Let B^(H) be a fractional Brownian motion with Hurst index 1/2≤H<1.In this paper,we consider the equation(called the Ornstein-Uhlenbeck process with a linear self-repelling drift)dX_(t)^(H)=dB_(t)^(H)+σ X_(t)^(H)...Let B^(H) be a fractional Brownian motion with Hurst index 1/2≤H<1.In this paper,we consider the equation(called the Ornstein-Uhlenbeck process with a linear self-repelling drift)dX_(t)^(H)=dB_(t)^(H)+σ X_(t)^(H)dt+vdt-θ(∫_(0)^(t)(X_(t)^(H)-X_(s)^(H))ds)dt,whereθ<0,σ,v∈ℝ.The process is an analogue of self-attracting diffusion(Cranston,Le Jan.Math Ann,1995,303:87–93).Our main aim is to study the large time behaviors of the process.We show that the solution X^(H)diverges to infinity as t tends to infinity,and obtain the speed at which the process X^(H)diverges to infinity.展开更多
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ...The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.展开更多
Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transp...Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.展开更多
Dear Editor,This letter presents an intelligent small sample defect detection of concrete surface using novel deep learning integrating the improved YOLOv5 based on the Wasserstein GAN(WGAN)enhancement algorithm.The p...Dear Editor,This letter presents an intelligent small sample defect detection of concrete surface using novel deep learning integrating the improved YOLOv5 based on the Wasserstein GAN(WGAN)enhancement algorithm.The proposed method is capable of producing top-notch data sets to address the issues of insufficient samples and substandard quality.展开更多
There are three distinct genetic systems in higher plants,the dominant nuclear genome and the semi-autonomous organelle genomes(plastids and mitochondria).In contrast to the conserved plastid genome(plastome),the plan...There are three distinct genetic systems in higher plants,the dominant nuclear genome and the semi-autonomous organelle genomes(plastids and mitochondria).In contrast to the conserved plastid genome(plastome),the plant mitochondrial genome(mitogenome)is characterized by an intriguing“evolutionary paradox”distinguished by a remarkably low mutation rate but with a significantly high rearrangement rate(Palmer and Herbon,1988;Lai et al.,2022).展开更多
An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX base...An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible,in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition,respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative.展开更多
Evacuation assistants are expected to spread the escape route information and lead evacuees toward the exit as quickly as possible. Their leading behavior influences the evacuees' movement directly, which is confi...Evacuation assistants are expected to spread the escape route information and lead evacuees toward the exit as quickly as possible. Their leading behavior influences the evacuees' movement directly, which is confirmed to be a decisive factor of the evacuation efficiency. The transmission process of escape information and its function on the evacuees' movement are accurately presented by the proposed extended dynamic communication field model. For evacuation assistants and eevacuees, their sensitivity parameter of static floor field(SFF), kL S, and kS, are fully discussed. The simulation results e indicate that the appropriate kL Sis associated with the maximum kSof evacuees. The optimal combinations of kL Sand e kSwere found to reach the highest evacuation efficiency. There also exists an optimal value for evacuation assistants' information transmission radius.展开更多
The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these p...The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.展开更多
Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown th...Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.展开更多
Wireless technology is a new emerging delivery networks and development scheme of wireless internet is given widely attention currently. In order to make international visitors to surge education website at any time, ...Wireless technology is a new emerging delivery networks and development scheme of wireless internet is given widely attention currently. In order to make international visitors to surge education website at any time, anywhere by mobile handsets. The communication method of web database, such as CGI, ISAPI, JDBC and so on have been aralyzed and a new Active Server Page &Wireless Makeup Language (ASP-WML) based approach is presented. The dynamical refreshment of the homepage of wireless website and the automatic query of main information have been realized. At last, the wireless website of Dong Hua University is taken as an example to testify the possibility of wireless website design which is mentioned above.展开更多
Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study,a kind of intelligent garment coordination and try-on system for fashi...Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study,a kind of intelligent garment coordination and try-on system for fashion retailing was proposed. Radio Frequency Identification (RFID) technology was used to identify customer and garment item automatically. The intelligent procedure for garment coordination recommendation using Artificial Neural Network (ANN) was developed to imitate fashion designers' decision-making on garment coordination. Virtual try-on algorithm based on the customer's 2D image was accomplished using image-warping technique. The system architecture and the software framework were also described. The results show that the system is a practical and useful application for fashion retailers.展开更多
In the emerging field of image segmentation,Fully Convolutional Networks(FCNs)have recently become prominent.However,their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparamete...In the emerging field of image segmentation,Fully Convolutional Networks(FCNs)have recently become prominent.However,their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters,which can often be a cumbersome manual task.The main aim of this study is to propose a more efficient,less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images.To this end,our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network(FCEDN).The optimization is handled by a novel Genetic Grey Wolf Optimization(G-GWO)algorithm.This algorithm employs the Genetic Algorithm(GA)to generate a diverse set of initial positions.It leverages Grey Wolf Optimization(GWO)to fine-tune these positions within the discrete search space.Testing on the Indian Diabetic Retinopathy Image Dataset(IDRiD),Diabetic Retinopathy,Hypertension,Age-related macular degeneration and Glacuoma ImageS(DR-HAGIS),and Ocular Disease Intelligent Recognition(ODIR)datasets showed that the G-GWO method outperformed four other variants of GWO,GA,and PSO-based hyperparameter optimization techniques.The proposed model achieved impressive segmentation results,with accuracy rates of 98.5%for IDRiD,98.7%for DR-HAGIS,and 98.4%,98.8%,and 98.5%for different sub-datasets within ODIR.These results suggest that the proposed hyperparameter-optimized FCEDN model,driven by the G-GWO algorithm,is more efficient than recent deep-learning models for image segmentation tasks.It thereby presents the potential for increased automation and accuracy in the segmentation of fundus images,mitigating the need for extensive manual hyperparameter adjustments.展开更多
The mass and thermal coupling makes the control of the reactive double dividing-wall distillation column(R-DDWDC) an especially challenging issue with a highly interactive nature. With reference to the separation of a...The mass and thermal coupling makes the control of the reactive double dividing-wall distillation column(R-DDWDC) an especially challenging issue with a highly interactive nature. With reference to the separation of an ideal endothermic quaternary reversible reaction with the most unfavorable ranking of relative volatilities(A + B ■ C + D with α_(A)>α_(C)>α_(D)>α_(B)), the operation rationality of the R-DDWDC is studied in this contribution. The four-point single temperature control system leads to great steady-state discrepancies in the compositions of products C and D and the reason stems essentially from the failure in keeping strictly the stoichiometric ratio between reactants A and B. A temperature plus temperature cascade control scheme is then employed to reinforce the stoichiometric ratio control and helps to secure a substantial abatement in the steady-state discrepancies. A temperature difference plus temperature cascade control scheme is finally synthesized and leads even to better performance than the most effective double temperature difference control scheme. These outcomes reveal not only the operation feasibility of the R-DDWDC but also the general significance of the proposed temperature difference plus temperature cascade control scheme to the inferential control of any other complicated distillation columns.展开更多
Purpose:This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province,China as the research sample.Design/methodology/approach:We de...Purpose:This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province,China as the research sample.Design/methodology/approach:We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings:Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations:We have to give up using some indicators because of limited data availability.There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications:The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value:Little or no research has been published about the allocative efficiency of rural information resources.The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.展开更多
Genomics research of Populus deltoides,an important timber species that is widely planted worldwide,is an important part of poplar breeding.Currently,the nuclear and chloroplast genome of P.deltoides have been sequenc...Genomics research of Populus deltoides,an important timber species that is widely planted worldwide,is an important part of poplar breeding.Currently,the nuclear and chloroplast genome of P.deltoides have been sequenced,but its mitochondrial genome(mitogenome)has not been reported.To further explore the evolution and phylogeny of P.deltoides,the mitogenome of P.deltoides I-69 was assembled using reads from Nanopore and Illumina sequencing platforms and found to consist of 802,637 bp and three circular chromosomes(336,205,280,841,and 185,591 bp)containing 58 genes(34 protein-coding genes,21 tRNA genes,and 3 rRNA genes).RNA analysis in combination with several species showed signifi cantly fewer RNA editingsites in the mitogenomes of poplar and other angiosperms than in gymnosperms.Sequence transfer analysis showed extensive mitogenome rearrangements in Populus species,and with evolution from lower to higher plants,tRNA transfer from chloroplasts to mitochondria became increasingly frequent.In a phylogenetic analysis,the evolutionary status of P.deltoides was determined,and the section Populus was supported.Our results based on the fi rst report of a multicircular conformation of the Populus mitogenome provide a basis for further study of the evolution and genetics of P.deltoides and other Populus species and for breeding programs.展开更多
This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the sy...This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the system state and attack signal simultaneously.Specifically,the proposed two observers are applicable to deal with the cases in the presence and absence of time delays during network communication.It is also shown that the proposed observers can ensure the attack estimations from different agents asymptotically converge to the same value.Sufficient conditions for guaranteeing the asymptotic convergence of the estimation errors are derived.Simulation examples are finally provided to demonstrate the effectiveness of the proposed results.展开更多
A fusion algorithm is proposed to enhance the search speed of an ant colony system(ACS)for the global path planning and overcome the challenges of the local path planning in an unmanned aerial vehicle(UAV).The ACS sea...A fusion algorithm is proposed to enhance the search speed of an ant colony system(ACS)for the global path planning and overcome the challenges of the local path planning in an unmanned aerial vehicle(UAV).The ACS search efficiency is enhanced by adopting a 16-direction 24-neighborhood search way,a safety grid search way,and an elite hybrid strategy to accelerate global convergence.Quadratic planning is performed using the moving average(MA)method.The fusion algorithm incorporates a dynamic window approach(DWA)to deal with the local path planning,sets a retracement mechanism,and adjusts the evaluation function accordingly.Experimental results in two environments demonstrate that the improved ant colony system(IACS)achieves superior planning efficiency.Additionally,the optimized dynamic window approach(ODWA)demonstrates its ability to handle multiple dynamic situations.Overall,the fusion optimization algorithm can accomplish the mixed path planning effectively.展开更多
An optimal quota-share and excess-of-loss reinsurance and investment problem is studied for an insurer who is allowed to invest in a risk-free asset and a risky asset.Especially the price process of the risky asset is...An optimal quota-share and excess-of-loss reinsurance and investment problem is studied for an insurer who is allowed to invest in a risk-free asset and a risky asset.Especially the price process of the risky asset is governed by Heston's stochastic volatility(SV)model.With the objective of maximizing the expected index utility of the terminal wealth of the insurance company,by using the classical tools of stochastic optimal control,the explicit expressions for optimal strategies and optimal value functions are derived.An interesting conclusion is found that it is better to buy one reinsurance than two under the assumption of this paper.Moreover,some numerical simulations and sensitivity analysis are provided.展开更多
The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from ne...The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspec-tives.The meme stock mania of 2021 brought together stock traders and investors that were also active on social media.This mania was in good part driven by retail investors’discussions on investment strategies that occurred on social media plat-forms such as Reddit during the COVID-19 lockdowns.The stock trades by these retail investors were then executed using services like Robinhood.In this paper,machine learning models are used to try and predict the stock price movements of two meme stocks:GameStop($GME)and AMC Entertainment($AMC).Two sentiment metrics of the daily social media discussions about these stocks on Red-dit are generated and used together with 85 other fundamental and technical indi-cators as the feature set for the machine learning models.It is demonstrated that through the use of a carefully chosen mix of a meme stock’s fundamental indica-tors,technical indicators,and social media sentiment scores,it is possible to pre-dict the stocks’next-day closing prices.Also,using an anomaly detection model,and the daily Reddit discussions about a meme stock,it was possible to identify potential market manipulators.展开更多
文摘Let B^(H) be a fractional Brownian motion with Hurst index 1/2≤H<1.In this paper,we consider the equation(called the Ornstein-Uhlenbeck process with a linear self-repelling drift)dX_(t)^(H)=dB_(t)^(H)+σ X_(t)^(H)dt+vdt-θ(∫_(0)^(t)(X_(t)^(H)-X_(s)^(H))ds)dt,whereθ<0,σ,v∈ℝ.The process is an analogue of self-attracting diffusion(Cranston,Le Jan.Math Ann,1995,303:87–93).Our main aim is to study the large time behaviors of the process.We show that the solution X^(H)diverges to infinity as t tends to infinity,and obtain the speed at which the process X^(H)diverges to infinity.
基金supported in part by the National Natural Science Foundation of China (62233012,62273087)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Shanghai Pujiang Program of China (22PJ1400400)。
文摘The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.
基金the National Natural Science Foundation of China(Nos.62272063,62072056 and 61902041)the Natural Science Foundation of Hunan Province(Nos.2022JJ30617 and 2020JJ2029)+4 种基金Open Research Fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology,Nanjing University of Posts and Telecommunications(No.JZNY202102)the Traffic Science and Technology Project of Hunan Province,China(No.202042)Hunan Provincial Key Research and Development Program(No.2022GK2019)this work was funded by the Researchers Supporting Project Number(RSPD2023R681)King Saud University,Riyadh,Saudi Arabia.
文摘Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.
基金supported by the National Natural Science Foundation of China(21978013)the Fundamental Research Funds for the Central in China(XK1802-4)。
文摘Dear Editor,This letter presents an intelligent small sample defect detection of concrete surface using novel deep learning integrating the improved YOLOv5 based on the Wasserstein GAN(WGAN)enhancement algorithm.The proposed method is capable of producing top-notch data sets to address the issues of insufficient samples and substandard quality.
基金The work is supported by the Natural Science Foundation of Jiangsu Province(BK20220414)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB220003).
文摘There are three distinct genetic systems in higher plants,the dominant nuclear genome and the semi-autonomous organelle genomes(plastids and mitochondria).In contrast to the conserved plastid genome(plastome),the plant mitochondrial genome(mitogenome)is characterized by an intriguing“evolutionary paradox”distinguished by a remarkably low mutation rate but with a significantly high rearrangement rate(Palmer and Herbon,1988;Lai et al.,2022).
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.11572084,11472061,71371046 and 61603088)the Fundamental Research Funds for the Central Universities and DHU Distinguished Young Professor Program(Grant No.16D210404)the China Scholarship Council(CSC)
文摘An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible,in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition,respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative.
基金Project supported by the National Basic Research Program of China(Grant No.2011CB706900)the National Natural Science Foundation of China(Grant Nos.71225007 and 71203006)+2 种基金the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(Grant No.2012BAK13B06)the Humanities and Social Sciences Project of the Ministry of Education of China(Grant Nos.10YJA630221 and 12YJCZH023)the Beijing Philosophy and Social Sciences Planning Project of the Twelfth Five-Year Plan,China(Grant Nos.12JGC090 and 12JGC098)
文摘Evacuation assistants are expected to spread the escape route information and lead evacuees toward the exit as quickly as possible. Their leading behavior influences the evacuees' movement directly, which is confirmed to be a decisive factor of the evacuation efficiency. The transmission process of escape information and its function on the evacuees' movement are accurately presented by the proposed extended dynamic communication field model. For evacuation assistants and eevacuees, their sensitivity parameter of static floor field(SFF), kL S, and kS, are fully discussed. The simulation results e indicate that the appropriate kL Sis associated with the maximum kSof evacuees. The optimal combinations of kL Sand e kSwere found to reach the highest evacuation efficiency. There also exists an optimal value for evacuation assistants' information transmission radius.
文摘The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.
基金supported by the National Natural Science Foundation of China (22078004)the Research Development Fund from Xi’an Jiaotong-Liverpool University (RDF-16-02-03 and RDF15-01-23)key program special fund (KSF-E-03)。
文摘Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.
文摘Wireless technology is a new emerging delivery networks and development scheme of wireless internet is given widely attention currently. In order to make international visitors to surge education website at any time, anywhere by mobile handsets. The communication method of web database, such as CGI, ISAPI, JDBC and so on have been aralyzed and a new Active Server Page &Wireless Makeup Language (ASP-WML) based approach is presented. The dynamical refreshment of the homepage of wireless website and the automatic query of main information have been realized. At last, the wireless website of Dong Hua University is taken as an example to testify the possibility of wireless website design which is mentioned above.
基金National Nature Science Foundations of China (No.60975059, No.60775052)Specialized Research Fund for the Doctoral Program of Higher Education from Ministry of Education of China (No.20090075110002)Projects of Shanghai Committee of Science and Technology, China (No.09JC1400900, No.08JC1400100, No.10DZ0506500)
文摘Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study,a kind of intelligent garment coordination and try-on system for fashion retailing was proposed. Radio Frequency Identification (RFID) technology was used to identify customer and garment item automatically. The intelligent procedure for garment coordination recommendation using Artificial Neural Network (ANN) was developed to imitate fashion designers' decision-making on garment coordination. Virtual try-on algorithm based on the customer's 2D image was accomplished using image-warping technique. The system architecture and the software framework were also described. The results show that the system is a practical and useful application for fashion retailers.
基金supported in part by the National Natural Science Foundation of China under Grant 11527801 and 41706201.
文摘In the emerging field of image segmentation,Fully Convolutional Networks(FCNs)have recently become prominent.However,their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters,which can often be a cumbersome manual task.The main aim of this study is to propose a more efficient,less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images.To this end,our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network(FCEDN).The optimization is handled by a novel Genetic Grey Wolf Optimization(G-GWO)algorithm.This algorithm employs the Genetic Algorithm(GA)to generate a diverse set of initial positions.It leverages Grey Wolf Optimization(GWO)to fine-tune these positions within the discrete search space.Testing on the Indian Diabetic Retinopathy Image Dataset(IDRiD),Diabetic Retinopathy,Hypertension,Age-related macular degeneration and Glacuoma ImageS(DR-HAGIS),and Ocular Disease Intelligent Recognition(ODIR)datasets showed that the G-GWO method outperformed four other variants of GWO,GA,and PSO-based hyperparameter optimization techniques.The proposed model achieved impressive segmentation results,with accuracy rates of 98.5%for IDRiD,98.7%for DR-HAGIS,and 98.4%,98.8%,and 98.5%for different sub-datasets within ODIR.These results suggest that the proposed hyperparameter-optimized FCEDN model,driven by the G-GWO algorithm,is more efficient than recent deep-learning models for image segmentation tasks.It thereby presents the potential for increased automation and accuracy in the segmentation of fundus images,mitigating the need for extensive manual hyperparameter adjustments.
基金the financial support from National Natural Science Foundation of China (21878011)。
文摘The mass and thermal coupling makes the control of the reactive double dividing-wall distillation column(R-DDWDC) an especially challenging issue with a highly interactive nature. With reference to the separation of an ideal endothermic quaternary reversible reaction with the most unfavorable ranking of relative volatilities(A + B ■ C + D with α_(A)>α_(C)>α_(D)>α_(B)), the operation rationality of the R-DDWDC is studied in this contribution. The four-point single temperature control system leads to great steady-state discrepancies in the compositions of products C and D and the reason stems essentially from the failure in keeping strictly the stoichiometric ratio between reactants A and B. A temperature plus temperature cascade control scheme is then employed to reinforce the stoichiometric ratio control and helps to secure a substantial abatement in the steady-state discrepancies. A temperature difference plus temperature cascade control scheme is finally synthesized and leads even to better performance than the most effective double temperature difference control scheme. These outcomes reveal not only the operation feasibility of the R-DDWDC but also the general significance of the proposed temperature difference plus temperature cascade control scheme to the inferential control of any other complicated distillation columns.
基金jointly supported by National Soft Science Research Program(Grant No.:2011GXQ4D048)the Fundamental Research Foundation for the Central Universities(Grant No.:KYZ201133)the Foundation for Humanities and Social Sciences of Jiangsu Province(Grant No.:11TQB005)
文摘Purpose:This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province,China as the research sample.Design/methodology/approach:We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings:Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations:We have to give up using some indicators because of limited data availability.There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications:The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value:Little or no research has been published about the allocative efficiency of rural information resources.The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.
基金funded by the National Key Research and Development Program of China[Grant Number 2021YFD2201205]the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Genomics research of Populus deltoides,an important timber species that is widely planted worldwide,is an important part of poplar breeding.Currently,the nuclear and chloroplast genome of P.deltoides have been sequenced,but its mitochondrial genome(mitogenome)has not been reported.To further explore the evolution and phylogeny of P.deltoides,the mitogenome of P.deltoides I-69 was assembled using reads from Nanopore and Illumina sequencing platforms and found to consist of 802,637 bp and three circular chromosomes(336,205,280,841,and 185,591 bp)containing 58 genes(34 protein-coding genes,21 tRNA genes,and 3 rRNA genes).RNA analysis in combination with several species showed signifi cantly fewer RNA editingsites in the mitogenomes of poplar and other angiosperms than in gymnosperms.Sequence transfer analysis showed extensive mitogenome rearrangements in Populus species,and with evolution from lower to higher plants,tRNA transfer from chloroplasts to mitochondria became increasingly frequent.In a phylogenetic analysis,the evolutionary status of P.deltoides was determined,and the section Populus was supported.Our results based on the fi rst report of a multicircular conformation of the Populus mitogenome provide a basis for further study of the evolution and genetics of P.deltoides and other Populus species and for breeding programs.
基金supported by the Fundamental Research Funds for the Central Universities(buctrc202201)High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology。
文摘This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the system state and attack signal simultaneously.Specifically,the proposed two observers are applicable to deal with the cases in the presence and absence of time delays during network communication.It is also shown that the proposed observers can ensure the attack estimations from different agents asymptotically converge to the same value.Sufficient conditions for guaranteeing the asymptotic convergence of the estimation errors are derived.Simulation examples are finally provided to demonstrate the effectiveness of the proposed results.
基金National Natural Science Foundation of China(No.62241503)Natural Science Foundation of Shanghai,China(No.22ZR1401400)。
文摘A fusion algorithm is proposed to enhance the search speed of an ant colony system(ACS)for the global path planning and overcome the challenges of the local path planning in an unmanned aerial vehicle(UAV).The ACS search efficiency is enhanced by adopting a 16-direction 24-neighborhood search way,a safety grid search way,and an elite hybrid strategy to accelerate global convergence.Quadratic planning is performed using the moving average(MA)method.The fusion algorithm incorporates a dynamic window approach(DWA)to deal with the local path planning,sets a retracement mechanism,and adjusts the evaluation function accordingly.Experimental results in two environments demonstrate that the improved ant colony system(IACS)achieves superior planning efficiency.Additionally,the optimized dynamic window approach(ODWA)demonstrates its ability to handle multiple dynamic situations.Overall,the fusion optimization algorithm can accomplish the mixed path planning effectively.
基金National Natural Science Foundation of China(No.62073071)Fundamental Research Funds for the Central Universities and Graduate Student Innovation Fund of Donghua University,China(No.CUSF-DH-D-2021045)。
文摘An optimal quota-share and excess-of-loss reinsurance and investment problem is studied for an insurer who is allowed to invest in a risk-free asset and a risky asset.Especially the price process of the risky asset is governed by Heston's stochastic volatility(SV)model.With the objective of maximizing the expected index utility of the terminal wealth of the insurance company,by using the classical tools of stochastic optimal control,the explicit expressions for optimal strategies and optimal value functions are derived.An interesting conclusion is found that it is better to buy one reinsurance than two under the assumption of this paper.Moreover,some numerical simulations and sensitivity analysis are provided.
文摘The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspec-tives.The meme stock mania of 2021 brought together stock traders and investors that were also active on social media.This mania was in good part driven by retail investors’discussions on investment strategies that occurred on social media plat-forms such as Reddit during the COVID-19 lockdowns.The stock trades by these retail investors were then executed using services like Robinhood.In this paper,machine learning models are used to try and predict the stock price movements of two meme stocks:GameStop($GME)and AMC Entertainment($AMC).Two sentiment metrics of the daily social media discussions about these stocks on Red-dit are generated and used together with 85 other fundamental and technical indi-cators as the feature set for the machine learning models.It is demonstrated that through the use of a carefully chosen mix of a meme stock’s fundamental indica-tors,technical indicators,and social media sentiment scores,it is possible to pre-dict the stocks’next-day closing prices.Also,using an anomaly detection model,and the daily Reddit discussions about a meme stock,it was possible to identify potential market manipulators.
