Multilevel carbon architecture of subnanoscopic silicon for fast‐charging high‐energy‐density lithium‐ion batteries

Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.

Mechanical response and microscopic damage mechanism of pre-flawed sandstone subjected to monotonic and multilevel cyclic loading:A laboratory-scale investigation

This study aims to investigate the mechanical response and acoustic emission(AE)characteristic of pre-flawed sandstone under both monotonic and multilevel constant-amplitude cyclic loads.Specifically,we explored how coplanar flaw angle and load type impact the strength and deformation behavior and microscopic damage mechanism.Results indicated that being fluctuated before rising with increasing fissure angle under monotonic loading,the peak strength of the specimen first increased slowly and then steeply under cyclic loading.The effect of multilevel cyclic loading on the mechanical parameters was more significant.For a single fatigue stage,the specimen underwent greater deformation in early cycles,which subsequently stabilized.Similar variation pattern was also reflected by AE count/energy/b-value.Crack behaviors were dominated by the fissure angle and load type and medium-scale crack accounted for 74.83%–86.44%of total crack.Compared with monotonic loading,crack distribution of specimen under cyclic loading was more complicated.Meanwhile,a simple model was proposed to describe the damage evolution of sandstone under cyclic loading.Finally,SEM images revealed that the microstructures at the fracture were mainly composed of intergranular fracture,and percentage of transgranular fracture jumped under cyclic loading due to the rapid release of elastic energy caused by high loading rate.

Enforcing a Source-end Cooperative Multilevel Defense Mechanism to Counter Flooding Attack

The exponential advancement in telecommunication embeds the Internet in every aspect of communication.Interconnections of networks all over the world impose monumental risks on the Internet.A Flooding Attack(FA)is one of the major intimidating risks on the Internet where legitimate users are prevented from accessing network services.Irrespective of the protective measures incorporated in the communication infrastructure,FA still persists due to the lack of global cooperation.Most of the existing mitigation is set up either at the traffic starting point or at the traffic ending point.Providing mitigation at one or the other end may not be a complete solution.To insist on better protection againstflooding attacks,this work proposes a cooperative multilevel defense mechanism.The proposed cooperative multilevel defense mechanism consists of two-level of mitigation.In thefirst level,it is proposed to design a Threshold-based rate-limiting with a Spoofing Resistant Tag(TSRT),as a source end countermeasure for High-Rate Flooding Attacks(HRFA)and spoofing attacks.In the second level,the accent is to discriminate normal traffic after Distributed Denial of Service(DDoS)traffic and drop the DDoS traffic at the destination end.Flow Congruence-based Selective Pushback(FCSP),as a destination-initiated countermeasure for the Low Rate Flooding Attack(LRFA).The source and the destination cooperate to identify and block the attack.A key advantage of this cooperative mechanism is that it can distinguish and channel down the attack traffic nearer to the starting point of the attack.The presentation of the agreeable cooperative multilevel safeguard mechanism is approved through broad recreation in NS-2.The investigation and the exploratory outcomes show that the proposed plan can effectively identify and shield from the attack.

Salp Swarm Algorithm with Multilevel Thresholding Based Brain Tumor Segmentation Model

Biomedical image processing acts as an essential part of severalmedical applications in supporting computer aided disease diagnosis. MagneticResonance Image (MRI) is a commonly utilized imaging tool used tosave glioma for clinical examination. Biomedical image segmentation plays avital role in healthcare decision making process which also helps to identifythe affected regions in the MRI. Though numerous segmentation models areavailable in the literature, it is still needed to develop effective segmentationmodels for BT. This study develops a salp swarm algorithm with multi-levelthresholding based brain tumor segmentation (SSAMLT-BTS) model. Thepresented SSAMLT-BTS model initially employs bilateral filtering based onnoise removal and skull stripping as a pre-processing phase. In addition,Otsu thresholding approach is applied to segment the biomedical imagesand the optimum threshold values are chosen by the use of SSA. Finally,active contour (AC) technique is used to identify the suspicious regions in themedical image. A comprehensive experimental analysis of the SSAMLT-BTSmodel is performed using benchmark dataset and the outcomes are inspectedin many aspects. The simulation outcomes reported the improved outcomesof the SSAMLT-BTS model over recent approaches with maximum accuracyof 95.95%.

A Multilevel Hierarchical Parallel Algorithm for Large-Scale Finite Element Modal Analysis

The strict and high-standard requirements for the safety and stability ofmajor engineering systems make it a tough challenge for large-scale finite element modal analysis.At the same time,realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice.This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis.Based on two-level partitioning and four-transformation strategies,the proposed algorithm not only improves the memory access rate through the sparsely distributed storage of a large amount of data but also reduces the solution time by reducing the scale of the generalized characteristic equation(GCEs).Moreover,a multilevel hierarchical parallelization approach is introduced during the computational procedure to enable the separation of the communication of inter-nodes,intra-nodes,heterogeneous core groups(HCGs),and inside HCGs through mapping computing tasks to various hardware layers.This method can efficiently achieve load balancing at different layers and significantly improve the communication rate through hierarchical communication.Therefore,it can enhance the efficiency of parallel computing of large-scale finite element modal analysis by fully exploiting the architecture characteristics of heterogeneous multicore clusters.Finally,typical numerical experiments were used to validate the correctness and efficiency of the proposedmethod.Then a parallel modal analysis example of the cross-river tunnel with over ten million degrees of freedom(DOFs)was performed,and ten-thousand core processors were applied to verify the feasibility of the algorithm.

A Sensor-less Surface Mounted PMSM for Electronic Speed Control in Multilevel Inverter

Recent advancements in power electronics technology evolves inverter fed electric motors.Speed signals and rotor position are essential for controlling an electric motor accurately.In this paper,the sensorless speed control of surface-mounted permanent magnet synchronous motor(SPMSM)has been attempted.SPMSM wants a digital inverter for its precise working.Hence,this study incor-poratesfifteen level inverter to the SPMSM.A sliding mode observer(SMO)based sensorless speed control scheme is projected to determine rotor spot and speed of the multilevel inverter(MLI)fed SPMSM.MLI has been operated using a multi carrier pulse width modulation(MCPWM)strategy for generation offif-teen level voltages.The simulation works are executed with MATLAB/SIMU-LINK software.The steadiness and the heftiness of the projected model have been investigated under no loaded and loaded situations of SPMSM.Furthermore,the projected method can be adapted for electric vehicles.

Multilevel optoelectronic hybrid memory based on N-doped Ge_(2)Sb_(2)Te_(5)film with low resistance drift and ultrafast speed

Multilevel phase-change memory is an attractive technology to increase storage capacity and density owing to its high-speed,scalable and non-volatile characteristics.However,the contradiction between thermal stability and operation speed is one of key factors to restrain the development of phase-change memory.Here,N-doped Ge_(2)Sb_(2)Te_(5)-based optoelectronic hybrid memory is proposed to simultaneously implement high thermal stability and ultrafast operation speed.The picosecond laser is adopted to write/erase information based on reversible phase transition characteristics whereas the resistance is detected to perform information readout.Results show that when N content is 27.4 at.%,N-doped Ge_(2)Sb_(2)Te_(5)film possesses high ten-year data retention temperature of 175℃and low resistance drift coefficient of 0.00024 at 85℃,0.00170 at 120℃,and 0.00249 at 150℃,respectively,owing to the formation of Ge–N,Sb–N,and Te–N bonds.The SET/RESET operation speeds of the film reach 520 ps/13 ps.In parallel,the reversible switching cycle of the corresponding device is realized with the resistance ratio of three orders of magnitude.Four-level reversible resistance states induced by various crystallization degrees are also obtained together with low resistance drift coefficients.Therefore,the N-doped Ge_(2)Sb_(2)Te_(5)thin film is a promising phase-change material for ultrafast multilevel optoelectronic hybrid storage.

基于Multilevel CodingTree模型的公路数字化档案标识编码研究

针对高速公路信息化建设中的编码问题,文章提出了基于Multilevel Coding Tree模型的"项目代号+属性+类别+流水号"四段位编码方案。根据该编码的结构,采用概率分析、实验测试和命题证明等手段,验证了编码的唯一性。该编码方案为公路信息化建设中各类文件提供了唯一的编码,达到一页(件)一码,是一种行之有效的编码方案。

Minimization of Switching Devices and Driver Circuits in Multilevel Inverter

The various configurations of multilevel inverter involve the use of more numbers of switching devices, energy storage devices and/or unidirectional devices. Each switching unit necessitates the add-on driver circuit for proper functionality. Cascaded H-Bridge Multilevel Inverter requires overlapped switching pulses for the switching devices in positive and negative arms of the bridge which may lead to short circuit during the device failure. This work addresses the problems in different configurations of multilevel inverter by using reduced number of switching and energy storage devices and driver circuits. In the present approach Single Switch is used for each stair case positive output and single H-Bridge for phase reversal. Driver circuits are reduced by using the property of body diode of the MOSFET. Switching pulses are generated by Arduino Development Board. The circuit is simulated using Matlab. More so, through experimental means, it is physically tested and results are analyzed for the 5-step inverter and thereby simulation is fully validated. Consequently, cycloconverter operation of the circuit is simulated using Matlab. Moreover, half bridge configuration of the multilevel inverter is also analyzed for high frequency induction heating applications.

Capacitor Pattern H-Bridge Multilevel Inverter (CPHMLI) Using Phase Diposition Pulse Width Modulation for Grid Applications

This work presents an implementation of an innovative single phase multilevel inverter using capacitors with reduced switches. The proposed Capacitor pattern H-bridge Multilevel Inverter (CPHMLI) topology consists of a proper number of Capacitor connected with switches and power sources. The advanced switching control supplied by Pulse Width Modulation (PDPWM) to attain mixed staircase switching state. The charging and discharging mode are achieved by calculating the voltage error at the load. Furthermore, to accomplish the higher voltage levels at the output with less number of semiconductors switches and simple commutation designed using CPHMLI topology. To prove the performance and effectiveness of the proposed approach, a set of experiments performed under various load conditions using MATLAB tool.

Human induced dryland degradation in Ordos Plateau,China,revealed by multilevel statistical modeling of normalized difference vegetation index and rainfall time-series

Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference vegetation index （NDVI） from remotely-sensed imagery, dividing human-induced land degradation from vegetation dynamics due to climate change is not a trivial task. This paper presented a multilevel statistical modeling of the NDVI-rainfall relationship to detect human-induced land degradation at local and landscape scales in the Ordos Plateau of Inner Mongolia, China, and recognized that anthropogenic activities result in either positive （land restoration and re-vegetation） or negative （degradation） trends. Linear regressions were used to assess the accuracy of the multi- level statistical model. The results show that： （1） land restoration was the dominant process in the Ordos Plateau between 1998 and 2012; （2） the effect of the statistical removal of precipitation revealed areas of human-induced land degradation and improvement, the latter reflecting successful restoration projects and changes in land man- agement in many parts of the Ordos; （3） compared to a simple linear regression, multilevel statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. Additional factors should be included when analyzing the NDVI-rainfall relationship and detecting human-induced loss of vegetation cover in drylands to improve the accuracy of the approach and elimi- nate some observed non-significant residual trends.

Improvement and performance of parallel multilevel fast multipole algorithm

The method of establishing data structures plays an important role in the efficiency of parallel multilevel fast multipole algorithm（PMLFMA）.Considering the main complements of multilevel fast multipole algorithm（MLFMA） memory,a new parallelization strategy and a modified data octree construction scheme are proposed to further reduce communication in order to improve parallel efficiency.For far interaction,a new scheme called dynamic memory allocation is developed.To analyze the workload balancing performance of a parallel implementation,the original concept of workload balancing factor is introduced and verified by numerical examples.Numerical results show that the above measures improve the parallel efficiency and are suitable for the analysis of electrical large-scale scattering objects.

A Context Sensitive Multilevel Thresholding Using Swarm Based Algorithms

In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images.

A multilevel preconditioner and its shared memory implementation for a new generation reservoir simulator

As a result of the interplay between advances in computer hardware, software, and algorithm, we are now in a new era of large-scale reservoir simulation, which focuses on accurate flow description, fine reservoir characterization, efficient nonlinear/linear solvers, and parallel implementation. In this paper, we discuss a multilevel preconditioner in a new-generation simulator and its implementation on multicore computers. This preconditioner relies on the method of subspace corrections to solve large-scale linear systems arising from fully implicit methods in reservoir simulations. We investigate the parallel efficiency and robustness of the proposed method by applying it to million-cell benchmark problems.

A novel analytical thermal model for multilevel nano-scale interconnects considering the via effect

Based on the heat diffusion equation of multilevel interconnects, a novel analytical thermal model for multilevel nano-scale interconnects considering the via effect is presented, which can compute quickly the temperature of multilevel interconnects, with substrate temperature given. Based on the proposed model and the 65 nm complementary metal oxide semiconductor （CMOS） process parameter, the temperature of nano-scale interconnects is computed. The computed results show that the via effect has a great effect on local interconnects, but the reduction of thermal conductivity has little effect on local interconnects. With the reduction of thermal conductivity or the increase of current density, however, the temperature of global interconnects rises greatly, which can result in a great deterioration in their performance. The proposed model can be applied to computer aided design （CAD） of very large-scale integrated circuits （VLSIs） in nano-scale technologies.

Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch

Multilevel feature moving average ratio method is proposed to realize an open-switch fault diagnosis for any switch of the microgrid inverter. The main steps of the proposed method include multilevel signal decomposition, coefficient reconstruction, absolute average ratio process and artificial neural network(ANN) classification. Specifically, multilevel signal decomposition is realized by using the means of multi resolution analysis to obtain the different frequency band coefficients of the three-phase current signal. The related coefficient reconstruction is executed to achieve signals decomposition in different levels. Furthermore,according to the obtained data, the absolute average ratio process is used to extract absolute moving average ratio of signal decomposition in different levels for the three-phase current.Finally, to intelligently classify the inverter switch fault and realize the adaptive ability, the ANN technology is applied.Compared to conventional fault diagnosis methods, the proposed method can accurately detect and locate the open-switch fault for any location of the microgrid inverter. Additionally, it need not set related threshold of algorithm and does not require normalization process, which is relatively easy to implement. The effectiveness of the proposed fault diagnosis method is demonstrated through detailed simulation results.

Multilevel read-only optical recording methods

The advantages of read-only storage is the predominance of optical recording relative to magnetic and other rewritable methods. Multilevel （ML） read-only technology has been a trend to improve the data capacity and transfer rate. Based on the principle and coding method of ML, this paper demonstrates some ML read-only recording methods, of which a new ML read-only recording is developed. This recording method integrates amplitude modulation achieved by the reaction mechanism of physics and chemistry of photoresist with the run-length-limited technology. The discs can be achieved using standard photoresist mastering and replication techniques with great compatibility to conventional binary read-only discs.

Gaussian shaper for nuclear pulses based on multilevel cascade convolution

For nuclear measurements,it is necessary to obtain accurate information from nuclear pulses,which should be obtained by first shaping the pulses outputted by the detectors.However,commonly used pulse-shaping algorithms have certain problems.For example,certain pulse-shaping algorithms have long dead-times in high-counting-rate environments or are difficult to achieve in digital systems.Gaussian signals are widely used in analog nuclear instruments owing to their symmetry and completeness.A Gaussian signal is usually implemented by using a multilevel S–K filter in series or in parallel.It is difficult to construct a real-time digital Gaussian filter for the complex Gaussian filtering algorithm.Based on the multilevel cascade convolution,a pulse-shaping algorithm for double exponential signals is proposed in this study,which,in addition to double exponential signals,allows more complex output signal models to be used in the new algorithm.The proposed algorithm can be used in high-counting-rate environments and has been implemented in an FPGA with fewer multipliers than those required in other traditional Gaussian pulse-shaping algorithms.The offline processing results indicated that the average peak base width of the output-shaped pulses obtained using the proposed algorithm was reduced compared with that obtained using the traditional Gaussian pulse-shaping algorithm.Experimental results also demonstrated that signal-to-noise ratios and energy resolutions were improved,particularly for pulses with a low energy.The energy resolution was improved by 0.1–0.2%while improving the counting rate.

Efficient analysis of dielectric radomes using multilevel fast multipole algorithm with CRWG basis

A full-wave analysis of the electromagnetic problem of a three-dimensional （3-D） antenna radiating through a 3-D dielectric radome is preserued. The problem is formulated using the Poggio-Miller-Chang-Harrington- Wu（PMCHW） approach for homogeneous dielectric objects and the electric field integral equation for conducting objects. The integral equations are discretized by the method of moment （MoM）, in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions. The resultant matrix equation is then solved by the multilevel fast multipole algorithm （MLFMA） and fast far-field approximation （FAFFA） is used to further accelerate the computation. The radiation patterns of dipole arrays in the presence of radomes are presented. The numerical results demonstrate the accuracy and versatility of this method.

Automatic Delineation of Lung Parenchyma Based on Multilevel Thresholding and Gaussian Mixture Modelling

Delineation of the lung parenchyma in the thoracic Computed Tomography(CT)is an important processing step for most of the pulmonary image analysis such as lung volume extraction,lung nodule detection and pulmonary vessel segmentation.An automatic method for accurate delineation of lung parenchyma in thoracic Computed Tomography images is presented in this paper.The proposed method involves a segmentation phase followed by a lung boundary correction technique.The tissues in the thoracic Computed Tomography can be represented by a number of Gaussians.We propose a histogram utilized Adaptive Multilevel Thresholding(AMT)for estimating the total number of Gaussians and their initial parameters.The parameters of Gaussian components are updated by Expectation Maximization(EM)algorithm.The segmented lung parenchyma from the Gaussian Mixture model(GMM)undergoes an Adaptive Morphological Filtering(AMF)to reduce the boundary errors.The proposed method has been tested on 70 diseased and 119 normal lung images from 28 cases obtained from Lung Image Database Consortium(LIDC).The performance of the proposed system has been validated.