This paper looks at this intriguing question: are single images with their details lost during deraining, reversible to artifact-free status? We propose an end-to-end detail-recovery image deraining network (termed a DRDNet) solve the problem. Unlike existing approaches that attempt meet conflicting goal of simultaneously and preserving in unified framework, we view rain removal detail recovery as two seperate tasks, so each part could specialize rather than trade-off between goals....

Image smoothing is a prerequisite for many computer vision and graphics applications. In this article, we raise an intriguing question whether dataset that semantically describes meaningful structures unimportant details can facilitate deep learning model to smooth complex natural images. To answer it, generate ground-truth labels from easy samples by candidate generation screening test synthesize hard in structure-preserving blending intricate multifarious with the labels. take full...

Based on the CO2-WAG (water-alternating-gas) flooding for conventional reservoirs, huff-n-puff in shale reservoirs is proposed. To clarify phase behavior and fluid flow of oil–CO2–water process, a series experimental studies are conducted under different injection sequences CO2 water. The results show that saturation pressure systems lower than oil–CO2 since portion dissolved In addition, followed by water can significantly reduce dissolution preferentially into macropores bedding fractures...

Abstract Industry competitiveness depends on the cost, performance, and timely delivery of product. Thus, an accurate, rapid, robust product cost estimation model for entire life cycle is essential. This research applies two machine learning methods – back-propagation neural networks (BPNs) least squares support vector machines (LS-SVMs) to solve problems. The performance a number models, statistical regression analyses, BPNs LS-SVMs, are compared in terms their performance. results reveal...

Cryptographic implementations bolster security against timing side-channel attacks by integrating constant-time components. However, the new ciphertext side channels resulting from deterministic memory encryption in Trusted Execution Environments (TEEs), enable ciphertexts to manifest identifiable patterns when being sequentially written same address. Attackers with read access encrypted TEEs can potentially deduce plaintexts analyzing these changing patterns. In this paper, we design...

Abstract In this study, we propose a novel model to predict Al2O3 film conformality in different aspect ratio trench structures under various process conditions. This is grounded on two-dimensional diffusion-reaction equation integrated with the distance regularized level set evolution method based edge active contour. The simulation results demonstrate that increasing gas pressure, pulse time, and initial sticking probability of precursor co-reactant molecules can enhance during deposition...

Abstract Analogous to the technique CO2 huff-n-puff, it has been determined that preliminary injection of a predetermined volume supercritical CO2, serving as pre-fracturing fluid, holds significant promise in augmenting EOR and facilitate carbon storage from shale oil reservoirs when applied prior hydraulic fracturing procedures. However, regardless whether it's pre-CO2 energized or post-hydraulic coexistence oil-CO2-water leads complex phase behavior flow characteristics. To this end,...

This paper presents the first critical analysis of building highly secure, performant, and confidential Byzantine fault-tolerant (BFT) consensus by integrating off-the-shelf crash (CFT) protocols with trusted execution environments (TEEs). TEEs, like Intel SGX, are CPU extensions that offer applications a secure environment strong integrity confidentiality guarantees, leveraging techniques hardware-assisted isolation, memory encryption, remote attestation. It has been speculated when...

Impulse components in vibration signals are important fault features of complex machines. Sparse coding (SC) algorithm has been introduced as an impulse feature extraction method, but it could not guarantee a satisfactory performance processing with heavy background noises. In this paper, method based on fusion sparse (FSC) and online dictionary learning is proposed to extract impulses efficiently. Firstly, scheme different algorithms presented ensure higher reconstruction accuracy. Then,...

Image deraining is a fundamental, yet not well-solved problem in computer vision and graphics. The traditional image approaches commonly behave ineffectively medium heavy rain removal, while the learning-based ones lead to degradations such as loss of details, halo artifacts and/or color distortion. Unlike existing that lack detail-recovery mechanism, we propose an end-to-end network (termed DRD-Net) for single images. We first time introduce two sub-networks with comprehensive function...

This article employs the continuous-time analog Hopfield neural network (CHNN) to compute temperature distribution in nonlinear heat conduction problems. The relationship between CHNN synaptic connection weights and governing equations of problems is established a corresponding connectivity circuit design scheme proposed. algorithm used solve equation for with power-law nonlinearity. results confirm that proposed provides an accurate means solving transient distributions on real-time basis.

Kaplan turbines are generally used in working conditions with a high flow and low head. These type of axial-flow hydro turbine that can adjust the opening guide vanes blades simultaneously order to achieve higher efficiency under wider range loads. Different combinations (cam relationship) will lead changes unit as well its vibration characteristics. A bad cam relationship cause or unstable operation turbine. In this study, relative large-scale 200 MW output were tested different vane blade...

Semi-supervised learning (SSL) is a powerful tool to address the challenge of insufficient annotated data in medical segmentation problems. However, existing semi-supervised methods mainly rely on internal knowledge for pseudo labeling, which biased due distribution mismatch between highly imbalanced labeled and unlabeled data. Segmenting left atrial appendage (LAA) from transesophageal echocardiogram (TEE) images typical image task featured by scarcity professional annotations diverse...

DRT is a customized public transport system with precisely matching of supply and demand efficient utilization supply. In this paper, the digital twin model introduced to construct individual trip chain bus operation respectively, as well realize calculation feedback whole process service. addition, paper also carries out equivalent solution for key link service, transit between stations, which ensures accuracy model. Finally, through case analysis, it verified that service plays an...

Rain severely hampers the visibility of scene objects when images are captured through glass in heavily rainy days. We observe three intriguing phenomenons that, 1) rain is a mixture raindrops, streaks and haze; 2) depth from camera determines degrees object visibility, where nearby faraway visually blocked by haze, respectively; 3) raindrops on randomly affect whole image space. for first time consider overall determined (MOR). However, existing solutions established datasets lack full...