Linear Loss Research Articles

Design and Application of a Resource Allocation Method for CAEVs Internet of Things Based on Swarm Intelligence Computing

The Internet of Things (IoT) faces significant challenges in the requirements of sensitive task latency, reasonable resource allocation and reliability for resource transactions. This paper introduces a novel method for road resource allocation in the IoT context of connected and autonomous electric vehicles (CAEVs). The proposed algorithm leverages the ant colony algorithm (ACA) to effectively allocate and coordinate road resources within groups of CAEVs. By considering the energy consumption and pheromone volatilization, the allocation and coordination process of road resources are optimized. To improve the linear packet loss of RED, we adopt the advanced ACA and CRED in the NS2 platform. The experimental results demonstrate that the proposed method outperforms the RED algorithm in packet loss rate and delay time, significantly enhancing system efficiency and performance. Furthermore, the combination of the CRED algorithm and ant colony algorithm successfully mitigates short-term congestion and identifies optimized paths with minimal delay.

Deep Transfer Learning-Based Multi-Modal Digital Twins for Enhancement and Diagnostic Analysis of Brain MRI Image.

it aims to adopt deep transfer learning combined with Digital Twins (DTs) in Magnetic Resonance Imaging (MRI) medical image enhancement. MRI image enhancement method based on metamaterial composite technology is proposed by analyzing the application status of DTs in medical direction and the principle of MRI imaging. On the basis of deep transfer learning, MRI super-resolution deep neural network structure is established. To address the problem that different medical imaging methods have advantages and disadvantages, a multi-mode medical image fusion algorithm based on adaptive decomposition is proposed and verified by experiments. the optimal Peak Signal to Noise Ratio (PSNR) of 34.11dB can be obtained by introducing modified linear element and loss function of deep transfer learning neural network structure. The Structural Similarity Coefficient (SSIM) is 85.24%. It indicates that the MRI truthfulness and sharpness obtained by adding composite metasurface are improved greatly. The proposed medical image fusion algorithm has the highest overall score in the subjective evaluation of the six groups of fusion image results. Group III had the highest score in Magnetic Resonance Imaging- Positron Emission Computed Tomography (MRI-PET) image fusion, with a score of 4.67, close to the full score of 5. As for the objective evaluation in group I of Magnetic Resonance Imaging- Single Photon Emission Computed Tomography (MRI-SPECT) images, the Root Mean Square Error (RMSE), Relative Average Spectral Error (RASE) and Spectral Angle Mapper (SAM) are the highest, which are 39.2075, 116.688, and 0.594, respectively. Mutual Information (MI) is 5.8822. the proposed algorithm has better performance than other algorithms in preserving spatial details of MRI images and color information direction of SPECT images, and the other five groups have achieved similar results.

MS-AGAN: Road Extraction via Multi-Scale Information Fusion and Asymmetric Generative Adversarial Networks from High-Resolution Remote Sensing Images under Complex Backgrounds

Extracting roads from remote sensing images is of significant importance for automatic road network updating, urban planning, and construction. However, various factors in complex scenes (e.g., high vegetation coverage occlusions) may lead to fragmentation in the extracted road networks and also affect the robustness of road extraction methods. This study proposes a multi-scale road extraction method with asymmetric generative adversarial learning (MS-AGAN). First, we design an asymmetric GAN with a multi-scale feature encoder to better utilize the context information in high-resolution remote sensing images (HRSIs). Atrous spatial pyramid pooling (ASPP) and feature fusion are integrated into the asymmetric encoder–decoder structure to avoid feature redundancy caused by multi-level cascading operations and enhance the generator network’s ability to extract fine-grained road information at the pixel level. Second, to maintain road connectivity, topologic features are considered in the pixel segmentation process. A linear structural similarity loss (LSSIM) is introduced into the loss function of MS-AGAN, which guides MS-AGAN to generate more accurate segmentation results. Finally, to fairly evaluate the performance of deep models under complex backgrounds, the Bayesian error rate (BER) is introduced into the field of road extraction for the first time. Experiments are conducted via Gaofen-2 (GF-2) high-resolution remote sensing images with high vegetation coverage in the Daxing District of Beijing, China, and the public DeepGlobe dataset. The performance of MS-AGAN is compared with a list of advanced models, including RCFSNet, CoANet, UNet, DeepLabV3+, and DiResNet. The final results show that (1) with respect to road extraction performance, the Recall, F1, and IoU values of MS-AGAN on the Daxing dataset are 2.17%, 0.04%, and 2.63% higher than the baselines. On DeepGlobe, the Recall, F1, and IoU of MS-AGAN improve by 1.12%, 0.42%, and 0.25%, respectively. (2) On road connectivity, the Conn index of MS-AGAN from the Daxing dataset is 46.39%, with an improvement of 0.62% over the baselines, and the Conn index of MS-AGAN on DeepGlobe is 70.08%, holding an improvement of 1.73% over CoANet. The quantitative and qualitative analyses both demonstrate the superiority of MS-AGAN in preserving road connectivity. (3) In particular, the BER of MS-AGAN is 20.86% over the Daxing dataset with a 0.22% decrease compared to the best baselines and 11.77% on DeepGlobe with a 0.85% decrease compared to the best baselines. The proposed MS-AGAN provides an efficient, cost-effective, and reliable method for the dynamic updating of road networks via HRSIs.

Multiplication of distributions in a linear gain and loss system

We consider a model of coupled oscillators which can be seen as a gain and loss system. In the attempt to quantize the system, we propose a new definition of multiplication between distributions, and we check that this definition can be adopted when checking the biorthonormality of the eigenstates of the Hamiltonian H of the system, and of its adjoint H^dagger . In the analysis carried out here, the role of weak pseudo-bosonic ladder operators is relevant.

A novel method based on composite effects for evaluating the hydrogen embrittlement of steels with low hydrogen diffusion coefficients

The effect of hydrogen on mechanical properties of a twinning-induced plasticity austenitic steel was investigated by slow strain rate tensile tests and scanning electron microscopy after various hydrogen pre-charging conditions. A new method for evaluating hydrogen embrittlement of materials with low hydrogen diffusion coefficient has been proposed. Materials with low hydrogen diffusion coefficients can be regarded as composite materials after pre-charging, i.e., a hydrogen-rich brittle region and a hydrogen-lean ductile region. Based on the rule of mixtures, the influence of the hydrogen on the mechanical properties can be reflected by the contribution of the brittle zone to the overall mechanical properties, which is more realistic and universal compared to the characterization of the mechanical property loss by hydrogen content. This helps to simplify the selection of materials resistant to hydrogen embrittlement by directly comparison linear loss of mechanical properties when the “average” hydrogen content of the brittle region is similar.

Analysis of electro-optically adjustable cascaded second-order nonlinearity in tapered BBO crystal: a compression scheme for ultra-short pulse

In this analytical approach, electro-optically tunable second-order cascaded nonlinearity was targeted to investigate the potential of ultrashort pulse compression in a tapering nonlinear medium. The proposed framework is ideally suited to generating high-intensity pulses with small pulse widths by exploiting second-harmonic generation and the electro-optic effect in a bulk beta-barium borate with exceptional optical advantages. Considering both linear and nonlinear absorption losses, the necessary and sufficient conditions for the compression of ultrashort pulses were developed using the generalized nonlinear Schrödinger equation. In agreement with simulations, an attempt is made to compress an optical pulse from 120 to 39 fs using an external voltage of ∓5.69 KV, which leads to a phase mismatch ( Δk ) = ± 124.8 m − 1, a phase shift ( ΔϕNL ) = ± 1.26π, and an effective cascaded refractive index (n2cascade)=±3.371×10−20 m2/W. The results suggest that the technology developed in this study will open the door to a plethora of applications, including fields as diverse as laser surgery, range finding through LIDAR, and many more.

Analysis of Core Loss Characteristics of Linear Phase-Shifting Transformer

Linear phase-shifting transformer, as a new type of phase-shifting transformer, has the advantages of shifting phase at any angle, good expansibility, and easy modularization compared with the traditional core column phase-shifting transformer. To calculate the output performance such as the efficiency of linear phase-shifting transformer, the loss of linear phase-shifting transformer should be studied. The loss of linear phase-shifting transformer includes copper loss and core loss. Among them, the core loss has an important impact on linear phase-shifting transformer performance parameters such as efficiency and temperature rise, but there is a lack of relevant research at present. In this paper, based on the traditional separation model of ferromagnetic materials, a calculation method for linear phase-shifting transformer core loss is proposed. In this method, the loss coefficient of the linear phase-shifting transformer iron loss model is calculated by the least square method based on the calculation and analysis of the magnetic field law of the core by the time-step finite element method, and the loss coefficient is further modified by considering the influence of local hysteresis loop, non-sinusoidal magnetic field, and harmonic magnetic field. The linear phase-shifting transformer model based on finite element field-road coupling simulation is established, a low-power experimental prototype is designed, and a multi-stack inverter system platform is built. The theoretical calculation is verified by simulation and experiment. Simulation and experimental results demonstrate the accuracy of the core loss calculation method presented in this paper.

Classical and Bayesian Inference for the Kavya–Manoharan Generalized Exponential Distribution under Generalized Progressively Hybrid Censored Data

This manuscript focuses on the statistical inference of the Kavya–Manoharan generalized exponential distribution under the generalized type-I progressive hybrid censoring sample (GTI-PHCS). Different classical approaches of estimation, such as maximum likelihood, the maximum product of spacing, least squares (LS), weighted LS, and percentiles under GTI-PHCS, are investigated. Based on the squared error and linear exponential loss functions, the Bayes estimates for the unknown parameters utilizing separate gamma priors under GTI-PHCS have been derived. Point and interval estimates of unknown parameters are developed. We carry out a simulation using the Monte Carlo algorithm to show the performance of the inferential procedures. Finally, real-world data collection is examined for illustration purposes.

Use of waste husk from millet grain cultivation in the production of fired clay bricks

AbstractThe consumption of colossal quantities of materials in the building industry has advanced the swift depletion of clean clay reserves. The use of organic additives in brick production is conserving clay resources. In addition, in some cases, it can lead to improvements in some material properties, such as decreasing thermal conductivity and increasing the capacity of the ceramic material in terms of thermal insulation. In the present investigation, waste millet husk (WMH) was incorporated in different proportions to clays to ascertain its influence on the fired brick properties. The raw materials were characterized for their physical, chemical, and thermal properties and found suitable for use in fired brick production. Additionally, the prepared modeled brick samples were tested for their physico‐mechanical properties. The results indicated that linear shrinkage and weight loss increased, whereas bulk density decreased from 2.06 to 1.58 g/cm3 depending on WMH incorporation amount in the clays and firing temperature. Similarly, compressive strength reduced by up to 68%. Thermal conductivity beneficially reduced by 42% with the addition of 16 wt.% of WMH. The best results in terms of mechanical properties were obtained with 4 wt.% of the WMH. In terms of thermal insulation, the best results were exhibited in the samples admixed with 16 wt.% of WMH. The results showed that porosity and bulk density were critical determining factors that directly influence the bricks physico‐mechanical properties.

Nonlinearity and lasing topological zero-mode in distorted photonic lattice

Recently we have witnessed experimental realization of a Majorana zero-mode bound at vortex distortion induced in bipartite hexagonal photonic lattices. Here, we address an open question of the impact of nonlinearity on the zero-mode dynamics by theoretically investigating the abilities of topologically protected zero-modes to guide, couple and lase light in the presence of nonlinear effects. Light-intensity related nonlinearity enters the scene through a local nonlinear lattice response and driving properties: saturable nonlinear gain and linear loss. We demonstrate an efficient steady zero-mode lasing regime by managing the lattice and driving parameters. Obtained results open up possibilities for design of new topological lasers in length-scalable photonic platforms, such as multicore optical fibers.

Quantum Langevin theory for two coupled phase-conjugated electromagnetic waves

While loss-gain-induced Langevin noises have been intensively studied in quantum optics, the effect of a complex-valued nonlinear coupling coefficient on the noises of two coupled phase-conjugated optical fields has never been questioned before. Here, we provide a general macroscopic phenomenological formula of quantum Langevin equations for two coupled phase-conjugated fields with linear loss (gain) and complex nonlinear coupling coefficient. The macroscopic phenomenological formula is obtained from the coupling matrix to preserve the field commutation relations and correlations, which does not require knowing the microscopic details of light-matter interaction and internal atomic structures. To validate this phenomenological formula, we take spontaneous four-wave mixing in a double-$\Lambda$ four-level atomic system as an example to numerically confirm that our macroscopic phenomenological result is consistent with that obtained from the microscopic Heisenberg-Langevin theory. Finally, we apply the quantum Langevin equations to study the effects of linear gain and loss, complex phase mismatching, as well as complex nonlinear coupling coefficient in entangled photon pair (biphoton) generation, particularly to their temporal quantum correlations.

Doubly Type II Censoring of Two Stress-Strength System Reliability Estimation for Generalized Exponential-Poisson Distribution

In this paper, a Bayesian analysis is made to estimate the Reliability of two stress-strength model systems. First: the reliability of a one component strengths X under stress Y. Second, reliability of one component strength under three stresses. Where X and Y are independent generalized exponential-Poison random variables with parameters (α,λ,θ) and (β,λ,θ) . The analysis is concerned with and based on doubly type II censored samples using gamma prior under four different loss functions, namely quadratic loss function, weighted loss functions, linear and non-linear exponential loss function. The estimators are compared by mean squared error criteria due to a simulation study. We also find that the mean square error is the best performance of the estimator from that found in quadratic, weighted, linear and non-linear exponential loss functions.

Deep Classification with Linearity-Enhanced Logits to Softmax Function.

Recently, there has been a rapid increase in deep classification tasks, such as image recognition and target detection. As one of the most crucial components in Convolutional Neural Network (CNN) architectures, softmax arguably encourages CNN to achieve better performance in image recognition. Under this scheme, we present a conceptually intuitive learning objection function: Orthogonal-Softmax. The primary property of the loss function is to use a linear approximation model that is designed by Gram-Schmidt orthogonalization. Firstly, compared with the traditional softmax and Taylor-Softmax, Orthogonal-Softmax has a stronger relationship through orthogonal polynomials expansion. Secondly, a new loss function is advanced to acquire highly discriminative features for classification tasks. At last, we present a linear softmax loss to further promote the intra-class compactness and inter-class discrepancy simultaneously. The results of the widespread experimental discussion on four benchmark datasets manifest the validity of the presented method. Besides, we want to explore the non-ground truth samples in the future.

Ceramics Properties of Indurated-Shale Quarry Wastes from Abakaliki, Southeastern Nigeria: Application as Raw Materials in Roofing-Tile Production

AbstractThe present study describes research carried out to evaluate the mineralogical, geochemical and technological properties of indurated shale-quarry wastes and assess the suitability of these low-cost and locally available quarry wastes generated from crushed indurated shales for possible use as alternatives to fresh raw materials in the manufacture of roofing-tile products. Firstly, the mineralogical and chemical properties of the indurated shales were investigated by X-ray diffraction (XRD) and X-ray fluorescence, while their physical properties were identified by grain-size distribution, Atterberg limits, and clay activity. Samples of indurated shale-quarry wastes (ISQWs) were subjected to heat treatment at elevated firing temperatures to provide the required strength and durability and their ceramics properties (linear shrinkage, weight loss, water absorption, bulk density, and flexural strength) were determined. From the results, the ISQWs were composed predominantly of fine particles with medium plasticity and clay activity with values generally >0.75. The mineralogy revealed a predominance of aluminosilicates (illite-kaolinite-smectite-chlorite) with large quartz contents and variable percentages of carbonate and feldspar. The oxides were dominated by SiO2 and Al2O3, small amounts of ferromagnesian minerals, and considerable amounts of alkalis (K2O and Na2O) which act as fluxes. The CaO concentrations were variable and related to carbonate contents. Characterizations based on compositional ternary (total clay mineral-carbonate-quartz + feldspar) systems, Casagrande clay workability charts, and Winkler and McNally diagrams revealed their suitability for ceramics applications as the majority of ISQW samples fell within the specifications for roofing tiles. The ISQWs fired at a high temperature of 1000°C revealed considerable weight loss, reduction in both linear shrinkage and water absorption with insignificant increase in flexural strength. In order to achieve excellent ceramics properties and further reduce sintering temperature for their suitability as raw materials in the production of roofing tiles, beneficiations of ISQWs are highly recommended.

Surface Evolution of Vermicular Cast Iron in High Frequent Cyclic Plasma and Different Facial Cooling Airflows

The surface evolution of vermicular cast iron in a high frequent cyclic plasma and facial cooling airflow was studied to understand the behavior and mechanism in different cooling conditions under a unique thermal shock environment. Results indicated that both the mass and linear loss presented titled inverted V-shaped relationships with the flux of the cooling airflow, while the change in roughness decreased continuously. As the cooling airflow rose, the eroded zone was reduced, the iron oxides lessened, and fluctuation of the surface temperature weakened. In combination with the thermodynamic calculations and thermal analysis, it was confirmed that the oxidation and mechanical erosion had contrary tendencies with the rising flux in the facial cooling airflow. The transformation of the dominant factor from oxidation to peeling off by thermal stress and scouring resulted in the evolution of mass and thickness. The surface oxides dominated the change in the roughness.

Statistical inference with joint progressive censoring for two populations using power Rayleigh lifetime distribution

In this study, point and interval estimations for the power Rayleigh distribution are derived using the joint progressive type-II censoring technique. The maximum likelihood and Bayes methods are used to estimate the two distributional parameters. The estimators’ approximate credible intervals and confidence intervals have also been determined. The Markov chain Monte Carlo (MCMC) method is used to provide the findings of Bayes estimators for squared error loss and linear exponential loss functions. The Metropolis–Hasting technique uses Gibbs to generate MCMC samples from the posterior density functions. A real data set is used to show off the suggested approaches. Finally, in order to compare the results of various approaches, a simulation study is performed.

Witnessing entangled two-photon absorption via quantum interferometry

Recent investigations have suggested that the use of non-classical states of light, such as entangled photon pairs, may open new and exciting avenues in experimental two-photon absorption spectroscopy. Despite several experimental studies of entangled two-photon absorption (eTPA), there is still a heated debate on whether eTPA has truly been observed. This interesting debate has arisen mainly because it has recently been argued that single-photon-loss mechanisms, such as scattering or hot-band absorption, may mimic the expected entangled-photon linear absorption behavior. In this work, we focus on transmission measurements of eTPA and explore three different two-photon quantum interferometers in the context of assessing eTPA. We demonstrate that the so-called N00N-state configuration is the only one among those considered insensitive to linear (single-photon) losses. Remarkably, our results show that N00N states may become a potentially powerful tool for quantum spectroscopy, placing them as a strong candidate for the certification of eTPA in an arbitrary sample.

Linear viscoelastic response of the vertex model with internal and external dissipation: Normal modes analysis

We use the normal mode formalism to study the shear rheology of the vertex model for epithelial tissue mechanics in the overdamped linear response regime. We consider systems with external (e.g., cell-substrate) and internal (e.g., cell-cell) dissipation mechanisms, and derive expressions for stresses on cells due to mechanical and dissipative forces. The semi-analytical method developed here is, however, general and can be directly applied to study the linear response of a broad class of soft matter systems with internal and external dissipation. It involves normal mode decomposition to calculate linear loss and storage moduli of the system. Specifically, displacements along each normal mode produce stresses due to elastic deformation and internal dissipation, which are in force balance with loads due to external dissipation. Each normal mode responds with a characteristic relaxation timescale, and its rheological behavior can be described as a combination of a standard linear solid element due to elastic stresses and a Jeffreys model element due to the internal dissipative stresses. The total response of the system is then fully determined by connecting in parallel all the viscoelastic elements corresponding to individual normal modes. This allows full characterization of the potentially complex linear rheological response of the system at all driving frequencies and identification of collective excitations. We show that internal and external dissipation mechanisms lead to qualitatively different rheological behaviors due to the presence or absence of Jeffreys elements, which is particularly pronounced at high driving frequencies. Our findings, therefore, underscore the importance of microscopic dissipation mechanisms in understanding the rheological behavior of soft materials and tissues, in particular.

Role of cementite morphology on corrosion layer formation of high-strength carbon steels in sweet and sour environments

The effect of cementite morphology on the corrosion layer formation of four high-strength carbon steels was studied in an aqueous solution containing CO2 and CO2/H2S. The linear polarization resistance and weight loss data reveal that as the cementite phase fraction is increased, the corrosion rate increases in CO2 environment, while no trend is observed in the CO2/H2S environment. The results indicate that a porous and, non protective corrosion layer forms in the CO2 environment, whereas a protective layer forms in the CO2/H2S environment. A mechanism that explains the role of cementite morphology on corrosion layer formation in a CO2 environment is proposed for the studied materials.

Valorization potential of coffee grounds waste as a renewable pore-forming agent to produce low-cost porous ceramic support

Every day expressive amounts of coffee grounds waste generated during making the coffee beverage are produced worldwide. The aim of this work was to investigate the valorization potential of the coffee grounds waste as an alternative pore-forming agent to produce porous kaolin-based ceramic supports. For this purpose, kaolin-based ceramic support formulations containing up to 40 mass % of coffee grounds waste were pressed and fired at temperatures ranging from 1000 to 1200 ºC. The sintering behavior and technical properties (linear shrinkage, mass loss, apparent density, mechanical strength, and apparent porosity) have been investigated. The microstructural evolution has been accompanied by scanning electron microscopy (SEM) and 3D-confocal microscopy. The obtained results demonstrated that the coffee grounds waste could serve as a very effective pore-forming agent to produce kaolin-based ceramic support with highly porous structures. Such ceramic supports incorporated with coffee grounds waste exhibited values of apparent porosity within the range of 41.87 % to 70.96 %. This results suggests that the coffee grounds waste, in the range of 10 - 40 mass %, could be a highly promising renewable porogenic material to be valorized to produce low-cost kaolin-based ceramic support with good porosity properties. This new approach could be an innovative alternative for the sustainable use of coffee grounds waste.