Search Results (645)

Wireless sensor networks (WSNs) are used for data acquisition and transmission in unmanned surface vessels (USVs). However, the openness of wireless networks makes USVs highly susceptible to false data injection (FDI) attacks during data transmission, which affects the sensors’ ability to receive real data and leads to decision-making errors in the control center. In this paper, a novel dynamic data encryption method is proposed whereby data are encrypted prior to transmission and the key is dynamically updated using historical system data, with a view to increasing the difficulty for attackers to crack the ciphertext. At the same time, a dynamic relationship is established among ciphertext, key, and auxiliary encrypted ciphertext, and an attack detection scheme based on dynamic encryption is designed to realize instant detection and localization of FDI attacks. Further, an $H_{\infty }$ fusion filter is designed to filter external interference noise, and the real information is estimated or restored by the weighted fusion algorithm. Ultimately, the validity of the proposed scheme is confirmed through simulation experiments. Full article

Under deep, high-intensity mining conditions, a high mineral pressure develops at the working face, which can easily cause floor heave deformation of the roadway. In this paper, with the geological conditions of Buertai coal mine as the background, through on-site monitoring and numerical simulation, the mechanism of strong dynamic pressure roadway floor heave is clarified and a cooperative control method for roadway floor heave deformation is proposed. The main conclusions are as follows: (1) The overall strength of the floor of this strong dynamic pressure roadway is low, which can easily cause roadway floor heave, and on-site multivariate monitoring of the mine pressure is carried out, which clarifies the evolution law of the mine pressure of the mining roadway and along-the-airway roadway. (2) Combined with FLAC3D numerical simulation software, we analyze the influence of coal seam depth and floor lithology on the stability of the roadway floor and find that both have a significant influence on the stability of the roadway. Under the condition of high-intensity mining, the floor will deteriorate gradually, forming a wide range of floor heave areas. (3) Based on the deformation and damage mechanism of the roadway floor, a synergistic control method of “roof cutting and pressure relief + floor anchor injection” is proposed and various technical parameters are designed. An optimized design scheme is designed for the control of floor heave in Buertai coal mine. Full article

In the era of big data, the security of information encryption systems has garnered extensive attention, particularly in critical domains such as financial transactions and medical data management. While traditional Shamir’s Secret Sharing (SSS) ensures secure integer sharing through threshold cryptography, it exhibits inherent limitations when applied to floating-point domains and high-precision numerical scenarios. To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. By categorizing real numbers into four types—rational numbers, special irrationals, common irrationals, and general irrationals—our approach achieves lossless transmission for rational numbers, special irrationals, and common irrationals, while enabling low-loss recovery for general irrationals. The scheme leverages a type-coding system to embed data category identifiers in polynomial coefficients, combined with Bernoulli-distributed random bit injection to enhance security. The experimental results validate its effectiveness in balancing precision and security across various real-number types. Full article

To investigate the energy conduction behavior of polymer gel profile control and flooding in low-permeability reservoirs, a parallel dual-tube displacement experiment was conducted to simulate reservoirs with different permeability ratios. Injection schemes included constant rates from 0.40 to 1.20 mL/min and dynamic injection from 1.20 to 0.40 mL/min. Pressure monitoring and shunt analysis were used to evaluate profile control and recovery performance. The results show that polymer gel preferentially enters high-permeability layers, transmitting pressure more rapidly than in low-permeability zones. At 1.20 mL/min, pressure onset at 90 cm in the high-permeability layer occurs earlier than in the low-permeability layer. Higher injection rates accelerate pressure buildup. At 0.80 mL/min, permeability contrast is minimized, achieving a 22.96% recovery rate in low-permeability layers. The combination effect of 1.2–0.4 mL/min is the best in dynamic injection, with the difference in shunt ratio of 9.6% and the recovery rate of low permeability layer increased to 31.23%. Polymer gel improves oil recovery by blocking high-permeability channels, expanding the swept volume, and utilizing viscoelastic properties. Full article

Cantonese Automatic Speech Recognition (ASR) is hindered by tonal complexity, acoustic diversity, and a lack of labelled data. This study proposes a phoneme-aware hierarchical augmentation framework that enhances performance without additional annotation. A Phoneme Substitution Matrix (PSM), built from Montreal Forced Aligner alignments and Tacotron-2 synthesis, injects adversarial phoneme variants into both transcripts and their aligned audio segments, enlarging pronunciation diversity. Concurrently, a semantic-aware SpecAugment scheme exploits wav2vec 2.0 attention heat maps and keyword boundaries to adaptively mask informative time–frequency regions; a reinforcement-learning controller tunes the masking schedule online, forcing the model to rely on a wider context. On the Common Voice Cantonese 50 h subset, the combined strategy reduces the character error rate (CER) from 26.17% to 16.88% with wav2vec 2.0 and from 38.83% to 23.55% with Zipformer. At 100 h, the CER further drops to 4.27% and 2.32%, yielding relative gains of 32–44%. Ablation studies confirm that phoneme-level and masking components provide complementary benefits. The framework offers a practical, model-independent path toward accurate ASR for Cantonese and other low-resource tonal languages. This paper presents an intelligent sensing-oriented modeling framework for speech signals, which is suitable for deployment on edge or embedded systems to process input from audio sensors (e.g., microphones) and shows promising potential for voice-interactive terminal applications. Full article

With the advance of Artificial Intelligence, Deep Neural Networks are widely employed in various sensor-based systems to analyze operational conditions. However, due to the inherently nondeterministic and probabilistic natures of neural networks, the assurance of overall system performance could become a challenging task. In particular, soft errors could weaken the robustness of such networks and thereby threaten the system’s safety. Conventional fault-tolerant techniques by means of hardware redundancy and software correction mechanisms often involve a tricky trade-off between effectiveness and scalability in addressing the extensive design space of Deep Neural Networks. In this work, we propose a Reinforcement-Learning-based approach to protect neural networks from soft errors by addressing and identifying the vulnerable bits. The approach consists of three key steps: (1) analyzing layer-wise resiliency of Deep Neural Networks by a fault injection simulation; (2) generating layer-wise bit masks by a Reinforcement-Learning-based agent to reveal the vulnerable bits and to protect against them; and (3) synthesizing and deploying bit masks across the network with guaranteed operation efficiency by adopting transfer learning. As a case study, we select several existing neural networks to test and validate the design. The performance of the proposed approach is compared with the performance of other baseline methods, including Hamming code and the Most Significant Bits protection schemes. The results indicate that the proposed method exhibits a significant improvement. Specifically, we observe that the proposed method achieves a significant performance gain of at least 10% to 15% over on the test network. The results indicate that the proposed method dynamically and efficiently protects the vulnerable bits compared with the baseline methods. Full article

The experimental and computational characterization of a cold model prototype designed to test the electromagnetic properties of a new RFQ (Radio-Frequency Quadrupole) cavity is reported. This cavity is intended to be an essential part of a compact, high-gradient proton accelerator for medical purposes. The RFQ’s design employs a novel RF power-coupler injection solution. One common way to couple the RF power in proton RFQs has been the use of loop-couplers inserted into the mid-section of the RFQ’s lobe sections. This technique has been demonstrated to be reliable and effective but introduces a significant perturbation into the lobe that can be more noticeable when dealing with compact structures. We propose a RF injection scheme that uses direct transition from a coaxial cable to the RFQ by connecting the inner coaxial conductor to the RFQ vane body. As a consequence, the lobe geometry is not perturbed, and the transversal electrical fields are directly excited through the vanes. Moreover, by using a pair of such couplers connected to opposite vanes at a given transversal plane of the RFQ, it is also possible to excite the desired quadrupolar TE210 modes while avoiding the excitation of dipolar TE110 modes. The resonances corresponding to different RFQ modes have been characterized, and the dependence of the amplitude of the modes on the relative phase of the field injected through the RF power ports has been demonstrated both by measurements and simulations. Full article

The strong heterogeneity of carbonate reservoirs poses significant technical challenges in reservoir classification and permeability evaluation. This study proposes a new method for reservoir classification based on nuclear magnetic resonance (NMR) logging data for the Asmari formation of the Middle East M Oilfield, a carbonate reservoir. By integrating NMR T₂ spectrum characteristic parameters (such as T₂ geometric mean, T_2R35/R50/R65, and pore volume fraction) with principal component analysis (PCA) for dimensionality reduction and an improved slope method, this study achieves fine reservoir type classification. The results are compared with core pressure curves and petrographic pore types. This study reveals that the Asmari reservoir can be divided into four categories (RT1 to RT4). RT1 reservoirs are characterized by large pore throats (maximum pore throat radius >3.8 μm), low displacement pressure (<0.2 MPa), and high permeability (average 22.16 mD), corresponding to a pore structure dominated by intergranular dissolution pores. RT4 reservoirs, on the other hand, exhibit small pore throats (<1 μm), high displacement pressure (>0.7 MPa), and low permeability (0.66 mD) and are primarily composed of dense dolostone or limestone. The classification results show good consistency with capillary pressure curves and petrographic pore types, and the pore–permeability relationships of each reservoir type have significantly higher fitting goodness (R² = 0.48~0.68) compared with the unclassified model (R² = 0.24). In the new well application, the root mean square error (RMSE) of permeability prediction decreased from 0.34 mD using traditional methods to 0.21 mD, demonstrating the method’s effectiveness. This approach does not rely on a large number of mercury injection experiments and can achieve reservoir classification solely through NMR logging. It provides a scalable technological paradigm for permeability prediction and development scheme optimization of highly heterogeneous carbonate reservoirs, offering valuable references for similar reservoirs worldwide. Full article

With the widespread adoption of deep learning in critical domains, such as computer vision, model security has become a growing concern. Backdoor attacks, as a highly stealthy threat, have emerged as a significant research topic in AI security. Existing backdoor attack methods primarily introduce perturbations in the spatial domain of images, which suffer from limitations, such as visual detectability and signal fragility. Although subsequent approaches, such as those based on steganography, have proposed more covert backdoor attack schemes, they still exhibit various shortcomings. To address these challenges, this paper presents HCBA (high-frequency chroma backdoor attack), a novel backdoor attack method based on high-frequency injection in the UV chroma channels. By leveraging discrete wavelet transform (DWT), HCBA embeds a polarity-triggered perturbation in the high-frequency sub-bands of the UV channels in the YUV color space. This approach capitalizes on the human visual system’s insensitivity to high-frequency signals, thereby enhancing stealthiness. Moreover, high-frequency components exhibit strong stability during data transformations, improving robustness. The frequency-domain operation also simplifies the trigger embedding process, enabling high attack success rates with low poisoning rates. Extensive experimental results demonstrate that HCBA achieves outstanding performance in terms of both stealthiness and evasion of existing defense mechanisms while maintaining a high attack success rate (ASR > 98.5%). Specifically, it improves the PSNR by 25% compared to baseline methods, with corresponding enhancements in SSIM as well. Full article

Fluid flow and mass transfer processes in some fractured aquifers are negligible in the low-permeability rock matrix and occur mainly in the fracture network. In this work, we consider coupled variable-density flow (VDF) and mass transport with dissolution in discrete fracture networks (DFNs). These three processes are ruled by nonlinear and strongly coupled partial differential equations (PDEs) due to the (i) density variation induced by concentration and (ii) fracture aperture evolution induced by dissolution. In this study, we develop an efficient model to solve the resulting system of nonlinear PDEs. The new model leverages the method of lines (MOL) to combine the robust finite volume (FV) method for spatial discretization with a high-order method for temporal discretization. A suitable upwind scheme is used on the fracture network to eliminate spurious oscillations in the advection-dominated case. The time step size and the order of the time integration are adapted during simulations to reduce the computational burden while preserving accuracy. The developed VDF-DFN model is validated by simulating saltwater intrusion and dissolution in a coastal fractured aquifer. The results of the VDF-DFN model, in the case of a dense fracture network, show excellent agreement with the Henry semi-analytical solution for saltwater intrusion and dissolution in a coastal aquifer. The VDF-DFN model is then employed to investigate coupled flow, mass transfer and dissolution for an injection/extraction well pair problem. This test problem enables an exploration of how dissolution influences the evolution of the fracture aperture, considering both constant and variable dissolution rates. Full article

The rapid growth of inverter-based resources (IBRs) has created a need for new islanding detection methodologies to determine whether an IBR has been disconnected from the transmission grid in some manner (islanded) or remains connected to the transmission grid (grid-connected). Active islanding detection methods inject a signal into the power system to achieve detection. Existing schemes frequently limit consideration to a single node system with one IBR. Schemes tested on multiple IBRs often see interference, with the signals from one IBR disturbing the others, or require intricate communication. Further, several methods destabilize an islanded grid to detect it, preventing a prospective microgrid from remaining in operation while islanded. This work develops an active islanding detection scheme using Pulse Compression Probing (PCP) that is microgrid-compatible and can be used with multiple IBRs without requirement for communication. This active islanding detection scheme can be implemented on existing inverter switching sequences and has a detection time of 167–223 ms, well within the detection time specified by existing standards. The method is verified via electromagnetic transient (EMT) simulation on a modified version of a 34-bus test system. Full article

This study presents a comprehensive treatment system for addressing leakage challenges in underground structure construction within complex karst terrains, demonstrated through the case of Baiyun Station in Guangzhou. Integrating advanced geological investigation, dynamic grouting techniques, and adaptive structural remediation strategies, this methodology effectively mitigates water inflow risks in structurally heterogeneous karst environments. Key innovations include the “one-trench two-drilling” exploration-grouting system for karst cave detection and filling, a multi-stage emergency water-gushing control protocol combining cofferdam sealing and dual-fluid grouting, and a zoned epoxy resin injection scheme for structural fissure remediation. Implementation at Baiyun Station achieved quantifiable outcomes: karst cave filling rates increased from 35.98% to 82.6%, foundation pit horizontal displacements reduced by 67–68%, and structural seepage repair rates reached 96.4%. The treatment system reduced construction costs by CNY 12 million and shortened schedules by 45 days through optimized pile formation efficiency (98% qualification rate) and minimized rework. While demonstrating superior performance in sealing > 0.2 mm fissures, limitations persist in addressing sub-micron fractures and ensuring long-term epoxy resin durability. This research establishes a replicable framework for underground engineering in karst regions, emphasizing real-time monitoring, multi-technology synergy, and environmental sustainability. Full article

Bilateral teleoperation of skid-steering mobile robots with time-varying delays presents significant challenges in ensuring accurate leader–follower coupling. This article presents a novel controller for a bilateral teleoperation system composed of a robot manipulator and a skid-steering mobile robot. The proposed controller leverages neural networks to compensate for ground–robot interactions, uncertain dynamics, and communication delays. The control strategy integrates a shared scheme between damping injection and two neural networks, enhancing the robustness and adaptability of the delayed system. A rigorous theoretical analysis of the closed-loop teleoperation system is provided, establishing conditions of control parameters to ensure stability and convergence of the coordination errors. The proposed method is validated through numerical testing, demonstrating strong agreement between theoretical outcomes and simulation results. Full article

This paper provides a comprehensive analysis of gas field produced water from four perspectives: water sources, chemical composition, treatment methods, and application scenarios. It identifies critical challenges in current formation reinjection practices, including poor containment performance for injection layers, difficulties in optimal layer selection, and uncertainties in injection volume determination. To address these issues, systematic selection criteria for reinjection layers were established. Taking a depleted gas reservoir in the Ordos Basin as a case study, we conducted a geological analysis of candidate formations based on previous research findings. We set up three groups of schemes regarding injection wells, injection rate, and permeability inhomogeneity and studied reservoir reinjection water volume, reinjection formation pressure, reinjection waves and range, and reinjection safety using three-dimensional numerical simulation technology. Finally, we selected the preferred scheme of reinjection well location in consideration of permeability inhomogeneity, with a cumulative reinjection volume of 1554.3 × 10⁴ m³ and a change in reinjection formation pressure of 0~20 MPa. The pressure change in the upper overburden of the reinjection layer was kept within 3 MPa, a value consistent with actual historical reinjection data, confirming again the accuracy of this layer selection strategy and the aforementioned layer selection analysis and providing a basis for layer selection and reinjection safety for the assessment of recovered water reinjection in other unconventional gas reservoirs. Full article

This study examines the impact of midpoint voltage fluctuations on the performance of multilevel converters and proposes an advanced control strategy to reduce the required DC bus capacitance while maintaining system stability. The research demonstrates that active voltage imbalance control in active neutral-point-clamped (ANPC) topologies allows for stable operation with significantly reduced capacitor values. A hybrid control approach, combining fuzzy logic control and third-harmonic injection PWM (THIPWM), is developed to enhance voltage balancing, and modulation techniques are systematically optimized. Both simulation and experimental analyses confirm the efficacy of the proposed method, which achieves superior voltage regulation compared to conventional PI-based control schemes. Specifically, experimental results show a reduction in peak-to-peak DC-link voltage fluctuation from 116 V to just 4 V, and the phase current THD is reduced from 3.6% to 0.8%. The results indicate a substantial reduction in voltage fluctuations, contributing to a total harmonic distortion (THD) as low as 0.8%. Furthermore, the proposed strategy facilitates an approximate 26-fold decrease in DC bus capacitor size without compromising system stability. The reduction in capacitance not only lowers the overall system costs and hardware complexity but also improves reliability. The inverter was tested at a rated power of 62.5 kW using 0.3 mF capacitors instead of the theoretically required 7.8 mF. This work advances power electronics by presenting an efficient voltage balancing methodology, offering a cost-effective and robust solution for multilevel converter applications. The findings are validated through comprehensive simulations and experimental tests, ensuring practical applicability. Full article