The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost. With development of Multinational Company, SOHO office, E-government the number of firewalls/VPN will increase rapidly. R...The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost. With development of Multinational Company, SOHO office, E-government the number of firewalls/VPN will increase rapidly. Rule table in stand-alone or network will be increased in geometric series accordingly. Checking the consistence of rule table manually is inadequate. A formal approach can define semantic consistence, make a theoretic foundation of intelligent management about rule tables. In this paper, a kind of formalization of host rules and network ones for auto rule-validation based on SET theory were proporsed and a rule validation scheme was defined. The analysis results show the superior performance of the methods and demonstrate its potential for the intelligent management based on rule tables.展开更多
With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions...With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.展开更多
In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this stu...In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.展开更多
Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER...Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER)models,which hinders the algorithm’s comprehension of emotional states and reduces the overall recognition accuracy.A novel FER model is introduced to address these issues.It integrates rebalancing mechanisms to regulate attention consistency and focus,offering enhanced efficacy.Our approach proposes the following improvements:(i)rebalancing weights are used to enhance the consistency between the heatmaps of an original face sample and its horizontally flipped counterpart;(ii)coefficient factors are incorporated into the standard cross entropy loss function,and rebalancing weights are incorporated to fine-tune the loss adjustment.Experimental results indicate that the FER model outperforms the current leading algorithm,MEK,achieving 0.69%and 2.01%increases in overall and average recognition accuracies,respectively,on the RAF-DB dataset.The model exhibits accuracy improvements of 0.49%and 1.01%in the AffectNet dataset and 0.83%and 1.23%in the FERPlus dataset,respectively.These outcomes validate the superiority and stability of the proposed FER model.展开更多
Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds...Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.展开更多
The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst...The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst random perturbations,and processing efficiency.Because of their simplicity,conventional numerical techniques like the Euler-Maruyama method are frequently employed to solve stochastic differential equations;nonetheless,they may have low-order accuracy and lower stability in stiff or high-resolution situations.This study proposes a novel computational scheme for solving SPDEs arising from a stochastic SEIR model with q-diffusion and a general incidence rate function.A proposed computational scheme can be used to solve stochastic partial differential equations.For spatial discretization,a compact scheme is chosen.The compact scheme can provide a sixth-order accurate solution.The proposed scheme can be considered an extension of the Euler Maruyama method.Stability and consistency in the mean square sense are also provided.For application purposes,the stochastic SEIR model is considered using q-diffusion effects.The scheme is used to solve the stochastic model and compared with the Euler-Maruyama method.The scheme is also compared with nonstandard finite difference method for solving deterministic models.In both cases,it performs better than existing schemes.Incorporating q-diffusion further enhanced the model’s ability to represent realistic spatial-temporal disease dynamics,especially in scenarios where classical diffusion is insufficient.展开更多
The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchai...The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.展开更多
This study introduces a novel bargaining solution termed the"'min-distance bargaining solution"and applies it to a differential games model.A comprehensive algorithm for implementing this new solution is...This study introduces a novel bargaining solution termed the"'min-distance bargaining solution"and applies it to a differential games model.A comprehensive algorithm for implementing this new solution is presented,considering its time consistency within the differential games framework.Realistic scenarios are carefully analyzed to derive insightful findings regarding the mindistance solution,which are further validated through simulations using the resource extraction differential games model.Specifically,we examine scenarios such as managing a finite resource stock in the resource extraction game.Furthermore,a comparative analysis is conducted,pitting the mindistance bargaining solution against well-established alternatives such as Nash bargaining,Kalai-Smorodinsky,and Egalitarian solutions.By subjecting these solutions to numerical evaluations,the study offers valuable insights into decision-making processes.The findings not only contribute to negotiation theory by providing theoretical support but also have practical implications for decision-makers seeking effective strategies.This research significantly advances the field of negotiation theory,particularly in the context of differential games.The proposed min-distance bargaining solution demonstrates its applicability to real-world scenarios and enhances our understanding of strategic decision-making.展开更多
Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often con...Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.展开更多
In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,...In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,we examined the structural characteristics and variability of female bubbling calls among four Cuculus species(Common Cuckoo C.canorus,Oriental Cuckoo C.optatus,Indian Cuckoo C.micropterus,and Lesser Cuckoo C.poliocephalus)breeding in South Korea.Comprehensive acoustic analyses of seven call parameters,using recordings from 2021 to 2023,were conducted to quantify the characteristics of their calls and compare withinand between-individual variability across species.Significant differences were found across all call parameters,with the Common Cuckoo producing the highest number of notes and the Oriental Cuckoo the lowest-frequency calls.Despite these differences,the overall structure of the calls remained acoustically similar,with overlapping characteristics across species.Furthermore,female Common Cuckoos exhibited greater within-individual variability in their calls,while the other species showed higher between-individual variability,which may further complicate species identification based vocalization alone.These findings highlight the complexities of female vocalizations in Cuculus cuckoos and suggest that ecological,social,and evolutionary factors may contribute to this vocal variability.展开更多
Distributed ducted propellers hold significant promise for propulsion systems in Advanced Air Mobility(AAM) due to their high efficiency, low noise, and enhanced redundancy and safety. However, a standardized benchmar...Distributed ducted propellers hold significant promise for propulsion systems in Advanced Air Mobility(AAM) due to their high efficiency, low noise, and enhanced redundancy and safety. However, a standardized benchmark for comparing the aerodynamic characteristics of different ducted propeller configurations remains lacking. Including additional ducted propellers can further complicate the flow field. This paper proposes an equivalent design method for ducted propellers based on the momentum theorem and similarity criteria, introducing three equivalent ducted propeller cases. Transient numerical simulations are conducted using the sliding mesh model. The three cases produce comparable thrust while consuming the same power, with the volume of distributed ducted propellers being reduced by over 29% compared to the single ducted propeller. This study investigates the effect of rotational frequency on aerodynamic performance under hovering conditions. While propeller performance demonstrates low sensitivity to variations in rotational frequency, duct performance exhibits high sensitivity. The research further examines how rotational frequency changes the pressure difference between the duct leading edge and trailing edge. Based on a sensitivity analysis of aerodynamic performance, the flow field mechanisms under different rotational consistency are examined for the case with one duct and two propellers. Differences in aerodynamic performance are attributed to the airflow velocity gradient differences at the duct leading edge and the flow separation characteristics on the crossing side. These findings are significant for enhancing the performance of distributed ducted propellers and improving aircraft controllability.展开更多
This opinion article discusses the original research work of Yünkül et al.(the Authors)published in the Journal of Mountain Science 21(9):3108–3122.Employing non-linear regression,fuzzy logic and artificial...This opinion article discusses the original research work of Yünkül et al.(the Authors)published in the Journal of Mountain Science 21(9):3108–3122.Employing non-linear regression,fuzzy logic and artificial neural network modeling techniques,the Authors interrogated a large database assembled from the existing research literature to assess the performance of twelve equation rules in predicting the undrained shear strength(s_(u))mobilized for remolded fine-grained soils at different values of liquidity index(I_(L))and water content ratio.Based on their analyses,the Authors proposed a simple and reportedly reliable correlation(i.e.,Eq.9 in their paper)for predicting s_(u) over the I_(L) range of 0.15 to 3.00.This article describes various shortcomings in the Authors’assembled database(including potentially anomalous data and covering an excessively wide I_(L) range in relation to routine geotechnical and transportation engineering applications)and their proposed s_(u)=f(I_(L))correlation.Contrary to the Authors’assertions,their proposed correlation is not reliable for fine-grained soils with consistencies in the general firm to stiff range(i.e.,for 0.15<I_(L)<0.40),increasingly overestimating s_(u) for reducing I_(L),and eventually predicting s_(u)→+∞for I_(L)→0.15+(while producing mathematically undefined s_(u) for I_(L)<0.15),thus rendering their correlation unconservative and potentially leading to unsafe geotechnical designs.Exponential or regular-power type s_(u)=f(I_(L))models are more s_(u)itable when developing correlations that are applicable over the full plastic range(of 0<I_(L)<1),thereby providing reasonably conservative s_(u) predictions for use in the preliminary design for routine geotechnical engineering applications.展开更多
The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficu...The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficulty effectively processing and fully representing their spatiotemporal complexity patterns.The article also discusses a potential path of AI development in the engineering domain.Based on the existing understanding of the principles of multilevel com-plexity,this article suggests that consistency among the logical structures of datasets,AI models,model-building software,and hardware will be an important AI development direction and is worthy of careful consideration.展开更多
Ground response analysis and determination of site-specific ground motion parameters are necessary for evaluating seismic loads to enable sustainable design of aboveground and underground structures,particularly in de...Ground response analysis and determination of site-specific ground motion parameters are necessary for evaluating seismic loads to enable sustainable design of aboveground and underground structures,particularly in deep overburden sites.This study investigates the influence of bedrock interface conditions and depth of soil deposits on obtained site-specific ground motion parameters.Employing the one-dimensional seismic response analysis program SOILQUAKE,the ground responses of five representative soil profiles and 1050 case studies are calculated considering three different site models of seismic input interfaces.The analysis employs the actual bedrock interface with a shear wave velocity of 760 m/s as the reference input bedrock interface.The results illustrate that the selection of the bedrock interface condition significantly affects the seismic response on the ground surface of deep overburden sites.Specifically,the ground surface acceleration response spectra at longer periods are notably smaller compared to those at the actual bedrock site.This may present a challenge for designing long-period high-rise buildings situated in deep overburden sites.It is recommended to select a seismic input bedrock interface closely approximating the actual bedrock depth when conducting seismic response analyses for deep overburden sites.展开更多
The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engin...The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.展开更多
In real industrial scenarios, equipment cannot be operated in a faulty state for a long time, resulting in a very limited number of available fault samples, and the method of data augmentation using generative adversa...In real industrial scenarios, equipment cannot be operated in a faulty state for a long time, resulting in a very limited number of available fault samples, and the method of data augmentation using generative adversarial networks for smallsample data has achieved a wide range of applications. However, the current generative adversarial networks applied in industrial processes do not impose realistic physical constraints on the generation of data, resulting in the generation of data that do not have realistic physical consistency. To address this problem, this paper proposes a physical consistency-based WGAN, designs a loss function containing physical constraints for industrial processes, and validates the effectiveness of the method using a common dataset in the field of industrial process fault diagnosis. The experimental results show that the proposed method not only makes the generated data consistent with the physical constraints of the industrial process, but also has better fault diagnosis performance than the existing GAN-based methods.展开更多
In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to...In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to Lie point symmetry in a properly prolonged system,based on which we get a new Bäcklund transformation for this system.New symmetry reduction solutions of the DSSH system are obtained by applying the classical Lie group approach on the prolonged system.Moreover,the DSSH system proves to be CRE integrable and new interesting interaction solutions between solitons and periodic waves are generated and analyzed.展开更多
Large amounts of labeled data are usually needed for training deep neural networks in medical image studies,particularly in medical image classification.However,in the field of semi-supervised medical image analysis,l...Large amounts of labeled data are usually needed for training deep neural networks in medical image studies,particularly in medical image classification.However,in the field of semi-supervised medical image analysis,labeled data is very scarce due to patient privacy concerns.For researchers,obtaining high-quality labeled images is exceedingly challenging because it involves manual annotation and clinical understanding.In addition,skin datasets are highly suitable for medical image classification studies due to the inter-class relationships and the inter-class similarities of skin lesions.In this paper,we propose a model called Coalition Sample Relation Consistency(CSRC),a consistency-based method that leverages Canonical Correlation Analysis(CCA)to capture the intrinsic relationships between samples.Considering that traditional consistency-based models only focus on the consistency of prediction,we additionally explore the similarity between features by using CCA.We enforce feature relation consistency based on traditional models,encouraging the model to learn more meaningful information from unlabeled data.Finally,considering that cross-entropy loss is not as suitable as the supervised loss when studying with imbalanced datasets(i.e.,ISIC 2017 and ISIC 2018),we improve the supervised loss to achieve better classification accuracy.Our study shows that this model performs better than many semi-supervised methods.展开更多
This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer mult...This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.展开更多
The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into ...The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.展开更多
文摘The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost. With development of Multinational Company, SOHO office, E-government the number of firewalls/VPN will increase rapidly. Rule table in stand-alone or network will be increased in geometric series accordingly. Checking the consistence of rule table manually is inadequate. A formal approach can define semantic consistence, make a theoretic foundation of intelligent management about rule tables. In this paper, a kind of formalization of host rules and network ones for auto rule-validation based on SET theory were proporsed and a rule validation scheme was defined. The analysis results show the superior performance of the methods and demonstrate its potential for the intelligent management based on rule tables.
文摘With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.
文摘In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.
基金support from the National Natural Science Foundation of China(Grant Number 62477023).
文摘Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER)models,which hinders the algorithm’s comprehension of emotional states and reduces the overall recognition accuracy.A novel FER model is introduced to address these issues.It integrates rebalancing mechanisms to regulate attention consistency and focus,offering enhanced efficacy.Our approach proposes the following improvements:(i)rebalancing weights are used to enhance the consistency between the heatmaps of an original face sample and its horizontally flipped counterpart;(ii)coefficient factors are incorporated into the standard cross entropy loss function,and rebalancing weights are incorporated to fine-tune the loss adjustment.Experimental results indicate that the FER model outperforms the current leading algorithm,MEK,achieving 0.69%and 2.01%increases in overall and average recognition accuracies,respectively,on the RAF-DB dataset.The model exhibits accuracy improvements of 0.49%and 1.01%in the AffectNet dataset and 0.83%and 1.23%in the FERPlus dataset,respectively.These outcomes validate the superiority and stability of the proposed FER model.
基金supported by the National Key Research and Development Program of China(2022YFC3202104)the Western LightKey Laboratory Cooperative Research Cross-Team Project of Chinese Academy of Sciences(xbzg-zdsys-202207)。
文摘Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2501).
文摘The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst random perturbations,and processing efficiency.Because of their simplicity,conventional numerical techniques like the Euler-Maruyama method are frequently employed to solve stochastic differential equations;nonetheless,they may have low-order accuracy and lower stability in stiff or high-resolution situations.This study proposes a novel computational scheme for solving SPDEs arising from a stochastic SEIR model with q-diffusion and a general incidence rate function.A proposed computational scheme can be used to solve stochastic partial differential equations.For spatial discretization,a compact scheme is chosen.The compact scheme can provide a sixth-order accurate solution.The proposed scheme can be considered an extension of the Euler Maruyama method.Stability and consistency in the mean square sense are also provided.For application purposes,the stochastic SEIR model is considered using q-diffusion effects.The scheme is used to solve the stochastic model and compared with the Euler-Maruyama method.The scheme is also compared with nonstandard finite difference method for solving deterministic models.In both cases,it performs better than existing schemes.Incorporating q-diffusion further enhanced the model’s ability to represent realistic spatial-temporal disease dynamics,especially in scenarios where classical diffusion is insufficient.
基金supported in part by the National Key R&D Program of China under project 2022YFB2702901the Guangxi Natural Science Foundation under grants 2024GXNSFDA010064 and 2024GXNSFAA010453+5 种基金the National Natural Science Foundation of China under projects 62172119,62362013,U21A20467 and 72192801Zhejiang Provincial Natural Science Foundation of China under grant LZ23F020012Innovation Project of GUET Graduate Education under grants 2023YCXS070the Guangxi Young Teachers'Basic Ability Improvement Program under grant 2024KY0224Lion Rock Labs of Cyberspace Security under grant LRL24-1-C003one of the research outcomes of the Xiong'an Autonomous and Controllable Blockchain Underlying Technology Platform Project(2020).
文摘The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.
文摘This study introduces a novel bargaining solution termed the"'min-distance bargaining solution"and applies it to a differential games model.A comprehensive algorithm for implementing this new solution is presented,considering its time consistency within the differential games framework.Realistic scenarios are carefully analyzed to derive insightful findings regarding the mindistance solution,which are further validated through simulations using the resource extraction differential games model.Specifically,we examine scenarios such as managing a finite resource stock in the resource extraction game.Furthermore,a comparative analysis is conducted,pitting the mindistance bargaining solution against well-established alternatives such as Nash bargaining,Kalai-Smorodinsky,and Egalitarian solutions.By subjecting these solutions to numerical evaluations,the study offers valuable insights into decision-making processes.The findings not only contribute to negotiation theory by providing theoretical support but also have practical implications for decision-makers seeking effective strategies.This research significantly advances the field of negotiation theory,particularly in the context of differential games.The proposed min-distance bargaining solution demonstrates its applicability to real-world scenarios and enhances our understanding of strategic decision-making.
基金National Natural Science Foundation of China under grant (62071281)Local Science and Technology Development Fund Project Guided by the Central Government under grant (YDZJSX2021A003)。
文摘Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by The Ministry of Education(NRF-2020R1I1A2063567)。
文摘In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,we examined the structural characteristics and variability of female bubbling calls among four Cuculus species(Common Cuckoo C.canorus,Oriental Cuckoo C.optatus,Indian Cuckoo C.micropterus,and Lesser Cuckoo C.poliocephalus)breeding in South Korea.Comprehensive acoustic analyses of seven call parameters,using recordings from 2021 to 2023,were conducted to quantify the characteristics of their calls and compare withinand between-individual variability across species.Significant differences were found across all call parameters,with the Common Cuckoo producing the highest number of notes and the Oriental Cuckoo the lowest-frequency calls.Despite these differences,the overall structure of the calls remained acoustically similar,with overlapping characteristics across species.Furthermore,female Common Cuckoos exhibited greater within-individual variability in their calls,while the other species showed higher between-individual variability,which may further complicate species identification based vocalization alone.These findings highlight the complexities of female vocalizations in Cuculus cuckoos and suggest that ecological,social,and evolutionary factors may contribute to this vocal variability.
基金supported by the Research Funding of Hangzhou International Innovation Institute of Beihang University,China(No.2024KQ143).
文摘Distributed ducted propellers hold significant promise for propulsion systems in Advanced Air Mobility(AAM) due to their high efficiency, low noise, and enhanced redundancy and safety. However, a standardized benchmark for comparing the aerodynamic characteristics of different ducted propeller configurations remains lacking. Including additional ducted propellers can further complicate the flow field. This paper proposes an equivalent design method for ducted propellers based on the momentum theorem and similarity criteria, introducing three equivalent ducted propeller cases. Transient numerical simulations are conducted using the sliding mesh model. The three cases produce comparable thrust while consuming the same power, with the volume of distributed ducted propellers being reduced by over 29% compared to the single ducted propeller. This study investigates the effect of rotational frequency on aerodynamic performance under hovering conditions. While propeller performance demonstrates low sensitivity to variations in rotational frequency, duct performance exhibits high sensitivity. The research further examines how rotational frequency changes the pressure difference between the duct leading edge and trailing edge. Based on a sensitivity analysis of aerodynamic performance, the flow field mechanisms under different rotational consistency are examined for the case with one duct and two propellers. Differences in aerodynamic performance are attributed to the airflow velocity gradient differences at the duct leading edge and the flow separation characteristics on the crossing side. These findings are significant for enhancing the performance of distributed ducted propellers and improving aircraft controllability.
文摘This opinion article discusses the original research work of Yünkül et al.(the Authors)published in the Journal of Mountain Science 21(9):3108–3122.Employing non-linear regression,fuzzy logic and artificial neural network modeling techniques,the Authors interrogated a large database assembled from the existing research literature to assess the performance of twelve equation rules in predicting the undrained shear strength(s_(u))mobilized for remolded fine-grained soils at different values of liquidity index(I_(L))and water content ratio.Based on their analyses,the Authors proposed a simple and reportedly reliable correlation(i.e.,Eq.9 in their paper)for predicting s_(u) over the I_(L) range of 0.15 to 3.00.This article describes various shortcomings in the Authors’assembled database(including potentially anomalous data and covering an excessively wide I_(L) range in relation to routine geotechnical and transportation engineering applications)and their proposed s_(u)=f(I_(L))correlation.Contrary to the Authors’assertions,their proposed correlation is not reliable for fine-grained soils with consistencies in the general firm to stiff range(i.e.,for 0.15<I_(L)<0.40),increasingly overestimating s_(u) for reducing I_(L),and eventually predicting s_(u)→+∞for I_(L)→0.15+(while producing mathematically undefined s_(u) for I_(L)<0.15),thus rendering their correlation unconservative and potentially leading to unsafe geotechnical designs.Exponential or regular-power type s_(u)=f(I_(L))models are more s_(u)itable when developing correlations that are applicable over the full plastic range(of 0<I_(L)<1),thereby providing reasonably conservative s_(u) predictions for use in the preliminary design for routine geotechnical engineering applications.
文摘The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficulty effectively processing and fully representing their spatiotemporal complexity patterns.The article also discusses a potential path of AI development in the engineering domain.Based on the existing understanding of the principles of multilevel com-plexity,this article suggests that consistency among the logical structures of datasets,AI models,model-building software,and hardware will be an important AI development direction and is worthy of careful consideration.
基金supported by the National Natural Science Foundation of China(Nos.52408435,52278384)。
文摘Ground response analysis and determination of site-specific ground motion parameters are necessary for evaluating seismic loads to enable sustainable design of aboveground and underground structures,particularly in deep overburden sites.This study investigates the influence of bedrock interface conditions and depth of soil deposits on obtained site-specific ground motion parameters.Employing the one-dimensional seismic response analysis program SOILQUAKE,the ground responses of five representative soil profiles and 1050 case studies are calculated considering three different site models of seismic input interfaces.The analysis employs the actual bedrock interface with a shear wave velocity of 760 m/s as the reference input bedrock interface.The results illustrate that the selection of the bedrock interface condition significantly affects the seismic response on the ground surface of deep overburden sites.Specifically,the ground surface acceleration response spectra at longer periods are notably smaller compared to those at the actual bedrock site.This may present a challenge for designing long-period high-rise buildings situated in deep overburden sites.It is recommended to select a seismic input bedrock interface closely approximating the actual bedrock depth when conducting seismic response analyses for deep overburden sites.
基金supported by the National Natural Science Foundation of China(No.42207175)。
文摘The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.
文摘In real industrial scenarios, equipment cannot be operated in a faulty state for a long time, resulting in a very limited number of available fault samples, and the method of data augmentation using generative adversarial networks for smallsample data has achieved a wide range of applications. However, the current generative adversarial networks applied in industrial processes do not impose realistic physical constraints on the generation of data, resulting in the generation of data that do not have realistic physical consistency. To address this problem, this paper proposes a physical consistency-based WGAN, designs a loss function containing physical constraints for industrial processes, and validates the effectiveness of the method using a common dataset in the field of industrial process fault diagnosis. The experimental results show that the proposed method not only makes the generated data consistent with the physical constraints of the industrial process, but also has better fault diagnosis performance than the existing GAN-based methods.
基金supported by the National Natural Science Foundation of China under Grant Nos.12175148 and 11975156。
文摘In this paper,the Drinfeld-Sokolov-Satsuma-Hirota(DSSH)system is studied by using residual symmetry and the consistent Riccati expansion(CRE)method,respectively.The residual symmetry of the DSSH system is localized to Lie point symmetry in a properly prolonged system,based on which we get a new Bäcklund transformation for this system.New symmetry reduction solutions of the DSSH system are obtained by applying the classical Lie group approach on the prolonged system.Moreover,the DSSH system proves to be CRE integrable and new interesting interaction solutions between solitons and periodic waves are generated and analyzed.
基金sponsored by the National Natural Science Foundation of China Grant No.62271302the Shanghai Municipal Natural Science Foundation Grant 20ZR1423500.
文摘Large amounts of labeled data are usually needed for training deep neural networks in medical image studies,particularly in medical image classification.However,in the field of semi-supervised medical image analysis,labeled data is very scarce due to patient privacy concerns.For researchers,obtaining high-quality labeled images is exceedingly challenging because it involves manual annotation and clinical understanding.In addition,skin datasets are highly suitable for medical image classification studies due to the inter-class relationships and the inter-class similarities of skin lesions.In this paper,we propose a model called Coalition Sample Relation Consistency(CSRC),a consistency-based method that leverages Canonical Correlation Analysis(CCA)to capture the intrinsic relationships between samples.Considering that traditional consistency-based models only focus on the consistency of prediction,we additionally explore the similarity between features by using CCA.We enforce feature relation consistency based on traditional models,encouraging the model to learn more meaningful information from unlabeled data.Finally,considering that cross-entropy loss is not as suitable as the supervised loss when studying with imbalanced datasets(i.e.,ISIC 2017 and ISIC 2018),we improve the supervised loss to achieve better classification accuracy.Our study shows that this model performs better than many semi-supervised methods.
基金supported by the National Natural Science Foundation of China (Nos. 62276204, 62203343)。
文摘This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.
基金This paper is funded by Project Information:2023 Guangdong Undergraduate Colleges and Universities Teaching Quality and Teaching Reform Project Construction Project,Project Name:Action Research on Whole-area Nurturing of English Reading Teaching in Universities,Secondary and Primary Schools under the Perspective of Discipline Nurturing.Project serial number:895.
文摘The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.
