Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimen...Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.展开更多
Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established man...Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established manly based on the effects of water deficits on final fruit quality.Few studies have focused on the real-time effects of water status on fruit and shoot growth.To establish soil water potential (ψ_(soil)) thresholds to trigger irrigation of peach at pivotal fruit developmental stages,photogrammetry,^(13)C labelling,and other techniques were used in this study to investigate real-time changes in stem diameter,fruit projected area,net leaf photosynthetic rate (P_(n)),and allocation of photoassimilates to fruit under soil water potential conditions ranging from saturation to stress in 6-year-old Shimizu hakuto’peach.Stem growth,fruit growth,and P_n exhibited gradually decreasing sensitivity to water deficits during fruit developmental stages I,II,and III.Stem diameter growth was significantly inhibited whenψ_(soil)dropped to-8.5,-7.6,and-5.4 k Pa,respectively.Fruit growth rate was low,reaching zero when theψ_(soil)was-9.0 to-23.1,-14.9 to-21.4,and-16.5 to-23.3 k Pa,respectively,and P_ndecreased significantly when theψ_(soil)reached-24.2,-22.7,and-20.4 kPa,respectively.In addition,more photoassimilates were allocated to fruit under moderateψ_(soil)conditions (-10.1 to-17.0 k Pa) than under otherψ_(soil)values.Our results revealed threeψ_(soil)thresholds,-10.0,-15.0,and-15.0 kPa,suitable for triggering irrigation during stages I,II,and III,respectively.These thresholds can be helpful for controlling excessive tree vigor,maintaining rapid fruit growth and leaf photosynthesis,and promoting the allocation of more photoassimilates to fruit.展开更多
The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining hall...The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.展开更多
Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Bas...Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.展开更多
In this study, based on the simulated discharge results of chemical disinfectants, hypocotyl germination concentration gradient pre-test and concentration gradient determination experiment were set up respectively. La...In this study, based on the simulated discharge results of chemical disinfectants, hypocotyl germination concentration gradient pre-test and concentration gradient determination experiment were set up respectively. Laboratory cultivation was conducted to compare and analyze the root germination and germination indexes, three mangrove hypocotyls of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. Rhynchopetalas’ efficiency of cumulative root germination, cumulative germination and the cumulative expansion of the second pair of leaves, one-way analysis of variance was used to obtain the tolerance threshold of three mangrove hypocotyls to strong chlorin disinfectant. The study determined that the by-products of strong chlorin disinfectant, the toxic threshold concentrations of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. rhynchopetala are close to 0.55 mg/L, 0.55 mg/L and 0.25 mg/L, respectively. This concentration range is lower than the average concentration of 1.183 mg/L of active chlorine emitted from strong chlorine concentrate during pond clearing in high-level shrimp ponds, indicating that transient emissions of strong chlorine concentrate during pond clearing can have a toxic effect on mangrove plants. The strength of tolerance of the embryonic axes of the three mangrove species to effective chlorine contamination was, Ceriopstagal C.B. Rob. stronger than Bruguiera sexangula var. rhynchopetala, and Kandelia candel (Linn.) Druce is the weakest.展开更多
Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven facto...Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven factors.However,previous studies on avulsion thresholds usually focused on topography-driven factors due to the centurial or millennial avulsion timescales of the world’s most deltas,but neglected the impacts of flood-driven factors.In the current study,a novel demarcation equation including the two driven factors was proposed,with the decadal timescale of avulsion being considered in the Yellow River Estuary(YRE).In order to quantify the contributions of different factors in each category,an entropy-based methodology was used to calculate the contributing weights of these factors.The factor with the highest weight in each category was then used to construct the demarcation equation,based on avulsion datasets associated with the YRE.An avulsion threshold was deduced according to the demarcation equation.This avulsion threshold was then applied to conduct the risk assessment of avulsion in the YRE.The results show that:two dominant factors cover respectively geomorphic coefficient representing the topography-driven factor and fluvial erosion intensity representing the flood-driven factor,which were thus employed to define a two dimensional mathematical space in which the demarcation equation can be obtained;the avulsion threshold derived from the equation was also applied in the risk assessment of avulsion;and the avulsion threshold proposed in this study is more accurate,as compared with the existing thresholds.展开更多
Threshold signature is an important branch of the digital signature scheme,which can distribute signature rights and avoid the abuse of signature rights.With the continuous development of quantum computation and quant...Threshold signature is an important branch of the digital signature scheme,which can distribute signature rights and avoid the abuse of signature rights.With the continuous development of quantum computation and quantum information,quantum threshold signatures are gradually becoming more popular.Recently,a quantum(t,n)threshold group signature scheme was analyzed that uses techniques such as quantum-controlled-not operation and quantum teleportation.However,this scheme cannot resist forgery attack and does not conform to the design of a threshold signature in the signing phase.Based on the original scheme,we propose an improved quantum(t,n)threshold signature scheme using quantum(t,n)threshold secret sharing technology.The analysis proves that the improved scheme can resist forgery attack and collusion attack,and it is undeniable.At the same time,this scheme reduces the level of trust in the arbitrator during the signature phase.展开更多
With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of...With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of data generated from the devices challenges the AIoT systems from information collection,storage,processing and communication.In the review,we introduce volatile threshold switching memristors,which can be roughly classified into three types:metallic conductive filament-based TS devices,amorphous chalcogenide-based ovonic threshold switching devices,and metal-insulator transition based TS devices.They play important roles in high-density storage,energy efficient computing and hardware security for AIoT systems.Firstly,a brief introduction is exhibited to describe the categories(materials and characteristics)of volatile TS devices.And then,switching mechanisms of the three types of TS devices are discussed and systematically summarized.After that,attention is focused on the applications in 3D cross-point memory technology with high storage-density,efficient neuromorphic computing,hardware security(true random number generators and physical unclonable functions),and others(steep subthreshold slope transistor,logic devices,etc.).Finally,the major challenges and future outlook of volatile threshold switching memristors are presented.展开更多
BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and t...BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and the cycle threshold(Ct)measured using the fluorescent polymerase chain reaction(PCR)method were related to pulmonary infections diagnosed via computed tomography(CT).AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values,as determined via PCR.METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2Omicron variant infections were retrospectively collected and categorized into low(<25),medium(25.00-34.99),and high(≥35)Ct groups.The characteristics of chest CT images in each group were statistically analyzed.RESULTS The PCR Ct values ranged from 13.36 to 39.81,with 99 patients in the low,155 in the medium,and 77 in the high Ct groups.Six abnormal chest CT signs were detected,namely,focal infection,patchy consolidation shadows,patchy groundglass shadows,mixed consolidation ground-glass shadows,subpleural interstitial changes,and pleural changes.Focal infections were less frequent in the low Ct group than in the medium and high Ct groups;these infections were the most common sign in the medium and high Ct groups.Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups.The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARSCoV-2 varied depending on the Ct values.Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.展开更多
Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomne...Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.展开更多
Extreme rainfall events on a slope under ridge tillage systems cause concentrated stream soil loss.To analyse the critical thresholds for different stages of water erosion process of ridge systems,simulated rainfall-e...Extreme rainfall events on a slope under ridge tillage systems cause concentrated stream soil loss.To analyse the critical thresholds for different stages of water erosion process of ridge systems,simulated rainfall-erosion experiments for the contour wide ridge(CWR),contour narrow ridge(CNR),longitudinal wide ridge(LWR),and longitudinal narrow ridge(LNR)were conducted under four rainfall intensities,with slope gradients of 3°and 5°.For the runoff event,the runoff depth order was LNR>LWR>CWR>CNR;the soil loss order was CNR>LNR>CWR>LWR.The product of slope factor(S)and rainfall erosivity(R)or runoff depth(D),can be adopted as critical thresholds for different stages of runoff and soil erosion process.For the longitudinal ridge systems,R values were provided for LWR and LNR and were the beginning of sheet flow,whereas the product of rainfall erosivity and slope factor(RS)values were provided for LWR and LNR as the beginning of the accelerated concentrated flow.For the contour ridge systems,R values were provided for CWR and CNR as critical thresholds for the beginning of overflow.The product of runoff depth and slope factor(DS)values were 9.98 and 7.73 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of ridge failure;the DS values were 18.45 and 12.75 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of the formation of ephemeral gully erosion.The critical thresholds can distinguish different stages of soil erosion process modelling.展开更多
The structural behavior of the Xiaowan ultrahigh arch dam is primarily influenced by external loads and time-varying characteristics of dam concrete and foundation rock mass during long-term operation. According to ov...The structural behavior of the Xiaowan ultrahigh arch dam is primarily influenced by external loads and time-varying characteristics of dam concrete and foundation rock mass during long-term operation. According to overload testing with a geological model and the measured time series of installed perpendicular lines, the space and time evolution characteristics of the arch dam structure were analyzed, and its mechanical performance was evaluated. Subsequently, the deformation centroid of the deflective curve was suggested to indicate the magnitude and unique distribution rules for a typical dam section using the measured deformation values at multi-monitoring points. The ellipse equations of the critical ellipsoid for the centroid were derived from the historical measured time series. Hydrostatic and seasonal components were extracted from the measured deformation values with a traditional statistical model, and residuals were adopted as a grey component. A time-varying grey model was developed to accurately predict the evolution of the deformation behavior of the ultrahigh arch dam during future operation. In the developed model, constant coefficients were modified so as to be time-dependent functions, and the prediction accuracy was significantly improved through introduction of a forgetting factor. Finally, the critical threshold was estimated, and predicted ellipsoids were derived for the Xiaowan arch dam. The findings of this study can provide technical support for safety evaluation of the actual operation of ultrahigh arch dams and help to provide early warning of abnormal changes.展开更多
Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of p...Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.展开更多
The total ionizing dose(TID) effect is a key cause for the degradation/failure of semiconductor device performance under energetic-particle irradiation. We developed a dynamic model of mobile particles and defects by ...The total ionizing dose(TID) effect is a key cause for the degradation/failure of semiconductor device performance under energetic-particle irradiation. We developed a dynamic model of mobile particles and defects by solving the rate equations and Poisson's equation simultaneously, to understand threshold voltage shifts induced by TID in silicon-based metal–oxide–semiconductor(MOS) devices. The calculated charged defect distribution and corresponding electric field under different TIDs are consistent with experiments. TID changes the electric field at the Si/SiO_(2) interface by inducing the accumulation of oxide charged defects nearby, thus shifting the threshold voltage accordingly. With increasing TID, the oxide charged defects increase to saturation, and the electric field increases following the universal 2/3 power law. Through analyzing the influence of TID on the interfacial electric field by different factors, we recommend that the radiation-hardened performance of devices can be improved by choosing a thin oxide layer with high permittivity and under high gate voltages.展开更多
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...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%.展开更多
With the rapid increase in demand for data trustworthiness and data security,distributed data storage technology represented by blockchain has received unprecedented attention.These technologies have been suggested fo...With the rapid increase in demand for data trustworthiness and data security,distributed data storage technology represented by blockchain has received unprecedented attention.These technologies have been suggested for various uses because of their remarkable ability to offer decentralization,high autonomy,full process traceability,and tamper resistance.Blockchain enables the exchange of information and value in an untrusted environment.There has been a significant increase in attention to the confidentiality and privacy preservation of blockchain technology.Ensuring data privacy is a critical concern in cryptography,and one of the most important protocols used to achieve this is the secret-sharing method.By dividing the secret into shares and distributing them among multiple parties,no one can access the secret without the cooperation of the other parties.However,Attackers with quantum computers in the future can execute Grover’s and Shor’s algorithms on quantum computers that can break or reduce the currently widely used cryptosystems.Furthermore,centralized management of keys increases the risk of key leakage.This paper proposed a post-quantum threshold algo-rithm to reduce the risk of data privacy leakage in blockchain Systems.This algorithm uses distributed key management technology to reduce the risk of individual node private key leakage and provide post-quantum security.The proposed privacy-preserving cryptographic algorithm provides a post-quantum threshold architecture for managing data,which involves defining users and interaction processes within the system.This paper applies a linear secret-sharing solution to partition the private key of the Number Theory Research Unit(NTRU)algorithm into n parts.It constructs a t–n threshold that allows recovery of the plaintext only when more than t nodes participate in decryption.The characteristic of a threshold makes the scheme resistant to collusion attacks from members whose combined credibility is less than the threshold.This mitigates the risk of single-point private key leakage.During the threshold decryption process,the private key information of the nodes will not be leaked.In addition,the fact that the threshold algorithm is founded on the NTRU lattice enables it to withstand quantum attacks,thus enhancing its security.According to the analysis,the proposed scheme provides superior protection compared to currently availablemethods.This paper provides postquantum security solutions for data security protection of blockchain,which will enrich the use of blockchain in scenarios with strict requirements for data privacy protection.展开更多
Coronavirus Disease 2019(COVID-19)is the most severe epidemic that is prevalent all over the world.How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidem...Coronavirus Disease 2019(COVID-19)is the most severe epidemic that is prevalent all over the world.How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic.Moreover,it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images.As we all know,image segmentation is a critical stage in image processing and analysis.To achieve better image segmentation results,this paper proposes to improve the multi-verse optimizer algorithm using the Rosenbrock method and diffusion mechanism named RDMVO.Then utilizes RDMVO to calculate the maximum Kapur’s entropy for multilevel threshold image segmentation.This image segmentation scheme is called RDMVO-MIS.We ran two sets of experiments to test the performance of RDMVO and RDMVO-MIS.First,RDMVO was compared with other excellent peers on IEEE CEC2017 to test the performance of RDMVO on benchmark functions.Second,the image segmentation experiment was carried out using RDMVO-MIS,and some meta-heuristic algorithms were selected as comparisons.The test image dataset includes Berkeley images and COVID-19 Chest X-ray images.The experimental results verify that RDMVO is highly competitive in benchmark functions and image segmentation experiments compared with other meta-heuristic algorithms.展开更多
Sign language is used as a communication medium in the field of trade,defence,and in deaf-mute communities worldwide.Over the last few decades,research in the domain of translation of sign language has grown and becom...Sign language is used as a communication medium in the field of trade,defence,and in deaf-mute communities worldwide.Over the last few decades,research in the domain of translation of sign language has grown and become more challenging.This necessitates the development of a Sign Language Translation System(SLTS)to provide effective communication in different research domains.In this paper,novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm(Hybrid-AO)for image segmentation is proposed for the translation of alphabet-level Indian Sign Language(ISLTS)with a 5-layer Convolution Neural Network(CNN).The focus of this paper is to analyze various image segmentation(Canny Edge Detection,Simple Thresholding,and Hybrid-AO),pooling approaches(Max,Average,and Global Average Pooling),and activation functions(ReLU,Leaky ReLU,and ELU).5-layer CNN with Max pooling,Leaky ReLU activation function,and Hybrid-AO(5MXLR-HAO)have outperformed other frameworks.An open-access dataset of ISL alphabets with approx.31 K images of 26 classes have been used to train and test the model.The proposed framework has been developed for translating alphabet-level Indian Sign Language into text.The proposed framework attains 98.95%training accuracy,98.05%validation accuracy,and 0.0721 training loss and 0.1021 validation loss and the perfor-mance of the proposed system outperforms other existing systems.展开更多
In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to ...In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection.However,these methods do not take into account the effect of sample size and its effect on improving CoR performance.In general,a large sample size results in more reliable detection,but takes longer sensing time and increases complexity.Thus,the locally sensed sample size is an optimization problem.Therefore,optimizing the local sample size for each cognitive user helps to improve CoR performance.In this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)optimization.Through the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.展开更多
Altered igneous reservoirs have low porosity and permeability,compact structure and certain heterogeneity.A simple digital core with certain generality and multi-parameter constraints can be con-structed to characteri...Altered igneous reservoirs have low porosity and permeability,compact structure and certain heterogeneity.A simple digital core with certain generality and multi-parameter constraints can be con-structed to characterize the microscopic pore structure and mineral composition.In this paper,based on core X-ray,CT images and whole-rock mineral analysis,threshold segmentation of mass content and grayscale distribution of various minerals in different lithologies of igneous rocks in the buried hill of Huizhou depression is carried out to construct digital core of altered igneous rocks.The results show that after converting the mineral mass content into volume content,the minerals of altered igneous rocks in Huizhou depression can be classified into components.According to the range of grayscale value,components can be divided into six parts.Due to the difference of the content of components in different lithologies of igneous rocks,differentiated grayscale threshold segmentation is needed to obtain the digital core for a single lithology.The final digital core generation process includes two steps:building a single component digital core,and stacking and combining.This kind of universal digital core model can support the subsequent pore scale numerical simulation and comprehensive rock physics research.展开更多
基金M.Zhu acknowledges support by the National Outstanding Youth Program(62322411)the Hundred Talents Program(Chinese Academy of Sciences)+1 种基金the Shanghai Rising-Star Program(21QA1410800)The financial support was provided by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB44010200).
文摘Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.
基金supported by the projects of China Agriculture Research System of MOF and MARA (Grant No.CARS-29-ZP-7)Outstanding Youth Science and Technology Fund of Henan Academy of Agricultural Sciences (Grant No.2022YQ08)。
文摘Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established manly based on the effects of water deficits on final fruit quality.Few studies have focused on the real-time effects of water status on fruit and shoot growth.To establish soil water potential (ψ_(soil)) thresholds to trigger irrigation of peach at pivotal fruit developmental stages,photogrammetry,^(13)C labelling,and other techniques were used in this study to investigate real-time changes in stem diameter,fruit projected area,net leaf photosynthetic rate (P_(n)),and allocation of photoassimilates to fruit under soil water potential conditions ranging from saturation to stress in 6-year-old Shimizu hakuto’peach.Stem growth,fruit growth,and P_n exhibited gradually decreasing sensitivity to water deficits during fruit developmental stages I,II,and III.Stem diameter growth was significantly inhibited whenψ_(soil)dropped to-8.5,-7.6,and-5.4 k Pa,respectively.Fruit growth rate was low,reaching zero when theψ_(soil)was-9.0 to-23.1,-14.9 to-21.4,and-16.5 to-23.3 k Pa,respectively,and P_ndecreased significantly when theψ_(soil)reached-24.2,-22.7,and-20.4 kPa,respectively.In addition,more photoassimilates were allocated to fruit under moderateψ_(soil)conditions (-10.1 to-17.0 k Pa) than under otherψ_(soil)values.Our results revealed threeψ_(soil)thresholds,-10.0,-15.0,and-15.0 kPa,suitable for triggering irrigation during stages I,II,and III,respectively.These thresholds can be helpful for controlling excessive tree vigor,maintaining rapid fruit growth and leaf photosynthesis,and promoting the allocation of more photoassimilates to fruit.
基金Project supported by the National Natural Science Foundation of China(Grant No.61871234).
文摘The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.
基金The authors gratefully acknowledge the financial supports from the National Science Foundation of China under Grant 52274027 as well as the High-end Foreign Experts Recruitment Plan of the Ministry of Science and Technology China under Grant G2022105027L.
文摘Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.
文摘In this study, based on the simulated discharge results of chemical disinfectants, hypocotyl germination concentration gradient pre-test and concentration gradient determination experiment were set up respectively. Laboratory cultivation was conducted to compare and analyze the root germination and germination indexes, three mangrove hypocotyls of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. Rhynchopetalas’ efficiency of cumulative root germination, cumulative germination and the cumulative expansion of the second pair of leaves, one-way analysis of variance was used to obtain the tolerance threshold of three mangrove hypocotyls to strong chlorin disinfectant. The study determined that the by-products of strong chlorin disinfectant, the toxic threshold concentrations of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. rhynchopetala are close to 0.55 mg/L, 0.55 mg/L and 0.25 mg/L, respectively. This concentration range is lower than the average concentration of 1.183 mg/L of active chlorine emitted from strong chlorine concentrate during pond clearing in high-level shrimp ponds, indicating that transient emissions of strong chlorine concentrate during pond clearing can have a toxic effect on mangrove plants. The strength of tolerance of the embryonic axes of the three mangrove species to effective chlorine contamination was, Ceriopstagal C.B. Rob. stronger than Bruguiera sexangula var. rhynchopetala, and Kandelia candel (Linn.) Druce is the weakest.
基金financially supported by the National Key Research and Development Program of China(Grant No.2023YFC3200026)the National Natural Science Foundation of China(Grant No.U2243238)。
文摘Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven factors.However,previous studies on avulsion thresholds usually focused on topography-driven factors due to the centurial or millennial avulsion timescales of the world’s most deltas,but neglected the impacts of flood-driven factors.In the current study,a novel demarcation equation including the two driven factors was proposed,with the decadal timescale of avulsion being considered in the Yellow River Estuary(YRE).In order to quantify the contributions of different factors in each category,an entropy-based methodology was used to calculate the contributing weights of these factors.The factor with the highest weight in each category was then used to construct the demarcation equation,based on avulsion datasets associated with the YRE.An avulsion threshold was deduced according to the demarcation equation.This avulsion threshold was then applied to conduct the risk assessment of avulsion in the YRE.The results show that:two dominant factors cover respectively geomorphic coefficient representing the topography-driven factor and fluvial erosion intensity representing the flood-driven factor,which were thus employed to define a two dimensional mathematical space in which the demarcation equation can be obtained;the avulsion threshold derived from the equation was also applied in the risk assessment of avulsion;and the avulsion threshold proposed in this study is more accurate,as compared with the existing thresholds.
基金the National Natural Science Foundation of China(Grant Nos.61771294 and 61972235)。
文摘Threshold signature is an important branch of the digital signature scheme,which can distribute signature rights and avoid the abuse of signature rights.With the continuous development of quantum computation and quantum information,quantum threshold signatures are gradually becoming more popular.Recently,a quantum(t,n)threshold group signature scheme was analyzed that uses techniques such as quantum-controlled-not operation and quantum teleportation.However,this scheme cannot resist forgery attack and does not conform to the design of a threshold signature in the signing phase.Based on the original scheme,we propose an improved quantum(t,n)threshold signature scheme using quantum(t,n)threshold secret sharing technology.The analysis proves that the improved scheme can resist forgery attack and collusion attack,and it is undeniable.At the same time,this scheme reduces the level of trust in the arbitrator during the signature phase.
基金supported by the STI 2030—Major Projects(Grant No.2021ZD0201201)National Natural Science Foundation of China(Grant No.92064012)Hubei Province Postdoctoral Innovation Research Program(Grant No.0106182103)。
文摘With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of data generated from the devices challenges the AIoT systems from information collection,storage,processing and communication.In the review,we introduce volatile threshold switching memristors,which can be roughly classified into three types:metallic conductive filament-based TS devices,amorphous chalcogenide-based ovonic threshold switching devices,and metal-insulator transition based TS devices.They play important roles in high-density storage,energy efficient computing and hardware security for AIoT systems.Firstly,a brief introduction is exhibited to describe the categories(materials and characteristics)of volatile TS devices.And then,switching mechanisms of the three types of TS devices are discussed and systematically summarized.After that,attention is focused on the applications in 3D cross-point memory technology with high storage-density,efficient neuromorphic computing,hardware security(true random number generators and physical unclonable functions),and others(steep subthreshold slope transistor,logic devices,etc.).Finally,the major challenges and future outlook of volatile threshold switching memristors are presented.
文摘BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and the cycle threshold(Ct)measured using the fluorescent polymerase chain reaction(PCR)method were related to pulmonary infections diagnosed via computed tomography(CT).AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values,as determined via PCR.METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2Omicron variant infections were retrospectively collected and categorized into low(<25),medium(25.00-34.99),and high(≥35)Ct groups.The characteristics of chest CT images in each group were statistically analyzed.RESULTS The PCR Ct values ranged from 13.36 to 39.81,with 99 patients in the low,155 in the medium,and 77 in the high Ct groups.Six abnormal chest CT signs were detected,namely,focal infection,patchy consolidation shadows,patchy groundglass shadows,mixed consolidation ground-glass shadows,subpleural interstitial changes,and pleural changes.Focal infections were less frequent in the low Ct group than in the medium and high Ct groups;these infections were the most common sign in the medium and high Ct groups.Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups.The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARSCoV-2 varied depending on the Ct values.Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.
基金supported by the National Natural Science Foundation of China(61703410,61873175,62073336,61873273,61773386,61922-089)the Basic Research Plan of Shaanxi Natural Science Foundation of China(2022JM-376).
文摘Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.
基金funded by the IWHR Research&Development Support Program(Grant SE0145B032021)the National Key Research and Development Program of China(Grant 2018YFC0507002)。
文摘Extreme rainfall events on a slope under ridge tillage systems cause concentrated stream soil loss.To analyse the critical thresholds for different stages of water erosion process of ridge systems,simulated rainfall-erosion experiments for the contour wide ridge(CWR),contour narrow ridge(CNR),longitudinal wide ridge(LWR),and longitudinal narrow ridge(LNR)were conducted under four rainfall intensities,with slope gradients of 3°and 5°.For the runoff event,the runoff depth order was LNR>LWR>CWR>CNR;the soil loss order was CNR>LNR>CWR>LWR.The product of slope factor(S)and rainfall erosivity(R)or runoff depth(D),can be adopted as critical thresholds for different stages of runoff and soil erosion process.For the longitudinal ridge systems,R values were provided for LWR and LNR and were the beginning of sheet flow,whereas the product of rainfall erosivity and slope factor(RS)values were provided for LWR and LNR as the beginning of the accelerated concentrated flow.For the contour ridge systems,R values were provided for CWR and CNR as critical thresholds for the beginning of overflow.The product of runoff depth and slope factor(DS)values were 9.98 and 7.73 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of ridge failure;the DS values were 18.45 and 12.75 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of the formation of ephemeral gully erosion.The critical thresholds can distinguish different stages of soil erosion process modelling.
基金supported by the National Natural Science Foundation of China(Grant No.52079046)the Fundamental Research Funds for the Central Universities(Grant No.B210202017).
文摘The structural behavior of the Xiaowan ultrahigh arch dam is primarily influenced by external loads and time-varying characteristics of dam concrete and foundation rock mass during long-term operation. According to overload testing with a geological model and the measured time series of installed perpendicular lines, the space and time evolution characteristics of the arch dam structure were analyzed, and its mechanical performance was evaluated. Subsequently, the deformation centroid of the deflective curve was suggested to indicate the magnitude and unique distribution rules for a typical dam section using the measured deformation values at multi-monitoring points. The ellipse equations of the critical ellipsoid for the centroid were derived from the historical measured time series. Hydrostatic and seasonal components were extracted from the measured deformation values with a traditional statistical model, and residuals were adopted as a grey component. A time-varying grey model was developed to accurately predict the evolution of the deformation behavior of the ultrahigh arch dam during future operation. In the developed model, constant coefficients were modified so as to be time-dependent functions, and the prediction accuracy was significantly improved through introduction of a forgetting factor. Finally, the critical threshold was estimated, and predicted ellipsoids were derived for the Xiaowan arch dam. The findings of this study can provide technical support for safety evaluation of the actual operation of ultrahigh arch dams and help to provide early warning of abnormal changes.
基金supported by the National Natural Science Foundation of China(61801154,61771176)the Zhejiang Provincial Natural Science Foundation of China(LY20F010008).
文摘Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.
基金Project supported by the Science Challenge Project of China (Grant No.TZ2018004)the National Natural Science Foundation of China (Grant Nos.11975018 and 11775254)+1 种基金the National MCF Energy R&D Program of China (Grant No.2018YEF0308100)the outstanding member of Youth Innovation Promotion Association CAS (Grant No.Y202087)。
文摘The total ionizing dose(TID) effect is a key cause for the degradation/failure of semiconductor device performance under energetic-particle irradiation. We developed a dynamic model of mobile particles and defects by solving the rate equations and Poisson's equation simultaneously, to understand threshold voltage shifts induced by TID in silicon-based metal–oxide–semiconductor(MOS) devices. The calculated charged defect distribution and corresponding electric field under different TIDs are consistent with experiments. TID changes the electric field at the Si/SiO_(2) interface by inducing the accumulation of oxide charged defects nearby, thus shifting the threshold voltage accordingly. With increasing TID, the oxide charged defects increase to saturation, and the electric field increases following the universal 2/3 power law. Through analyzing the influence of TID on the interfacial electric field by different factors, we recommend that the radiation-hardened performance of devices can be improved by choosing a thin oxide layer with high permittivity and under high gate voltages.
基金The author would like to express their gratitude to the Ministry of Education and the Deanship of Scientific Research-Najran University-Kingdom of Saudi Arabia for their financial and technical support under code number:NU/NRP/SERC/11/3.
文摘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%.
基金supported by the National Key R&D Program of China(2022YFB2703400).
文摘With the rapid increase in demand for data trustworthiness and data security,distributed data storage technology represented by blockchain has received unprecedented attention.These technologies have been suggested for various uses because of their remarkable ability to offer decentralization,high autonomy,full process traceability,and tamper resistance.Blockchain enables the exchange of information and value in an untrusted environment.There has been a significant increase in attention to the confidentiality and privacy preservation of blockchain technology.Ensuring data privacy is a critical concern in cryptography,and one of the most important protocols used to achieve this is the secret-sharing method.By dividing the secret into shares and distributing them among multiple parties,no one can access the secret without the cooperation of the other parties.However,Attackers with quantum computers in the future can execute Grover’s and Shor’s algorithms on quantum computers that can break or reduce the currently widely used cryptosystems.Furthermore,centralized management of keys increases the risk of key leakage.This paper proposed a post-quantum threshold algo-rithm to reduce the risk of data privacy leakage in blockchain Systems.This algorithm uses distributed key management technology to reduce the risk of individual node private key leakage and provide post-quantum security.The proposed privacy-preserving cryptographic algorithm provides a post-quantum threshold architecture for managing data,which involves defining users and interaction processes within the system.This paper applies a linear secret-sharing solution to partition the private key of the Number Theory Research Unit(NTRU)algorithm into n parts.It constructs a t–n threshold that allows recovery of the plaintext only when more than t nodes participate in decryption.The characteristic of a threshold makes the scheme resistant to collusion attacks from members whose combined credibility is less than the threshold.This mitigates the risk of single-point private key leakage.During the threshold decryption process,the private key information of the nodes will not be leaked.In addition,the fact that the threshold algorithm is founded on the NTRU lattice enables it to withstand quantum attacks,thus enhancing its security.According to the analysis,the proposed scheme provides superior protection compared to currently availablemethods.This paper provides postquantum security solutions for data security protection of blockchain,which will enrich the use of blockchain in scenarios with strict requirements for data privacy protection.
基金supported by the Natural Science Foundation of Zhejiang Province(LY21F020001,LZ22F020005)National Natural Science Foundation of China(62076185,U1809209)+1 种基金Science and Technology Plan Project of Wenzhou,China(ZG2020026)We also acknowledge the respected editor and reviewers'efforts to enhance the quality of this research.
文摘Coronavirus Disease 2019(COVID-19)is the most severe epidemic that is prevalent all over the world.How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic.Moreover,it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images.As we all know,image segmentation is a critical stage in image processing and analysis.To achieve better image segmentation results,this paper proposes to improve the multi-verse optimizer algorithm using the Rosenbrock method and diffusion mechanism named RDMVO.Then utilizes RDMVO to calculate the maximum Kapur’s entropy for multilevel threshold image segmentation.This image segmentation scheme is called RDMVO-MIS.We ran two sets of experiments to test the performance of RDMVO and RDMVO-MIS.First,RDMVO was compared with other excellent peers on IEEE CEC2017 to test the performance of RDMVO on benchmark functions.Second,the image segmentation experiment was carried out using RDMVO-MIS,and some meta-heuristic algorithms were selected as comparisons.The test image dataset includes Berkeley images and COVID-19 Chest X-ray images.The experimental results verify that RDMVO is highly competitive in benchmark functions and image segmentation experiments compared with other meta-heuristic algorithms.
文摘Sign language is used as a communication medium in the field of trade,defence,and in deaf-mute communities worldwide.Over the last few decades,research in the domain of translation of sign language has grown and become more challenging.This necessitates the development of a Sign Language Translation System(SLTS)to provide effective communication in different research domains.In this paper,novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm(Hybrid-AO)for image segmentation is proposed for the translation of alphabet-level Indian Sign Language(ISLTS)with a 5-layer Convolution Neural Network(CNN).The focus of this paper is to analyze various image segmentation(Canny Edge Detection,Simple Thresholding,and Hybrid-AO),pooling approaches(Max,Average,and Global Average Pooling),and activation functions(ReLU,Leaky ReLU,and ELU).5-layer CNN with Max pooling,Leaky ReLU activation function,and Hybrid-AO(5MXLR-HAO)have outperformed other frameworks.An open-access dataset of ISL alphabets with approx.31 K images of 26 classes have been used to train and test the model.The proposed framework has been developed for translating alphabet-level Indian Sign Language into text.The proposed framework attains 98.95%training accuracy,98.05%validation accuracy,and 0.0721 training loss and 0.1021 validation loss and the perfor-mance of the proposed system outperforms other existing systems.
基金This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R97),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection.However,these methods do not take into account the effect of sample size and its effect on improving CoR performance.In general,a large sample size results in more reliable detection,but takes longer sensing time and increases complexity.Thus,the locally sensed sample size is an optimization problem.Therefore,optimizing the local sample size for each cognitive user helps to improve CoR performance.In this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)optimization.Through the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.
基金Supported by Project of the National Natural Science Foundation of China (No. 42072323)
文摘Altered igneous reservoirs have low porosity and permeability,compact structure and certain heterogeneity.A simple digital core with certain generality and multi-parameter constraints can be con-structed to characterize the microscopic pore structure and mineral composition.In this paper,based on core X-ray,CT images and whole-rock mineral analysis,threshold segmentation of mass content and grayscale distribution of various minerals in different lithologies of igneous rocks in the buried hill of Huizhou depression is carried out to construct digital core of altered igneous rocks.The results show that after converting the mineral mass content into volume content,the minerals of altered igneous rocks in Huizhou depression can be classified into components.According to the range of grayscale value,components can be divided into six parts.Due to the difference of the content of components in different lithologies of igneous rocks,differentiated grayscale threshold segmentation is needed to obtain the digital core for a single lithology.The final digital core generation process includes two steps:building a single component digital core,and stacking and combining.This kind of universal digital core model can support the subsequent pore scale numerical simulation and comprehensive rock physics research.
