDi) was measured during inspiration. These two values were multiplied to form the formula IVCDi × (ST/SM). Based on the IVCDi × (ST/SM) value, patients were divided into two groups: those with high values (>17, n = 144) and those with low values (≤17, n = 176). The primary endpoint of our study was all-cause mortality, and the secondary endpoint was major adverse cardiovascular events (MACE), including appropriate shocks, hospital admission due to acute heart failure decompensation, and mortality. Results: Long-term mortality was higher in the high IVCDi × (ST/SM) group compared to the low-value group (44% vs. 15%, p < 0.001). The MACE frequency was also higher in patients with high IVCDi × (ST/SM) values (71% vs. 30%, p < 0.001). In multivariable analysis, IVCDi × (ST/SM) was an independent predictor of both mortality (HR: 1.027, 95%CI: 1.009–1.046, p = 0.003), and MACE (HR: 1.018, 95%CI: 1.004–1.032, p = 0.013). Conclusions: We demonstrated that the IVCDi × ST/SM value, a novel tissue Doppler echocardiographic parameter, is an independent predictor of both long-term mortality and major adverse cardiac events (MACE) in HFrEF patients with ICD. This parameter may be valuable in identifying high-risk patients and optimizing their treatment management. Full article

On the basis of the space voltage vector pulse width modulation (SVPWM) technique, the random pulse width modulation (RPWM) technique, which can reduce harmonics, is investigated based on the vector control system of permanent magnet synchronous motor (PMSM) to address the problem of generating a large number of high-amplitude harmonics at the carrier frequency and its multiplier frequency. Firstly, the root causes of the large number of high-amplitude harmonics at the carrier frequency and its multiplier frequency are analyzed in depth, and the RPWM technique is explained in detail on how to reduce the amplitude of these harmonics effectively. Secondly, to address the problem of insufficient random performance in the traditional RPWM technique, an innovative optimization scheme is proposed, i.e., the introduction of a two-state Markov chain and, based on the immune algorithm for transition probability and random gain, the optimization of two key parameters. Ultimately, through experimental verification, the proposed method significantly improves the spectral distribution of the current waveform compared with the traditional RPWM, which makes the distribution more uniform and effectively reduces the high-amplitude harmonics concentrated near the carrier frequency and its octave frequency, thus enhancing the overall performance of the system. Full article

With the exponential growth in transactions and exchanges carried out via the Internet, the risks of the falsification and distortion of information are multiplying, encouraged by widespread access to the virtual world. In this context, digital image watermarking has emerged as an essential solution for protecting digital content by enhancing its durability and resistance to manipulation. However, no current digital watermarking technology offers complete protection against all forms of attack, with each method often limited to specific applications. This field has recently benefited from the integration of deep learning techniques, which have brought significant advances in information security. This article explores the implementation of digital watermarking in embedded systems, addressing the challenges posed by resource constraints such as memory, computing power, and energy consumption. We propose optimization techniques, including frequency domain methods and the use of lightweight deep learning models, to enhance the robustness and resilience of embedded systems. The experimental results validate the effectiveness of these approaches for enhanced image protection, opening new prospects for the development of information security technologies adapted to embedded environments. Full article

Edge-computing applications demand ultra-low-power architectures for both feature extraction and classification tasks. In this manuscript, a Keyword Spotting (KWS) system tailored for energy-constrained portable environments is proposed. A 16-channel analog filter bank is employed for audio feature extraction, followed by a digital Gated Recurrent Unit (GRU) classifier. The filter bank is behaviorally modeled, making use of second-order band-pass transfer functions, simulating the analog front-end (AFE) processing. To enable efficient deployment, the GRU classifier is trained using a Learned Step Size (LSQ) and Look-Up Table (LUT)-aware quantization method. The resulting quantized model, with 4-bit weights and 8-bit activation functions (W4A8), achieves 91.35% accuracy across 12 classes, including 10 keywords from the Google Speech Command Dataset v2 (GSCDv2), with less than 1% degradation compared to its full-precision counterpart. The model is estimated to require only 34.8 kB of memory and 62,400 multiply–accumulate (MAC) operations per inference in real-time settings. Furthermore, the robustness of the AFE against noise and analog impairments is evaluated by injecting Gaussian noise and perturbing the filter parameters (center frequency and quality factor) in the test data, respectively. The obtained results confirm a strong classification performance even under degraded circuit-level conditions, supporting the suitability of the proposed system for ultra-low-power, noise-resilient edge applications. Full article

A high-efficiency frequency multiplier is presented in 65-nm CMOS with a core area of 0.06 mm². A low-cost five-segment triangular-resistance phase interpolation scheme is proposed. By performing resistive interpolation on four-path orthogonal triangular signals, 10-fold frequency multiplication is achieved within the input frequency range of 12–20 MHz. The prototype only includes a quadrature square-wave generator, four orthogonal square-triangular converters and the proposed four-path 5-segment triangular-resistance phase interpolators, with a frequency deviation less than 7%. The presented design achieves an output power of −9.8 dBm, with an input power of −2.0 dBm and power consumption of 0.45 mW from a 1.2-V supply, which obtains a frequency multiplication efficiency up to 9.6%. The proposed mechanism could be extended to accomplish a configurable multiplication factor. Full article