In wireless sensor networks,ensuring communication security via specific emitter identification(SEI)is crucial.However,existing SEI methods are limited to closed-set scenarios and lack the ability to detect unknown de...In wireless sensor networks,ensuring communication security via specific emitter identification(SEI)is crucial.However,existing SEI methods are limited to closed-set scenarios and lack the ability to detect unknown devices and perform classincremental training.This study proposes a class-incremental open-set SEI approach.The open-set SEI model calculates radiofrequency fingerprints(RFFs)prototypes for known signals and employs a self-attention mechanism to enhance their discriminability.Detection thresholds are set through Gaussian fitting for each class.For class-incremental learning,the algorithm freezes the parameters of the previously trained model to initialize the new model.It designs specific losses:the RFFs extraction distribution difference loss and the prototype transformation distribution difference loss,which force the new model to retain old knowledge while learning new knowledge.The training loss enables learning of new class RFFs.Experimental results demonstrate that the open-set SEI model achieves state-of-theart performance and strong noise robustness.Moreover,the class-incremental learning algorithm effectively enables the model to retain old device RFFs knowledge,acquire new device RFFs knowledge,and detect unknown devices simultaneously.展开更多
Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint featur...Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.展开更多
This study aimed to clarify the pathogen composition,biological characteristics,infection patterns,and effective control agents for panicle blight of rice in Heilongjiang Province.Diseased panicles were collected from...This study aimed to clarify the pathogen composition,biological characteristics,infection patterns,and effective control agents for panicle blight of rice in Heilongjiang Province.Diseased panicles were collected from different rice-growing areas in Heilongjiang Province and subjected to tissue isolation,pathogenicity tests,morphological observation,and molecular identification.The primary pathogens identified were Fusarium graminearum,Alternaria alternata and Nigrospora oryzae.The biological characteristics of these three pathogens were systematically investigated.Pathogenicity assays revealed that F.graminearum exhibited the strongest pathogenicity,followed by A.alternata,while N.oryzae was the weakest.In vitro toxicity tests screened highly effective fungicides:75%trifloxystrobin-tebuconazole showed the best inhibitory effect against F.graminearum(EC50=0.0140μg·mL^(-1));30%tebuconazole-azoxystrobin was the most effective against A.alternata(EC50=0.0060μg·mL^(-1))and N.oryzae(EC50=0.0310μg·mL^(-1)).展开更多
Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to...Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to miniaturization of electronic components,it is challenging to directly measure or numerically predict the mechanical response of small-sized critical interconnections in board-level packaging structures to ensure the mechanical reliability of electronic devices in projectiles under harsh working conditions.To address this issue,an indirect measurement method using the Bayesian regularization-based load identification was proposed in this study based on finite element(FE)pre-dictions to estimate the load applied on critical interconnections of board-level packaging structures during the process of projectile penetration.For predicting the high-strain-rate penetration process,an FE model was established with elasto-plastic constitutive models of the representative packaging ma-terials(that is,solder material and epoxy molding compound)in which material constitutive parameters were calibrated against the experimental results by using the split-Hopkinson pressure bar.As the impact-induced dynamic bending of the printed circuit board resulted in an alternating tensile-compressive loading on the solder joints during penetration,the corner solder joints in the edge re-gions experience the highest S11 and strain,making them more prone to failure.Based on FE predictions at different structural scales,an improved Bayesian method based on augmented Tikhonov regulariza-tion was theoretically proposed to address the issues of ill-posed matrix inversion and noise sensitivity in the load identification at the critical solder joints.By incorporating a wavelet thresholding technique,the method resolves the problem of poor load identification accuracy at high noise levels.The proposed method achieves satisfactorily small relative errors and high correlation coefficients in identifying the mechanical response of local interconnections in board-level packaging structures,while significantly balancing the smoothness of response curves with the accuracy of peak identification.At medium and low noise levels,the relative error is less than 6%,while it is less than 10%at high noise levels.The proposed method provides an effective indirect approach for the boundary conditions of localized solder joints during the projectile penetration process,and its philosophy can be readily extended to other scenarios of multiscale analysis for highly nonlinear materials and structures under extreme loading conditions.展开更多
As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem su...As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem suggestions for solution according to the practical situation. （RFID） plays an important role in dairy information tracing and culture function extension of managing breeding technology, and finally put forward some展开更多
Identification of powdery mildew pathogens on melon（Cucumis melo） is important for melon breeding and diseaseresistant germplasm selection. In this study, a powdery mildew pathogen that infected melon plants in Heil...Identification of powdery mildew pathogens on melon（Cucumis melo） is important for melon breeding and diseaseresistant germplasm selection. In this study, a powdery mildew pathogen that infected melon plants in Heilongjiang Province, China, was investigated in terms of host identification, morphological characteristics and phylogenetic relationships. The morphological characteristics of the pathogen were observed at five phases in the life cycle： germinating conidia, primary germ tube, hyphae, conidiophores, and colonization. The conidia were elliptical, colorless, catenulate, and the average length was 29.07 μm and average width was 17.82 μm. One ascus and eight ascospores were produced. DNA was extracted from 0.01 g conidiophores from a strain of powdery mildew pathogen that infected melon. ITS ribosomal DNA region（524 bp） was amplified with the universal ITS1 and ITS4 primers. The nucleotide sequence showed 100% similarity with ITS sequences for three Podosphaera fusca strains obtained from the GenBank database. The identity of the pathogen was confirmed as Sphaerotheca fuliginea. International standard differential hosts were used to identify S. fuliginea strain as 2F race. These results supported the notion that Podosphaera fusca was a synonym of S. fuliginea.展开更多
Based on the specialty of major rock-forning minerals and elementary composition of metamorphite,the detailed and systematical review,analysis and summary are completed for a series of lithology and reservoir fracture...Based on the specialty of major rock-forning minerals and elementary composition of metamorphite,the detailed and systematical review,analysis and summary are completed for a series of lithology and reservoir fracture identification teehnologies with logging that are recent years.Research shows that nuclear logging series in conventional logging are more favorable to identify the metanorphie lithology.ECS(elemental capturespectrosoopy)and other new logging lechnologies can be applied to identify metamorphic lithology.Due to theolex and di-verse metamorphic lithologies,the correspending reservoir identification standard should be established for metamorphic reservoir identificat lithology identification,The applicable conventional logging methods for metamorphic reservoir fracture identification mainly incldle dual lat ging,scoustic logging,dual lateral logging-microspherical focus,borehole diameter logging,natural gamma ray spectrology baging,etc.In additie acoustic-resistivity imaging logging,multipolar array acoustic logging,cross dipole acoustic logging and other new logging tec nologies with unique ad-vantages are increasingly applied for metamorphic reservoir fractureidentification.Currently,there are no gener appli sandards for logging i-dentification of metamorphic lithology and reservoir fracture.The specific metamorphic reservoir development a field actual data in specific ar-eas should be considered to study the logging identification and evaluation.展开更多
Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass S...Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass Spectral Deconvolution and Identification System)program was used to identify parts per million(ppm)HACC concentrations in petroleum fractions in place of traditional techniques(extraction and standard injection).Polycyclic aromatic sulfur heterocycles(S-PAHs)were used as model compounds to confirm the validity of the AMDIS identifiers,which were compared with extracted results using the off-line X-calibur software.AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate.There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate.AMDIS was also used to detect nitrogen-containing compounds(NCCs)and alkylphenols in oil condensate.Our results confirmed the presence of 2-methylbenzothiazole,carbazole,and 2,4-ditertbutyl phenol.In a crude oil sample,AMDIS identification of m/z=191 biomarkers wa s consistent with empirical results.Therefore,AMDIS can help to reduce the number of experimental steps in identification protocols.展开更多
A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus...A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus and a potential target for SARS-specific cell-mediated immune responses. A pa nel of S protein-derived peptides was tested for their binding affinity to HLA -A *0201 molecules. Peptides with high affinity for HLA-A *0201 were then as se ssed for their capacity to elicit specific immune responses mediated by cytotoxi c T lymphocytes (CTLs) both in vivo, in HLA-A2.1/K b transgenic mice, a nd in vitro, from peripheral blood lymphocytes (PBLs) harvested from healthy HLA-A 2.1 + donors. SARS-CoV protein-derived peptide-1 (SSp-1 RLNEVAKNL), induced pepti de-specific CTLs both in vivo (transgenic mice) and in vitro (human PBL s), which specifically released interferon-gamma (IFN-gamma) upon stimulation with SSp-1-pulsed autologous dendritic cells (DCs) or T2 cells. SSp-1-specif ic CTLs also lysed major histocompatibility complex (MHC)-matched tumor cell lines engineered to express S proteins. HLA-A *0201-SSp-1 tetramer staining re vealed the presence of significant populations of SSp-1-specific CTLs in SSp- 1-induced CD8 + T cells. We propose that the newly identified epitope SSp-1 w ill help in the characterization of virus control mechanisms and immunopathology in SARS-CoV infection, and may be relevant to the development of immunotherape utic approaches for SARS.展开更多
A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibratio...A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.展开更多
In this study,a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory.The ADAMS software ...In this study,a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory.The ADAMS software was used to build a parameterized dynamic model of the saddle ring.A parameter identification method for the ring was proposed based on the particle swarm optimization algorithm.A loading test was designed and performed several times at different elevation angles.The response histories of the saddle ring with different loads were then obtained.The parameters of the saddle ring dynamic model were identified from statistics generated at a 500 elevation angle to verify the feasibility and accuracy of the proposed method.The actual loading history of the ring at a 70°elevation angle was taken as the model input.The response histories of the ring under these working conditions were obtained through a simulation.The simulation results agreed with the actual response.Thus,the effectiveness and applicability of the proposed dynamic model were verified,and it provides an effective method for modeling saddle rings.展开更多
An adaptive stable observer with output current online identification strategy for the auxiliary inverters applied in advanced electric trains, such as high speed railway, urban rail, subway and maglev trains, is prop...An adaptive stable observer with output current online identification strategy for the auxiliary inverters applied in advanced electric trains, such as high speed railway, urban rail, subway and maglev trains, is proposed. The designed observer is used to estimate the state variables, i.e. controllable duty ratio and current components in d-q-o rotary reference frame. The convergence of the observer estimation error is analyzed with consideration of uncertain level variation of input voltage at direct current(DC) side and sufficient conditions are given to prove its practical stability. Experimental results are shown to confirm the effectiveness of the proposed observer.展开更多
A robust fault diagnosis approach is developed by incorporating a set-membership identification (SMI) method. A class of systems with linear models in the form of fault related parameters is investigated, with model u...A robust fault diagnosis approach is developed by incorporating a set-membership identification (SMI) method. A class of systems with linear models in the form of fault related parameters is investigated, with model uncertainties and parameter variations taken into account explicitly and treated as bounded errors. An ellipsoid bounding set-membership identification algorithm is proposed to propagate bounded uncertainties rigorously and the guaranteed feasible set of faults parameters enveloping true parameter values is given. Faults arised from abrupt parameter variations can be detected and isolated on-line by consistency check between predicted and observed parameter sets obtained in the identification procedure. The proposed approach provides the improved robustness with its ability to distinguish real faults from model uncertainties, which comes with the inherent guaranteed robustness of the set-membership framework. Efforts are also made in this work to balance between conservativeness and computation complexity of the overall algorithm. Simulation results for the mobile robot with several slipping faults scenarios demonstrate the correctness of the proposed approach for faults detection and isolation (FDI).展开更多
Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS syste...Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS system in two-line breeding is laborsaving,timesaving,simple,inexpensive,efficient,and eliminating the limitations of the cytoplasmic male sterility(CMS)system.'AnnongS'is the first discovered and deeply studied TGMS rice lines in China.'AnnongS-1'and'Y58S',two derivatives of TGMS line AnnongS,were both controlled by a single recessive gene named tms5,which was genetically mapped on chromosome 2.In this study,three populations('AnnongS-1'×'Nanjing11','Y58S'×'Q611',and'Y58S'×'Guanghui122')were developed and used for the molecular fine mapping of the tms5 gene.By analyzing recombination events in the sterile individuals using a total of 125 probes covering the tms5 region,the tms5 gene was physically mapped to a 19-kb DNA fragment between two markers 4039-1 and 4039-2,which were located on the BAC clone AP004039.After the construction of the physical map between two markers 4039-1 and 4039-2,a member(ONAC023)of the NAC(NAM-ATAF-CUC-related)gene family was identified as the candidate gene of the tms5 gene.展开更多
Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network...Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network applications by optimized back-propagation (BP) neural network. Particle swarm optimization (PSO) algorithm was used to optimize the BP neural network. And in order to increase the identification performance, wavelet packet decomposition (WPD) was used to extract several hidden features from the time-frequency information of network traffic. The experimental results show that the average classification accuracy of various network applications can reach 97%. Moreover, this approach optimized by BP neural network takes 50% of the training time compared with the traditional neural network.展开更多
A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear cont...A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.展开更多
Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression mo...Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.展开更多
A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng...A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng were identified by the method.The NCFs of the three samples of Panax ginsengs were determined through two nonlinear chemical systems,namely system 1 consisting of sample components,H2SO4,MnSO4,NaBrO3,acetone and the new system,system 2 consisting of sample components,H2SO4,(NH4)4Ce(SO4)2,NaBrO3 and citric acid.The comparison between the results determined through systems 1 and 2 shows that the speed to determine NCF through system 2 is much faster than that through system 1;for systems 1 and 2,the system similarities of the same kind of samples are≥98.09%and 99.78%,respectively,while those of different kinds of samples are≤63.04%and 86.34%,respectively.The results to identify the kinds of some samples by system similarity pattern show that both the accuracies of identification methods based on single system 1 and 2 are≥95.6%,and the average values are 97.1%and 96.3%,respectively;the accuracy of the method based on double system is≥97.8%,and the average accuracy is 99.3%.The accuracy of the method based on double system is higher than that based on any single system.展开更多
Total 75 rice varieties （lines） in Heilongjiang Province （or cold region） as germplasm resources were identified for cold tolerance at germinating stage by controlling temperature in artificial incubator. The resu...Total 75 rice varieties （lines） in Heilongjiang Province （or cold region） as germplasm resources were identified for cold tolerance at germinating stage by controlling temperature in artificial incubator. The results showed that the shooting seed rate at the germinating stage could be used as the evaluation index of cold tolerance. The cold tolerance was recorded on 1-9 scale and could be identified by the criteria of five indexes such as highly tolerant （HT）, tolerant （T）, moderately tolerant （MT）, susceptible （S）, highly susceptible （HS）.展开更多
基金supported by the National Natural Science Foundation of China(62371465)Taishan Scholar Project of Shandong Province(ts201511020)。
文摘In wireless sensor networks,ensuring communication security via specific emitter identification(SEI)is crucial.However,existing SEI methods are limited to closed-set scenarios and lack the ability to detect unknown devices and perform classincremental training.This study proposes a class-incremental open-set SEI approach.The open-set SEI model calculates radiofrequency fingerprints(RFFs)prototypes for known signals and employs a self-attention mechanism to enhance their discriminability.Detection thresholds are set through Gaussian fitting for each class.For class-incremental learning,the algorithm freezes the parameters of the previously trained model to initialize the new model.It designs specific losses:the RFFs extraction distribution difference loss and the prototype transformation distribution difference loss,which force the new model to retain old knowledge while learning new knowledge.The training loss enables learning of new class RFFs.Experimental results demonstrate that the open-set SEI model achieves state-of-theart performance and strong noise robustness.Moreover,the class-incremental learning algorithm effectively enables the model to retain old device RFFs knowledge,acquire new device RFFs knowledge,and detect unknown devices simultaneously.
基金supported by the Youth Science and Technology Innovation Award of National University of Defense Technology (18/19-QNCXJ)the National Science Foundation of China (62271494)
文摘Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.
基金Supported by the Green Plant Protection Project in Heilongjiang Province(2130108)the Key R&D Program Project of Heilongjiang Province(2023ZX02B0502)the Heilongjiang Province Rice Modern Agriculture Industry Technology Collaborative Innovation System Project(2025)。
文摘This study aimed to clarify the pathogen composition,biological characteristics,infection patterns,and effective control agents for panicle blight of rice in Heilongjiang Province.Diseased panicles were collected from different rice-growing areas in Heilongjiang Province and subjected to tissue isolation,pathogenicity tests,morphological observation,and molecular identification.The primary pathogens identified were Fusarium graminearum,Alternaria alternata and Nigrospora oryzae.The biological characteristics of these three pathogens were systematically investigated.Pathogenicity assays revealed that F.graminearum exhibited the strongest pathogenicity,followed by A.alternata,while N.oryzae was the weakest.In vitro toxicity tests screened highly effective fungicides:75%trifloxystrobin-tebuconazole showed the best inhibitory effect against F.graminearum(EC50=0.0140μg·mL^(-1));30%tebuconazole-azoxystrobin was the most effective against A.alternata(EC50=0.0060μg·mL^(-1))and N.oryzae(EC50=0.0310μg·mL^(-1)).
基金supported by the National Natural Science Foundation of China(Grant Nos.52475166,52175148)the Regional Collaboration Project of Shanxi Province(Grant No.202204041101044).
文摘Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to miniaturization of electronic components,it is challenging to directly measure or numerically predict the mechanical response of small-sized critical interconnections in board-level packaging structures to ensure the mechanical reliability of electronic devices in projectiles under harsh working conditions.To address this issue,an indirect measurement method using the Bayesian regularization-based load identification was proposed in this study based on finite element(FE)pre-dictions to estimate the load applied on critical interconnections of board-level packaging structures during the process of projectile penetration.For predicting the high-strain-rate penetration process,an FE model was established with elasto-plastic constitutive models of the representative packaging ma-terials(that is,solder material and epoxy molding compound)in which material constitutive parameters were calibrated against the experimental results by using the split-Hopkinson pressure bar.As the impact-induced dynamic bending of the printed circuit board resulted in an alternating tensile-compressive loading on the solder joints during penetration,the corner solder joints in the edge re-gions experience the highest S11 and strain,making them more prone to failure.Based on FE predictions at different structural scales,an improved Bayesian method based on augmented Tikhonov regulariza-tion was theoretically proposed to address the issues of ill-posed matrix inversion and noise sensitivity in the load identification at the critical solder joints.By incorporating a wavelet thresholding technique,the method resolves the problem of poor load identification accuracy at high noise levels.The proposed method achieves satisfactorily small relative errors and high correlation coefficients in identifying the mechanical response of local interconnections in board-level packaging structures,while significantly balancing the smoothness of response curves with the accuracy of peak identification.At medium and low noise levels,the relative error is less than 6%,while it is less than 10%at high noise levels.The proposed method provides an effective indirect approach for the boundary conditions of localized solder joints during the projectile penetration process,and its philosophy can be readily extended to other scenarios of multiscale analysis for highly nonlinear materials and structures under extreme loading conditions.
基金Supported by the Project of the National "948" (2006-Z12)
文摘As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem suggestions for solution according to the practical situation. （RFID） plays an important role in dairy information tracing and culture function extension of managing breeding technology, and finally put forward some
基金Supported by the Earmarked Fund for Modern Agro-industry Technology Research System(CARS-26-02)the National Natural Science Foundation(31000917)Heilongjiang Excellent Young Funding(JC200712)
文摘Identification of powdery mildew pathogens on melon（Cucumis melo） is important for melon breeding and diseaseresistant germplasm selection. In this study, a powdery mildew pathogen that infected melon plants in Heilongjiang Province, China, was investigated in terms of host identification, morphological characteristics and phylogenetic relationships. The morphological characteristics of the pathogen were observed at five phases in the life cycle： germinating conidia, primary germ tube, hyphae, conidiophores, and colonization. The conidia were elliptical, colorless, catenulate, and the average length was 29.07 μm and average width was 17.82 μm. One ascus and eight ascospores were produced. DNA was extracted from 0.01 g conidiophores from a strain of powdery mildew pathogen that infected melon. ITS ribosomal DNA region（524 bp） was amplified with the universal ITS1 and ITS4 primers. The nucleotide sequence showed 100% similarity with ITS sequences for three Podosphaera fusca strains obtained from the GenBank database. The identity of the pathogen was confirmed as Sphaerotheca fuliginea. International standard differential hosts were used to identify S. fuliginea strain as 2F race. These results supported the notion that Podosphaera fusca was a synonym of S. fuliginea.
文摘Based on the specialty of major rock-forning minerals and elementary composition of metamorphite,the detailed and systematical review,analysis and summary are completed for a series of lithology and reservoir fracture identification teehnologies with logging that are recent years.Research shows that nuclear logging series in conventional logging are more favorable to identify the metanorphie lithology.ECS(elemental capturespectrosoopy)and other new logging lechnologies can be applied to identify metamorphic lithology.Due to theolex and di-verse metamorphic lithologies,the correspending reservoir identification standard should be established for metamorphic reservoir identificat lithology identification,The applicable conventional logging methods for metamorphic reservoir fracture identification mainly incldle dual lat ging,scoustic logging,dual lateral logging-microspherical focus,borehole diameter logging,natural gamma ray spectrology baging,etc.In additie acoustic-resistivity imaging logging,multipolar array acoustic logging,cross dipole acoustic logging and other new logging tec nologies with unique ad-vantages are increasingly applied for metamorphic reservoir fractureidentification.Currently,there are no gener appli sandards for logging i-dentification of metamorphic lithology and reservoir fracture.The specific metamorphic reservoir development a field actual data in specific ar-eas should be considered to study the logging identification and evaluation.
文摘Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass Spectral Deconvolution and Identification System)program was used to identify parts per million(ppm)HACC concentrations in petroleum fractions in place of traditional techniques(extraction and standard injection).Polycyclic aromatic sulfur heterocycles(S-PAHs)were used as model compounds to confirm the validity of the AMDIS identifiers,which were compared with extracted results using the off-line X-calibur software.AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate.There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate.AMDIS was also used to detect nitrogen-containing compounds(NCCs)and alkylphenols in oil condensate.Our results confirmed the presence of 2-methylbenzothiazole,carbazole,and 2,4-ditertbutyl phenol.In a crude oil sample,AMDIS identification of m/z=191 biomarkers wa s consistent with empirical results.Therefore,AMDIS can help to reduce the number of experimental steps in identification protocols.
文摘A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus and a potential target for SARS-specific cell-mediated immune responses. A pa nel of S protein-derived peptides was tested for their binding affinity to HLA -A *0201 molecules. Peptides with high affinity for HLA-A *0201 were then as se ssed for their capacity to elicit specific immune responses mediated by cytotoxi c T lymphocytes (CTLs) both in vivo, in HLA-A2.1/K b transgenic mice, a nd in vitro, from peripheral blood lymphocytes (PBLs) harvested from healthy HLA-A 2.1 + donors. SARS-CoV protein-derived peptide-1 (SSp-1 RLNEVAKNL), induced pepti de-specific CTLs both in vivo (transgenic mice) and in vitro (human PBL s), which specifically released interferon-gamma (IFN-gamma) upon stimulation with SSp-1-pulsed autologous dendritic cells (DCs) or T2 cells. SSp-1-specif ic CTLs also lysed major histocompatibility complex (MHC)-matched tumor cell lines engineered to express S proteins. HLA-A *0201-SSp-1 tetramer staining re vealed the presence of significant populations of SSp-1-specific CTLs in SSp- 1-induced CD8 + T cells. We propose that the newly identified epitope SSp-1 w ill help in the characterization of virus control mechanisms and immunopathology in SARS-CoV infection, and may be relevant to the development of immunotherape utic approaches for SARS.
基金Project(2012BAK09B02-05) supported by the National Key Technology R&D Program of China during the Twelfth Five-year PeriodProject(51274250) supported by the National Natural Science Foundation of China
文摘A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.
基金supported by National Natural Science Foundation of China(11472137)the Natural Science Foundation of Jiangsu Province,China(BK20140773)。
文摘In this study,a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory.The ADAMS software was used to build a parameterized dynamic model of the saddle ring.A parameter identification method for the ring was proposed based on the particle swarm optimization algorithm.A loading test was designed and performed several times at different elevation angles.The response histories of the saddle ring with different loads were then obtained.The parameters of the saddle ring dynamic model were identified from statistics generated at a 500 elevation angle to verify the feasibility and accuracy of the proposed method.The actual loading history of the ring at a 70°elevation angle was taken as the model input.The response histories of the ring under these working conditions were obtained through a simulation.The simulation results agreed with the actual response.Thus,the effectiveness and applicability of the proposed dynamic model were verified,and it provides an effective method for modeling saddle rings.
基金Project(61273158)supported by the National Natural Science Foundation of China
文摘An adaptive stable observer with output current online identification strategy for the auxiliary inverters applied in advanced electric trains, such as high speed railway, urban rail, subway and maglev trains, is proposed. The designed observer is used to estimate the state variables, i.e. controllable duty ratio and current components in d-q-o rotary reference frame. The convergence of the observer estimation error is analyzed with consideration of uncertain level variation of input voltage at direct current(DC) side and sufficient conditions are given to prove its practical stability. Experimental results are shown to confirm the effectiveness of the proposed observer.
基金supported by the National Natural Science Foundation of China(616732546157310061573101)
文摘A robust fault diagnosis approach is developed by incorporating a set-membership identification (SMI) method. A class of systems with linear models in the form of fault related parameters is investigated, with model uncertainties and parameter variations taken into account explicitly and treated as bounded errors. An ellipsoid bounding set-membership identification algorithm is proposed to propagate bounded uncertainties rigorously and the guaranteed feasible set of faults parameters enveloping true parameter values is given. Faults arised from abrupt parameter variations can be detected and isolated on-line by consistency check between predicted and observed parameter sets obtained in the identification procedure. The proposed approach provides the improved robustness with its ability to distinguish real faults from model uncertainties, which comes with the inherent guaranteed robustness of the set-membership framework. Efforts are also made in this work to balance between conservativeness and computation complexity of the overall algorithm. Simulation results for the mobile robot with several slipping faults scenarios demonstrate the correctness of the proposed approach for faults detection and isolation (FDI).
文摘Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS system in two-line breeding is laborsaving,timesaving,simple,inexpensive,efficient,and eliminating the limitations of the cytoplasmic male sterility(CMS)system.'AnnongS'is the first discovered and deeply studied TGMS rice lines in China.'AnnongS-1'and'Y58S',two derivatives of TGMS line AnnongS,were both controlled by a single recessive gene named tms5,which was genetically mapped on chromosome 2.In this study,three populations('AnnongS-1'×'Nanjing11','Y58S'×'Q611',and'Y58S'×'Guanghui122')were developed and used for the molecular fine mapping of the tms5 gene.By analyzing recombination events in the sterile individuals using a total of 125 probes covering the tms5 region,the tms5 gene was physically mapped to a 19-kb DNA fragment between two markers 4039-1 and 4039-2,which were located on the BAC clone AP004039.After the construction of the physical map between two markers 4039-1 and 4039-2,a member(ONAC023)of the NAC(NAM-ATAF-CUC-related)gene family was identified as the candidate gene of the tms5 gene.
基金Project(2007CB311106) supported by National Key Basic Research Program of ChinaProject(NEUL20090101) supported by the Foundation of National Information Control Laboratory of China
文摘Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network applications by optimized back-propagation (BP) neural network. Particle swarm optimization (PSO) algorithm was used to optimize the BP neural network. And in order to increase the identification performance, wavelet packet decomposition (WPD) was used to extract several hidden features from the time-frequency information of network traffic. The experimental results show that the average classification accuracy of various network applications can reach 97%. Moreover, this approach optimized by BP neural network takes 50% of the training time compared with the traditional neural network.
基金Project(2015BAG06B00)supported by the National Key Technology Research from Development Program of the Ministry of Science and Technology of China
文摘A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.
基金supported by the National Security Major Basic Research Project of China (973-61334).
文摘Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.
基金Project(61533021)supported by the National Natural Science Foundation of ChinaProject(R201706)supported by Hunan Food Pharmaceutical,China
文摘A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng were identified by the method.The NCFs of the three samples of Panax ginsengs were determined through two nonlinear chemical systems,namely system 1 consisting of sample components,H2SO4,MnSO4,NaBrO3,acetone and the new system,system 2 consisting of sample components,H2SO4,(NH4)4Ce(SO4)2,NaBrO3 and citric acid.The comparison between the results determined through systems 1 and 2 shows that the speed to determine NCF through system 2 is much faster than that through system 1;for systems 1 and 2,the system similarities of the same kind of samples are≥98.09%and 99.78%,respectively,while those of different kinds of samples are≤63.04%and 86.34%,respectively.The results to identify the kinds of some samples by system similarity pattern show that both the accuracies of identification methods based on single system 1 and 2 are≥95.6%,and the average values are 97.1%and 96.3%,respectively;the accuracy of the method based on double system is≥97.8%,and the average accuracy is 99.3%.The accuracy of the method based on double system is higher than that based on any single system.
文摘Total 75 rice varieties （lines） in Heilongjiang Province （or cold region） as germplasm resources were identified for cold tolerance at germinating stage by controlling temperature in artificial incubator. The results showed that the shooting seed rate at the germinating stage could be used as the evaluation index of cold tolerance. The cold tolerance was recorded on 1-9 scale and could be identified by the criteria of five indexes such as highly tolerant （HT）, tolerant （T）, moderately tolerant （MT）, susceptible （S）, highly susceptible （HS）.
