REVO?is a dynamic measuring head and probe system,which is designed and applied in orthogonal coordinatemeasuring machines(CMMs)to maximize measurement throughput whilst maintaining high system accuracy.A calibration ...REVO?is a dynamic measuring head and probe system,which is designed and applied in orthogonal coordinatemeasuring machines(CMMs)to maximize measurement throughput whilst maintaining high system accuracy.A calibration approachto the stylus deformation of REVO head is proposed and the scale value of each CMM axis is separated from the limiteddata returned from the measuring system according to the application of REVO head in non-orthogonal CMM.Experimentsshow that the calibration method presented and extraction of scale value are of effectiveness and correctness.Results demonstratethat the maximum measurement error has decreased from0.2021mm to0.0009mm and the variation of scale value ofeach CMM axis is two orders lower after the stylus deformation is compensated.展开更多
[ Objective] Computer image processing technology was used to distinguish the angular leaf spot and spotted disease in the agricultural production. [Method] The computer vision technology was used to carry out chromat...[ Objective] Computer image processing technology was used to distinguish the angular leaf spot and spotted disease in the agricultural production. [Method] The computer vision technology was used to carry out chromatic research on the plant pathological characteristics. The color and texture were taken as the plant disease image characteristic parameter to extract the perimeter, area and the shape of the lesion image, thus carrying out the classification judgment on the disease image. [ Result] C IE1976H IS chorma percentage histogram method was adopted to extract chromaticity characteristic parameters, the process was simple and effective with fast operation speed, eliminating the effect of leaf size and shape. The statistical characteristic parameter of chorma histogram was analyzed to obtain chroma skewness, which could significantly distinguish different symptoms of disease. [ Conclusion] The study suggested that chroma skewness could be adopted as the characteristic parameter to distinguish spotted disease with angular leaf spot.展开更多
The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as...The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as Transaction Order Dependence(TOD),Blockchain Extractable Value(BEV),and Transaction Importance Diversity(TID),which collectively undermine the fairness and security of DeFi systems.BEV-related activities,including sandwich attacks,liquidations,transaction replay etc.have emerged as significant threats,collectively generating$540.54 million in losses over 32 months across 11,289 addresses,involving 49,691 cryptocurrencies and 60,830 on-chain markets.These attacks exploit transaction mechanics to manipulate asset prices and extract value at the expense of other participants,with sandwich attacks being particularly impactful.Additionally,the growing adoption of blockchain in traditional finance highlights the challenge of TID,wherein high transaction volumes can strain systems and compromise time-sensitive operations.To address these pressing issues,we propose a novel Distributed Transaction Sequencing Strategy(DTSS)that integrates forking mechanisms with an Analytic Hierarchy Process(AHP)to enforce fair and transparent transaction ordering in a decentralized manner.Our approach is further enhanced by an optimization framework and the introduction of a Normalized Allocation Disparity Metric(NADM)that ensures optimal parameter selection for transaction prioritization.Experimental evaluations demonstrated that the DTSS effectively mitigated BEV risks,enhanced transaction fairness,and significantly improved the security and transparency of DeFi ecosystems.展开更多
基金National Natural Science Foundation of China(No.51375338)
文摘REVO?is a dynamic measuring head and probe system,which is designed and applied in orthogonal coordinatemeasuring machines(CMMs)to maximize measurement throughput whilst maintaining high system accuracy.A calibration approachto the stylus deformation of REVO head is proposed and the scale value of each CMM axis is separated from the limiteddata returned from the measuring system according to the application of REVO head in non-orthogonal CMM.Experimentsshow that the calibration method presented and extraction of scale value are of effectiveness and correctness.Results demonstratethat the maximum measurement error has decreased from0.2021mm to0.0009mm and the variation of scale value ofeach CMM axis is two orders lower after the stylus deformation is compensated.
基金Supported by Natural Science Foundation in Education Department of Henan Province(2008B210001)~~
文摘[ Objective] Computer image processing technology was used to distinguish the angular leaf spot and spotted disease in the agricultural production. [Method] The computer vision technology was used to carry out chromatic research on the plant pathological characteristics. The color and texture were taken as the plant disease image characteristic parameter to extract the perimeter, area and the shape of the lesion image, thus carrying out the classification judgment on the disease image. [ Result] C IE1976H IS chorma percentage histogram method was adopted to extract chromaticity characteristic parameters, the process was simple and effective with fast operation speed, eliminating the effect of leaf size and shape. The statistical characteristic parameter of chorma histogram was analyzed to obtain chroma skewness, which could significantly distinguish different symptoms of disease. [ Conclusion] The study suggested that chroma skewness could be adopted as the characteristic parameter to distinguish spotted disease with angular leaf spot.
基金funded by the University of Macao(file no.MYRG2022-00162-FST and MYRG2019-00136-FST).
文摘The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as Transaction Order Dependence(TOD),Blockchain Extractable Value(BEV),and Transaction Importance Diversity(TID),which collectively undermine the fairness and security of DeFi systems.BEV-related activities,including sandwich attacks,liquidations,transaction replay etc.have emerged as significant threats,collectively generating$540.54 million in losses over 32 months across 11,289 addresses,involving 49,691 cryptocurrencies and 60,830 on-chain markets.These attacks exploit transaction mechanics to manipulate asset prices and extract value at the expense of other participants,with sandwich attacks being particularly impactful.Additionally,the growing adoption of blockchain in traditional finance highlights the challenge of TID,wherein high transaction volumes can strain systems and compromise time-sensitive operations.To address these pressing issues,we propose a novel Distributed Transaction Sequencing Strategy(DTSS)that integrates forking mechanisms with an Analytic Hierarchy Process(AHP)to enforce fair and transparent transaction ordering in a decentralized manner.Our approach is further enhanced by an optimization framework and the introduction of a Normalized Allocation Disparity Metric(NADM)that ensures optimal parameter selection for transaction prioritization.Experimental evaluations demonstrated that the DTSS effectively mitigated BEV risks,enhanced transaction fairness,and significantly improved the security and transparency of DeFi ecosystems.
