Search Results (542)

Identifying induction-motor equivalent-circuit parameters from nameplate data is challenging without the IEEE Std 112 no-load and locked-rotor tests. This study reformulates the task from constraint-based curve fitting to population-calibrated maximum-a-posteriori (MAP)-type estimation of seven steady-state parameters. Under an identical protocol, the best of fifteen metaheuristics reached 14.71% global error against 23.40% for the best analytical method; its residual structure motivates the central step: closed-form nameplate predictors, calibrated on a five-motor reference population, become Gaussian prior means whose cross-validated dispersions set the prior widths and the $\pm 3\sigma$ search bounds. Re-anchoring the loss priors to a per-machine constant-loss decomposition (MAP+) lowers the apparent error to 3.48%, and nested leave-one-out cross-validation, re-calibrating all statistical quantities per fold, gives a validated 4.27%. With algorithm, budget and seeds fixed, formulation outweighs optimizer choice. Withholding catalog quantities and predicting them back gives forty out-of-fit checks on ten machines: rated current within 0.96% and partial-load power factor within 2.65%, but the breakdown-torque ratio only within 9.04%, proving it an input rather than an output; locked-rotor errors confine the single-cage model to running operation. It offers a calibrated, validity-bounded basis for the steady-state layer of digital twins and energy auditing, not a general-purpose estimator. Full article

Bandwidth-limited aerial–ground sensing requires an explicit trade-off among payload size, decoded-map quality, and downstream route utility. This paper evaluates a strict RGB-D edge-perception interface in which the receiver accesses only a quantized C × 16 × 16 tensor and no encoder-side skip features. Under a fixed AeroScapes protocol, five-seed latent-8 training gives a test intersection over union (IoU) of 0.5617 ± 0.0585 and route utility of 0.0539 ± 0.0227; the strongest validation-selected checkpoint reaches an IoU of 0.6584 but is reported only as a checkpoint-specific result. Acontrolled five-seed width ablation identifies a Pareto set: latent-8 is the lowest-rate operating point at 16.448 kbit, latent-16 has the smallest IoU standard deviation, and latent-32 gives the highest mean IoU (0.5788) and route utility (0.0921), with no significant pairwise differences between widths. A paired threeseed stabilization test likewise finds no significant IoU improvement from depth dropout, a soft topology loss, or their combination (p ≥ 0.6060); the combined configuration raises mean IoU to 0.5700 but increases dispersion. Relative to a practical reference combining JPEG (quality 75) RGB and 8-bit PNG depth, latent-8 reduces the mean payload by a factor of 4.32. The digital-link study extends the additive-noise analysis to fading, intersymbol interference, timevariation, packet and burst errors, near–far interference, and corrupted range metadata. Conventional short codes, source-aware unequal protection, and a 3GPP NR LDPC implementation are evaluated with framing, automatic repeat request, mediumaccess overhead, and transmission delay. Cross-domain evaluation establishes an important limitation: zero-shot AeroScapes-to-UAVid transfer is weak, whereas sequence-disjoint tenseed UAVid training improves the eight-class mean IoU from 0.2417 ± 0.0221 for RGB-only to 0.2602 ± 0.0129 for strict RGB-D (p = 0.0161). Lightweight depth, visibility, missingdepth, weighted-topology, and coarse-to-local refinement experiments further delimit deployment. Together, these experiments provide an auditable cross-layer evaluation linking source representation, channel reliability, protocol cost, spatial error, and receivergrid connectivity without equating one favorable checkpoint with general superiority. Full article

The filling-and-emptying valve and downstream shaft are crucial components of navigation-lock systems. Under insufficient downstream submergence, air can be drawn through the shaft and trapped in the post-valve culvert, altering the flow structure and compromising hydraulic stability. A three-dimensional Reynolds-averaged Navier–Stokes/volume-of-fluid model was developed to investigate shaft aeration and entrapped-air-pocket evolution under varying inlet velocities and downstream-submergence depths. The aeration process comprises three stages: jet establishment, air-pocket formation, and air-pocket breakup and reorganization. Downstream-submergence depth determines whether a continuous air-intake pathway forms, whereas inlet velocity primarily controls aeration intensity and air-pocket persistence once the pathway is established. With decreasing submergence depth, the flow transitions successively from a water-sealed regime to a transition regime, a stable entrapped-air-pocket regime, and a strongly unsteady hydraulic-jump-like regime. For the present geometry and fixed valve opening, the transition from transient to sustained shaft aeration is identified within the downstream-submergence interval of h_w = 2–5 m. Combined analyses of the air-pocket volume per unit width, pressure response, vortex structures, and shear-layer characteristics indicate that enhanced jet-induced shear is closely associated with shaft aeration and air entrapment, while pressure fluctuations are closely coupled with air-pocket formation, persistence, breakup, and reorganization. Full article

Repeated non-equidistant unmanned aerial vehicle (UAV) inspections of slope-road cracks require measurements from different distances, poses, and image scales to remain comparable and sufficiently precise for engineering-state decisions. Existing studies rarely integrate cross-view physical conversion, measurement uncertainty, and a project-defined minimum detectable change. We develop an engineering-detectability framework that defines cross-period criteria for crack width and displacement and derives equivalent widths for ideal, representative non-standard, and arbitrary viewpoints. First-order error propagation and reliability allocation convert the minimum detectable change into accuracy requirements for range, field of view, and normalized image coordinates. Crack-boundary coordinates and localization uncertainties provide a common interface for interchangeable detection and photogrammetric modules. Validation combines a controlled fixed-camera sequence with a close-range field-camera multiview test of seven physical openings under local coplanarity. All six determinate stages in the controlled sequence agreed with the digital image correlation (DIC) comparison, while one borderline stage required review. Across the seven openings, the four-view means gave a mean absolute error (MAE) of 0.196 mm and a root mean square error (RMSE) of 0.270 mm, with cross-view coefficients of variation (CVs) of 0.33–4.93%. An illustrative error budget demonstrates reverse screening of system configurations from project thresholds. The framework therefore connects viewpoint-equivalent measurements, uncertainty constraints, and engineering-state decisions in an auditable chain. Full article

Underground coal mining can induce deformation and failure of overlying strata and ground surface, which seriously endangers the safety of human life and property. During mining, the immediate roof rock successively experiences initial caving (fixed support on four sides) and periodic caving (fixed support on three sides and free on one side). Different boundary conditions alter the unloading and deformation processes such as cracking and fracturing of immediate roof rock, thereby affecting its subsequent mechanical behavior of compaction and deformation, and resulting in differences in the movement law of overlying strata. In this paper, the numerical simulation method is adopted to investigate the variation laws of unloading and fracturing characteristics of immediate roof rock under initial caving and periodic caving with thickness-width ratio (t/w), length-width ratio (l/w), unloading stress (σ_u) and specimen strength (σ_c), and the corresponding action mechanism is revealed. The fractal evolution law of fractured immediate roof rock obtained from this study can quantitatively evaluate the compaction characteristics of caved rock, provide refined parameter support for surface subsidence prediction and possess guiding significance for stope surrounding rock control engineering. The results show that the fragments formed after the failure of immediate roof rock are mainly block-strip shaped under both first caving and periodic caving conditions. With the increase in the thickness-width ratio, the flexural rigidity of immediate roof rock increases and crack propagation is restrained, so that the particle-size–mass fractal dimension of fragments increases first and then decreases for the two caving modes. The increase in length-width ratio weakens the propagation of secondary fractures and raises the particle size of fragments, while the overall variation in particle-size–mass fractal dimension is small under the two working conditions. As the unloading stress continuously rises, the coupled tension-shear effect inside the rock gradually intensifies, and the failure mode changes from tension-shear failure to global shear failure. Accordingly, both the particle-size–mass fractal dimension and fractal dimension of crack distribution increase first and then decrease under first caving and periodic caving conditions. The increase in the strength of immediate roof rock raises the energy consumption during rock failure, and large-size fragments are more likely to be generated, which reduces the particle-size–mass fractal dimension and increases the particle size of fragments under both caving modes. Meanwhile, internal micro-fractures continuously initiate and propagate with the growth of rock strength. For specimens with relatively high strength, crack propagation is inhibited and the development of secondary fractures is weakened, leading to an evolution trend that the fractal dimension of crack distribution increases first and then decreases. Under identical parameter conditions, the particle-size distribution and crack complexity for first caving are mainly affected by geometric parameters; the particle size of fragments is primarily controlled by specimen strength; and the unloading stress threshold governs the transition of failure mode. For periodic caving, the crack-initiation location is first determined by asymmetric boundary constraints. The thickness-width ratio dominates the particle-size distribution of fragments, and unloading stress as well as specimen strength further regulate the complexity of cracks. Full article

Enhanced circular tubes are widely employed in shell-and-tube heat exchangers, power-generation condensers, chemical reactors, refrigeration systems, and air-cooled heat exchangers, where improved convective performance can reduce the heat-transfer area required for a specified thermal duty. Helical screw tapes (HSTs) are passive inserts that promote sustained swirling motion and enhance convective heat transfer within such tubes. Although helical screw tapes and multiple-insert arrangements have been investigated previously, the combined thermohydraulic and second-law effects of increasing the number of co-rotating HSTs under fixed geometric ratios remain insufficiently quantified. In this investigation, turbulent airflow in a heated round tube was numerically investigated to examine the effect of tape number on heat transfer, pressure drop, thermal performance, total entropy generation (S_total), and exergy destruction (Ex_D). Six HST configurations containing one to six tapes were examined over a Reynolds-number range of Re = 5000–20,000 in a circular tube with an inner diameter of D_T = 31 mm, which was also adopted as the characteristic length for the Reynolds number, Nusselt number, and friction factor. The helical pitch P, screw diameter D_s, tape width W, and tape thickness t were 60 mm, 30 mm, 4.5 mm, and 0.2 mm, respectively, giving a pitch ratio of P/D_s = 2.0 and a width ratio of W/D_s = 0.15. A plain tube (PT) served as the baseline case. The results show that increasing the number of tapes intensifies swirl flow and enhances heat transfer but also leads to a continuous increase in pressure loss. For the optimum three-tape arrangement, the Nusselt number is increased by 126.0–158.8% and the thermal performance factor by 4.5–19.5% relative to the plain tube, while the total entropy generation and exergy destruction are simultaneously reduced by 7.9–61.0%. Among the configurations examined, HST-P2.0-W0.150-3, comprising three tapes at a pitch ratio of P/D_s = 2.0 and a width ratio of W/D_s = 0.15, achieved the best overall performance by delivering the highest thermal performance factor and the lowest total entropy generation and exergy destruction among the HST cases. Full article

Wind power interval forecasting remains challenging due to the uncertainty and strong variability of wind generation. To capture temporal dependency and predictive uncertainty, this paper proposes a hybrid interval forecasting framework that integrates an Informer-based point prediction model with a temporal convolutional network (TCN) conditional quantile model. The Informer is used to generate deterministic forecasts, while the TCN models the temporal dependency of prediction residuals and estimates conditional quantiles for interval construction. To further improve interval quality, an improved osprey optimization algorithm (IOOA) is introduced to optimize key TCN hyperparameters. The Coverage–Width Criterion (CWC) on the validation set is adopted as the optimization objective for hyperparameter tuning and adaptive quantile-pair selection. To maintain the nominal 90% confidence level, candidate quantile pairs are constrained to have a fixed quantile span of 0.90. Experiments on real-world wind power datasets demonstrate that, when averaged across the two wind farms, the proposed framework achieves a prediction interval coverage probability (PICP) of 0.910, satisfying the nominal coverage level of 90%, and a mean prediction interval width (MPIW) of 7.48, the lowest among all compared methods. Specifically, it reduces the mean interval width by 8.89–28.35% relative to the benchmark models, indicating that the proposed framework generates sharper prediction intervals without compromising coverage reliability and achieves a better trade-off between reliability and sharpness. Full article

Optical Camera Communication (OCC) enables data reception using common CMOS cameras and commercial webcams. However, applying multi-level modulation with rolling-shutter sensors is constrained by temporal acquisition parameters that may be undocumented or not directly accessible, making it challenging since many existing solutions rely on specialized hardware or require high processing complexity. This paper demonstrates that reliable multi-level OCC can be achieved using only unmodified commercial hardware and straightforward signal processing by experimentally characterizing and validating a 4-level pulse width modulation (4-PWM) link. Data are encoded in the duty cycle of the transmitted signal and recoveblack from the width of the captublack rolling-shutter stripes. Two internal timing parameters are estimated directly from the captublack images without access to the internal camera timing: the row readout period (34.38 $\mathsf{\mu }$s), obtained from the spatial periodicity of the stripes, and the effective integration time (490 $\mathsf{\mu }$s), inferblack from the deformation of the received constellation with carrier frequency. A single-parameter model is derived to describe this deformation and is validated at two carrier frequencies differing by a factor of four, pblackicting constellation compression, a fixed point at a duty cycle of 0.5, and constellation collapse (followed by inversion) when the exposure-to-carrier-period ratio reaches 0.5. We evaluate system performance under different exposure settings, showing that automatic camera control strongly degrades multi-level detection (BER of 0.290, with mean image level variation constrained to $0.14\%$ compablack to $61\%$ under fixed exposure). Under optimal fixed-exposure operating conditions, a prospective 15 min transmission achieved zero bit errors over 35,878 bits at 40 bps, corresponding to a $95\%$ upper confidence bound on the BER of $8.4\times {10}^{-5}$. These results reveal a practical balance between cost, complexity, and performance, demonstrating that 4-PWM rolling-shutter OCC is a viable solution for Internet of Things (IoT) signaling and low-rate data transmission using commercially available devices. Full article

This paper presents the hardware aspects of a Hjorth-parameter deep neural network (DNN)-based cardiac fibrillation diagnosis pipeline targeting low-power Internet of Medical Things (IoMT) devices and ASIC implementations. Building on earlier edge-to-cloud studies where Hjorth activity, mobility, and complexity were computed in software on microcontrollers and classified by a floating-point DNN, we introduce a fully synthesizable fixed-point hardware module that computes these parameters in real time, together with a quantized neural network (QNN) operating directly on the resulting fixed-point features. The Hjorth block includes derivative generation, accumulator banks, variance computation, and hardware divider and square-root units. Using the Shandong Provincial Hospital Database (SPHD) as in our previous work, we evaluate the impact of end-to-end fixed-point quantization on the AF-related arrhythmia detection performance for bit widths between 6 and 16 bits. For 10–12-bit configurations, the quantized pipeline achieves accuracy of approximately 93.7% and an area under the ROC curve (AUC) above 0.97, closely matching the floating-point baseline while significantly reducing the arithmetic complexity and memory footprint. ASIC synthesis in a 28 nm CMOS standard-cell library shows that the complete atrial detector core, integrating the Hjorth extractor and the hardware fully connected QNN, occupies on the order of $2\times {10}^4\mathsf{\mu }{\mathrm{m}}^2$ and dissipates about 3 mW, with a critical-path delay of 7.08 ns. For the optimal 10–12-bit operating points, the synthesized core achieves per-inference energy in the range of 18.6–19.0 nJ (18,600–19,000 pJ) per classification, confirming its suitability for integration into wearable and IoMT ECG monitoring nodes. These results demonstrate that co-designed fixed-point Hjorth hardware and quantized DNNs can deliver a favorable trade-off between diagnostic performance, area, power, latency, and per-inference energy compared with existing MCU-, FPGA-, and ASIC-based ECG classifiers. Full article

Coal-bearing tight gas and deep coalbed methane (CBM) widely co-occur in China, and integrated commingled production outperforms separate development. Conventional separated simulation fails to capture coupled reservoir–wellbore gas–water flow. This study develops an integrated geomechanical coupled numerical model with multi-scale fractures and multi-phase wellbore flow: tight gas reservoirs use a stress-sensitive single-porosity model, deep CBM adopts a dual-porosity model for matrix desorption, and EDFM characterizes non-Darcy flow in hydraulic fractures. The Gray gas column and liquid column methods calculate layered bottomhole pressure according to reservoir vertical distribution, and matrix bordering solves the whole coupled system. Validated by field data of Well C-1 in Shanxi, the model yields average relative errors of 8.76% for daily gas output and 2.92% for daily water output. Sensitivity analysis on Well C-2 indicates vertical reservoir stacking controls interlayer pressure difference, and commingled gas curves show dual peaks with shifting dominant gas sources over production stages. A 3.9% rise in deep coalbed methane gas content significantly boosts mid-term peak production and cumulative gas output, making reservoir gas content the dominant geological factor governing commingled production performance. A 120.0% increase in tight gas saturation only delivers a slight uplift in cumulative production under low-porosity conditions. Elevated reservoir stress sensitivity triggers a cumulative gas production reduction of over 50%. Cumulative gas output varies proportionally with hydraulic fracture length, while fracture network width brings mismatched production improvement due to pressure drawdown funnel effects. Therefore, hydraulic fracturing operations should prioritize extending artificial fractures to expand the drainage area of commingled wells. Schemes with constant bottomhole flowing pressure and constant gas rate exert marginal influences on ultimate cumulative production and can be flexibly switched on site. To stabilize daily gas deliverability throughout the early, middle and late production stages, a bottomhole pressure drawdown rate of 0.05 MPa/d or a fixed daily gas rate of 4000 m³/d is recommended. This work provides theoretical support for optimizing commingled development of superimposed tight gas and deep CBM reservoirs. Full article

The aim of this in vitro study is to evaluate the stress distribution of different definitive restorative materials designed with different connector dimensions using finite element analysis. Two adjacent prepared maxillary molars were designed digitally. Two-unit splinted fixed dental prostheses (FDPs) were designed with 4 different triangular connector dimensions (2 × 3, 3 × 3, 3 × 4, and 4 × 4 mm (width × length)). The tested materials are Gold Metal, Base Metal Alloy, Feldspathic Porcelain, Lithium Disilicate, Zirconia, and Zirconia-Reinforced Lithium Silicate. A total of 56 two-unit splinted crowns models were designed and evaluated using finite element analysis (FEA) in Autodesk Fusion 360. FEA demonstrated a non-linear relationship between connector size and performance, with the 3 × 4 mm design exhibiting optimal stress distribution and the highest safety factor. Among different materials, the base metal alloy showed the highest safety factor across all configurations, while zirconia and lithium disilicate performed comparably under static loading. The 3 × 4 mm connector demonstrated optimal performance across all tested materials. Base metal alloy exhibited the highest safety factor among all connector dimensions. Full article

Correlated electronic phenomena in magic-angle twisted bilayer graphene have garnered widespread research interest in two-dimensional materials science. As a powerful multiscale framework bridging atomic-scale resolution and mesoscopic structural evolution, the structural phase field crystal method has been widely adopted for graphene system studies. In this work, we develop a self-consistent XPFC model specifically for twisted bilayer graphene (tBLG) simulations. By globally optimizing the core free-energy functional parameters via a genetic algorithm, the proposed model achieves a marked improvement in consistency between the equilibrium density field and the first-principles generalized stacking fault energy surface. We further introduce a self-consistent dynamic interlayer interaction potential to replace the conventional fixed-substrate approximation, which captures the bidirectional coupling and mutual relaxation between adjacent graphene layers in a self-consistent manner. We calibrate the precise magnitude of the interlayer potential using the widths of stacking domain boundaries between distinct stacking configurations as a key metric, with the results benchmarked against atomistic simulation data. When applied to the 1.1° magic-angle tBLG system, the model uncovers spontaneous structural relaxation driven by interlayer van der Waals interactions: low-energy AB–BA stacking domains expand significantly, while high-energy AA domains shrink correspondingly. Full article

Branch prediction errors can reduce superscalar throughput by more than the error frequency alone suggests because a single misprediction can trigger redirect, squash, refetch, refill, and window recovery, which collectively disrupt sustained instruction-level parallelism. This paper presents a quantitative framework that relates prediction accuracy to realized parallelism loss in out-of-order superscalar processors. The framework separates prediction-error frequency, effective recovery cost, and unrealized issue capacity using prediction accuracy (Acc), misprediction rate (MR), effective branch penalty in cycles per misprediction (BP), parallelism loss ratio (PLR), the ratio-based branch sensitivity factor $BSF=PLR/MR$, and the slope-based branch sensitivity factor $\mathit{S-BSF}=\mathit{\partial }PLR/\mathit{\partial }MR$. BSF measures how strongly a particular processor configuration and workload convert prediction errors into lost issue capacity, whereas S-BSF provides a more stable sensitivity estimate when MR approaches zero. The framework is evaluated using timing-detailed gem5 O3 simulations on RV64GC workloads. The evaluation includes controlled branch microbenchmarks and six GAPBS graph workloads, allowing the proposed metrics to be examined under both mechanism-isolating and complex workload conditions. Two complementary controlled sweeps are used. At a fixed processor structure, predictor family and predictor level are varied to determine whether changing the predictor strengthens or weakens the relationship between MR and IPC/PLR. At a fixed predictor configuration, issue width and an effective front-end-depth proxy are varied to measure how the microarchitecture amplifies the performance cost of the remaining prediction errors. Thus, issue width is treated as an amplification variable for branch-prediction failures rather than as an independent performance topic. At the fixed structural point, Tournament and BiMode predictors show strong monotonic MR–PLR relationships on the high-branch benchmark, with Spearman coefficients of 1.00 and 0.98, whereas the Local predictor exhibits nearly unchanged MR but materially different IPC and PLR across levels. This demonstrates that the mapping from MR to throughput depends on predictor family and configuration rather than being invariant. In the controlled structural sweep, increasing issue width from 4 to 8 raises PLR by 37.6% and BSF by 55.0% on the high-branch benchmark, even though MR remains in the same order of magnitude. On GAPBS workloads, the lowest-MR configuration is not always the highest-IPC configuration, confirming that effective branch penalty and parallelism loss must be considered together with prediction frequency. These numerical findings are conditional on the evaluated single-thread gem5 DerivO3CPU model, RV64GC binaries, predictor implementations, memory hierarchy, and workload set. They characterize predictor–microarchitecture interactions in this controlled simulation environment and should not be interpreted as universal constants for all processors or applications. Full article

Implicit neural representations (INRs) encode video frames as network weights, offering a new compression paradigm. A persistent limitation is that existing INR codecs train one model per target bitrate, so multi-rate deployment needs separate runs, separate checkpoints, and model reloading, costs that grow with the number of rate points. We propose a Generalized Slimmable Framework that replaces standard layers with width-configurable counterparts in most INR decoders, letting a single checkpoint serve multiple bitrates through nested weight tensors without topology changes. To recover the quality lost in shared-weight training, we introduce Slimmable Conditional Decoder Modulation (SCDM), which blends slimmable expert convolutions via width- and frame-conditioned gating. For encoder-based backbones, encoder output caching separates encoder computation from multi-width training. Across four INR backbones on DAVIS and Bunny, the framework cuts multi-rate storage by about $2.3$–$2.5\times$, and SCDM recovers substantial quality at all rate points while surpassing independently trained fixed-width models at narrow widths. Full article

In this paper, an improved fixed-width histogram (IFWH) algorithm with multi-strategy enhancement is proposed for simulation-based AUV path planning in complex underwater environments. A multi-constraint optimization framework considering propulsion energy consumption, obstacle threats, terrain collision risks, and maneuverability constraints is established. Chaotic population initialization, adaptive global–local search transfer, quadratic interpolation, and spiral local refinement are integrated to enhance population diversity and trajectory smoothness. Numerical simulations are conducted under current-free terrains, overlapping seabed-current conditions, and environments with static and dynamic obstacles. Compared with A*, FWH, IPSO, and SVF-RRT*, IFWH reduces the average terrain slope by 43.91%, 47.24%, 44.94%, and 43.71%, respectively, and decreases estimated propulsion energy consumption by 35.29%, 37.38%, 24.66%, and 35.93% in current-free Scenario A. Under overlapping seabed-current conditions, IFWH achieves a 100% success rate over 30 independent trials, obtaining average slope angles of 15.58° and 18.73° with propulsion energy costs of 1163.57 J and 1116.99 J, respectively. In mixed environments, all trials are completed without collision, with average planning times of $1.674 0.700 \mathrm{s}$ and $0.692\pm 0.053 \mathrm{s}$ under following- and rotary-current conditions, respectively. Full article