Terrestrial laser scanning(TLS) is a useful technology for rock mass characterization. A laser scanner produces a massive point cloud of a scanned area, such as an exposed rock surface in an underground tunnel,with mi...Terrestrial laser scanning(TLS) is a useful technology for rock mass characterization. A laser scanner produces a massive point cloud of a scanned area, such as an exposed rock surface in an underground tunnel,with millimeter precision. The density of the point cloud depends on several parameters from both the TLS operational conditions and the specifications of the project, such as the resolution and the quality of the laser scan, the section of the tunnel, the distance between scanning stations, and the purpose of the scans. One purpose of the scan can be to characterize the rock mass and statistically analyze the discontinuities that compose it for further discontinuous modeling. In these instances, additional data processing and a detailed analysis should be performed on the point cloud to extract the parameters to define a discrete fracture network(DFN) for each discontinuity set. I-site studio is a point cloud processing software that allows users to edit and process laser scans. This software contains a set of geotechnical analysis tools that assist engineers during the structural mapping process, allowing for greater and more representative data regarding the structural information of the rock mass, which may be used for generating DFNs. This paper presents the procedures used during a laser scan for characterizing discontinuities in an underground limestone mine and the results of the scan as applied to the generation of DFNs for further discontinuous modeling.展开更多
The detection range of underwater laser imaging technology achieves 4—6 times of detection range of conventional camera in intervening water medium, which makes it very promising in oceanic research, deep sea explora...The detection range of underwater laser imaging technology achieves 4—6 times of detection range of conventional camera in intervening water medium, which makes it very promising in oceanic research, deep sea exploration and robotic works. However, the special features in underwater laser images, such as speckle noise and non-uniform illumination, bring great difficulty for image segmentation. In this paper, a novel saliency motivated pulse coupled neural network(SM-PCNN) is proposed for underwater laser image segmentation. The pixel saliency is used as external stimulus of neurons. For improvement of convergence speed to optimal segmentation, a gradient descent method based on maximum two-dimensional Renyi entropy criterion is utilized to determine the dynamic threshold. On the basis of region contrast in each iteration step, the real object regions are effectively distinguished,and the robustness against speckle noise and non-uniform illumination is improved by region selection. The proposed method is compared with four other state-of-the-art methods which are watershed, fuzzy C-means, meanshift and normalized cut methods. Experimental results demonstrate the superiority of our proposed method to allow more accurate segmentation and higher robustness.展开更多
Laser blank welding is becoming more and more important in the automotive industry and the quality of the weld is critical for a successful application. A fully automated solution is required to inspect the quality of...Laser blank welding is becoming more and more important in the automotive industry and the quality of the weld is critical for a successful application. A fully automated solution is required to inspect the quality of the blanks. This paper presents a vision inspection system with a CMOS camera which uses ART2 network to inspect the defects on-line to obtain the geometry and the quality of the weld seam. The neural network ART2 has the capability of self-learning fiom the environment. It can distinguish the defects that have been learned before and give new outputs for new defects. So ART2 network is suitable for weld quality inspection in laser blank welding. Additionally, a CO2 laser is used for the blank butt-welding.展开更多
In the present work,a study is made to investigate the effects of process parameters,namely,laser power,scanning speed,hatch spacing, layer thickness and powder temperature, on the tensile strength for selective laser...In the present work,a study is made to investigate the effects of process parameters,namely,laser power,scanning speed,hatch spacing, layer thickness and powder temperature, on the tensile strength for selective laser sintering( SLS) of polystyrene( PS). Artificial neural network( ANN) methodology is employed to develop mathematical relationships between the process parameters and the output variable of the sintering strength. Experimental data are used to train and test the network. The present neural network model is applied to predicting the experimental outcome as a function of input parameters within a specified range. Predicted sintering strength using the trained back propagation( BP) network model showed quite a good agreement with measured ones. The results showed that the networks had high processing speed,the abilities of error-correcting and self-organizing. ANN models had favorable performance and proved to be an applicable tool for predicting sintering strength SLS of PS.展开更多
One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated ...One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated a combination of time-resolved LIBS and convolutional neural networks(CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R_c^2?=?0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network(ANN), showing R_v^2?=?0.6318 and the root mean square error of validation(RMSEV)?=?0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R_v^2?=?0.7366 and RMSEV?=?0.7855.These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K.However, due to limited calibration samples, the two-dimensional models presented over-fitting.The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.展开更多
Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on...Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To exploit the benefits presented by the laser hardening process, it is necessary to develop an integrated strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive modelling approach for predicting the hardened surface physical and geometrical attributes. The laser surface transformation hardening of cylindrical AISI 4340 steel workpieces is modeled using the conventional regression equation method as well as artificial neural network method. The process parameters included in the study are laser power, beam scanning speed, and the workpiece rotational speed. The upper and the lower limits for each parameter are chosen considering the start of the transformation hardening and the maximum hardened zone without surface melting. The resulting models are able to predict the depths representing the maximum hardness zone, the hardness drop zone, and the overheated zone without martensite transformation. Because of its ability to model highly nonlinear problems, the ANN based model presents the best modelling results and can predict the hardness profile with good accuracy.展开更多
Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consiste...Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consistent biomarkers for NPC, particularly for early detection of NPC. Methods: A proteomic pattern was identified in a training set (134 NPC patients and 73 control individuals) using the surface-enhanced laser desorption and ionization-mass spectrometry (SELDI-MS), and used to screen the test set (44 NPC patients and 25 control individuals) to determine the screening accuracy. To confirm the accuracy, it was used to test another group of 52 NPC patients and 32 healthy individuals at 6 months later. Results: Eight proteomic biomarkers with top-scored peak mass/charge ratios (m/z) of 8605 Da, 5320 Da, 5355 Da, 5380 Da, 5336 Da, 2791 Da, 7154 Da, and 9366 Da were selected as the potential biomarkers of NPC with a sensitivity of 90.9% (40/44) and a specificity of 92.0% (23/25). The performance was better than the current diagnostic method by using the Epstein-Barr virus (EBV) capsid antigen IgA antibodies (VCA/IgA). Similar sensitivity (88.5%) and specificity (90.6%) were achieved in another group of 84 samples. Conclusion: SELDI-MS profiling might be a potential tool to identify patients with NPC, particularly at early clinical stages.展开更多
Rotationally symmetric triangulation(RST)sensor has more flexibility and less uncertainty limits because of the abaxial rotationally symmetric optical system.But if the incident laser is eccentric,the symmetry of the ...Rotationally symmetric triangulation(RST)sensor has more flexibility and less uncertainty limits because of the abaxial rotationally symmetric optical system.But if the incident laser is eccentric,the symmetry of the image will descend,and it will result in the eccentric error especially when some part of the imaged ring is blocked.The model of rotationally symmetric triangulation that meets the Schimpflug condition is presented in this paper.The error from eccentric incident laser is analysed.It is pointed out that the eccentric error is composed of two parts,one is a cosine in circumference and proportional to the eccentric departure factor,and the other is a much smaller quadric factor of the departure.When the ring is complete,the first error factor is zero because it is integrated in whole ring, but if some part of the ring is blocked,the first factor will be the main error.Simulation verifies the result of the a- nalysis.At last,a compensation method to the error when some part of the ring is lost is presented based on neural network.The results of experiment show that the compensation will make the absolute maximum error descend to half,and the standard deviation of error descends to 1/3.展开更多
Accuracy is one of the most important key indices to evaluate multi-axis systems’ (MAS’s) characteristics and performances. The accuracy of MAS’s such as machine tools, measuring machines and robots is adversely af...Accuracy is one of the most important key indices to evaluate multi-axis systems’ (MAS’s) characteristics and performances. The accuracy of MAS’s such as machine tools, measuring machines and robots is adversely affected by various error sources, including geometric imperfections, thermal deformations, load effects, and dynamic disturbances. The increasing demand for higher dimensional accuracy in various industrial applications has created the need to develop cost-effective methods for enhancing the overall performance of these mechanisms. Improving the accuracy of a MAS by upgrading the physical structure would lead to an exponential increase in manufacturing costs without totally eliminating geometrical deviations and thermal deformations of MAS components. Hence, the idea of reducing MAS’s error by a software-based alternative approach to provide real-time prediction and correction of geometric and thermally induced errors is considered a strategic step toward achieving the full potential of the MAS. This paper presents a structured approach designed to improve the accuracy of Cartesian MAS’s through software error compensation. Four steps are required to develop and implement this approach: (i) measurement of error components using a multidimensional laser interferometer system, (ii) tridimensional volumetric error mapping using rigid body kinematics, (iii) volumetric error prediction via an artificial neural network model, and finally (iv) implementation of the on-line error compensation. An illustrative example using a bridge type coordinate measuring machine is presented.展开更多
A new synchronization technique of inner and outer couplings is proposed in this work to investigate the synchro- nization of network group. Some Haken-Lorenz lasers with chaos behaviors are taken as the nodes to cons...A new synchronization technique of inner and outer couplings is proposed in this work to investigate the synchro- nization of network group. Some Haken-Lorenz lasers with chaos behaviors are taken as the nodes to construct a few nearest neighbor complex networks and those sub-networks are also connected to form a network group. The effective node controllers are designed based on Lyapunov function and the complete synchronization among the sub-networks is realized perfectly under inner and outer couplings. The work is of potential applications in the cooperation output of lasers and the communication network.展开更多
In this paper, we put emphasis on the analysis the mechanism of the photon induced frequency conversion β BaB 2O 4 crystal inside a borate glass using femtosecond laser. Because of the nature of femtosecond laser...In this paper, we put emphasis on the analysis the mechanism of the photon induced frequency conversion β BaB 2O 4 crystal inside a borate glass using femtosecond laser. Because of the nature of femtosecond laser's ultra short pulse duration and high energy density, in essence the laser glass interaction mechanism is changed. Based on multiphoton ionization, collisional ionization and the network depolymerization in the borate glass, production of the plasma drives the microstructure rearrangement near the laser beam focusing area. From the structure of glass and crystal analysis, we conclude that the complicated borate groups containing BO 3 and BO 4 units inside the glass are converted into(B 3O 6) -3 anion rings.展开更多
The integrated absorption cross section Σ abs, peak emis sion cross section σ emi, Judd-Ofeld intensity parameters Ω t(t=2,4,6), and spontaneous emission probability A R of Er 3+ ions were determined fo r...The integrated absorption cross section Σ abs, peak emis sion cross section σ emi, Judd-Ofeld intensity parameters Ω t(t=2,4,6), and spontaneous emission probability A R of Er 3+ ions were determined fo r Erbium doped alkali and alkaline earth phosphate glasses. It is found the comp ositional dependence of σ emi is almost similar to that of Σ abs, wh ich is determined by the sum of Ω t (3Ω 2+10Ω 4+21Ω 6). In addition, the compositional dependence of Ω t was studied in these glass systems. As a resu lt, compared with Ω 4 and Ω 6, the Ω 2 has a stronger compositional depend ence on the ionic radius and content of modifiers. The covalency of Er-O bonds in phosphate glass is weaker than that in silicate glass, germanate glass, alumi nate glass, and tellurate glass, since Ω 6 of phosphate glass is relatively la rge. A R is affected by the covalency of the Er 3+ ion sites and correspon ds to the Ω 6 value.展开更多
The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteri...The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteria cultured at different time was discussed and the effect of the network parameters on the classification was investigated. The cross-validation method was used to test the trained networks. The correctness of the classification of different bacteria investigated changes in a wide range from 61.5% to 92.8%. Owing to the complexity of biological effects in bacterial growth, the more rigid control of bacterial culture conditions seems to be a critical factor for improving the rate of correctness for bacterial classification.展开更多
基金funded by the NIOSH Mining Program under Contract No. 200-2016-91300
文摘Terrestrial laser scanning(TLS) is a useful technology for rock mass characterization. A laser scanner produces a massive point cloud of a scanned area, such as an exposed rock surface in an underground tunnel,with millimeter precision. The density of the point cloud depends on several parameters from both the TLS operational conditions and the specifications of the project, such as the resolution and the quality of the laser scan, the section of the tunnel, the distance between scanning stations, and the purpose of the scans. One purpose of the scan can be to characterize the rock mass and statistically analyze the discontinuities that compose it for further discontinuous modeling. In these instances, additional data processing and a detailed analysis should be performed on the point cloud to extract the parameters to define a discrete fracture network(DFN) for each discontinuity set. I-site studio is a point cloud processing software that allows users to edit and process laser scans. This software contains a set of geotechnical analysis tools that assist engineers during the structural mapping process, allowing for greater and more representative data regarding the structural information of the rock mass, which may be used for generating DFNs. This paper presents the procedures used during a laser scan for characterizing discontinuities in an underground limestone mine and the results of the scan as applied to the generation of DFNs for further discontinuous modeling.
基金the National High Technology Research and Development Program(863)of China(No.2011AA09A106)the National Natural Science Foundation of China(No.51009040)and the Fundamental Research Funds for Central Universities of China(No.HEUCF140113)
文摘The detection range of underwater laser imaging technology achieves 4—6 times of detection range of conventional camera in intervening water medium, which makes it very promising in oceanic research, deep sea exploration and robotic works. However, the special features in underwater laser images, such as speckle noise and non-uniform illumination, bring great difficulty for image segmentation. In this paper, a novel saliency motivated pulse coupled neural network(SM-PCNN) is proposed for underwater laser image segmentation. The pixel saliency is used as external stimulus of neurons. For improvement of convergence speed to optimal segmentation, a gradient descent method based on maximum two-dimensional Renyi entropy criterion is utilized to determine the dynamic threshold. On the basis of region contrast in each iteration step, the real object regions are effectively distinguished,and the robustness against speckle noise and non-uniform illumination is improved by region selection. The proposed method is compared with four other state-of-the-art methods which are watershed, fuzzy C-means, meanshift and normalized cut methods. Experimental results demonstrate the superiority of our proposed method to allow more accurate segmentation and higher robustness.
文摘Laser blank welding is becoming more and more important in the automotive industry and the quality of the weld is critical for a successful application. A fully automated solution is required to inspect the quality of the blanks. This paper presents a vision inspection system with a CMOS camera which uses ART2 network to inspect the defects on-line to obtain the geometry and the quality of the weld seam. The neural network ART2 has the capability of self-learning fiom the environment. It can distinguish the defects that have been learned before and give new outputs for new defects. So ART2 network is suitable for weld quality inspection in laser blank welding. Additionally, a CO2 laser is used for the blank butt-welding.
基金National Natural Science Foundation of China(No.51475315)Innovative Project on the Integration of Industry,Education and Research of Jiangsu Province,China(No.BY2014059-10)
文摘In the present work,a study is made to investigate the effects of process parameters,namely,laser power,scanning speed,hatch spacing, layer thickness and powder temperature, on the tensile strength for selective laser sintering( SLS) of polystyrene( PS). Artificial neural network( ANN) methodology is employed to develop mathematical relationships between the process parameters and the output variable of the sintering strength. Experimental data are used to train and test the network. The present neural network model is applied to predicting the experimental outcome as a function of input parameters within a specified range. Predicted sintering strength using the trained back propagation( BP) network model showed quite a good agreement with measured ones. The results showed that the networks had high processing speed,the abilities of error-correcting and self-organizing. ANN models had favorable performance and proved to be an applicable tool for predicting sintering strength SLS of PS.
基金supported by National Natural Science Foundation of China (Grant No. 61505253)National Key Research and Development Plan of China (Project No. 2016YFD0200601)
文摘One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated a combination of time-resolved LIBS and convolutional neural networks(CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R_c^2?=?0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network(ANN), showing R_v^2?=?0.6318 and the root mean square error of validation(RMSEV)?=?0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R_v^2?=?0.7366 and RMSEV?=?0.7855.These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K.However, due to limited calibration samples, the two-dimensional models presented over-fitting.The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.
文摘Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To exploit the benefits presented by the laser hardening process, it is necessary to develop an integrated strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive modelling approach for predicting the hardened surface physical and geometrical attributes. The laser surface transformation hardening of cylindrical AISI 4340 steel workpieces is modeled using the conventional regression equation method as well as artificial neural network method. The process parameters included in the study are laser power, beam scanning speed, and the workpiece rotational speed. The upper and the lower limits for each parameter are chosen considering the start of the transformation hardening and the maximum hardened zone without surface melting. The resulting models are able to predict the depths representing the maximum hardness zone, the hardness drop zone, and the overheated zone without martensite transformation. Because of its ability to model highly nonlinear problems, the ANN based model presents the best modelling results and can predict the hardness profile with good accuracy.
基金National Science & Technology Pillar Program in the Eleventh Five-year Plan of China (No. 2006BAI02A11)Planned Sci-Tech Project of Guangdong Province (No. 2005B50301006)
文摘Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consistent biomarkers for NPC, particularly for early detection of NPC. Methods: A proteomic pattern was identified in a training set (134 NPC patients and 73 control individuals) using the surface-enhanced laser desorption and ionization-mass spectrometry (SELDI-MS), and used to screen the test set (44 NPC patients and 25 control individuals) to determine the screening accuracy. To confirm the accuracy, it was used to test another group of 52 NPC patients and 32 healthy individuals at 6 months later. Results: Eight proteomic biomarkers with top-scored peak mass/charge ratios (m/z) of 8605 Da, 5320 Da, 5355 Da, 5380 Da, 5336 Da, 2791 Da, 7154 Da, and 9366 Da were selected as the potential biomarkers of NPC with a sensitivity of 90.9% (40/44) and a specificity of 92.0% (23/25). The performance was better than the current diagnostic method by using the Epstein-Barr virus (EBV) capsid antigen IgA antibodies (VCA/IgA). Similar sensitivity (88.5%) and specificity (90.6%) were achieved in another group of 84 samples. Conclusion: SELDI-MS profiling might be a potential tool to identify patients with NPC, particularly at early clinical stages.
基金Supported by China Scholarship Council(CSC),Deutscher Akademischer Austausch Dienst(DAAD),National Natural Science Foundation of China(60375011,60575028)Natural Science Foundation of Anhui Province(04042044)Supported by Program for New Century Excellent Talents in University(NCET-04-0560)
文摘Rotationally symmetric triangulation(RST)sensor has more flexibility and less uncertainty limits because of the abaxial rotationally symmetric optical system.But if the incident laser is eccentric,the symmetry of the image will descend,and it will result in the eccentric error especially when some part of the imaged ring is blocked.The model of rotationally symmetric triangulation that meets the Schimpflug condition is presented in this paper.The error from eccentric incident laser is analysed.It is pointed out that the eccentric error is composed of two parts,one is a cosine in circumference and proportional to the eccentric departure factor,and the other is a much smaller quadric factor of the departure.When the ring is complete,the first error factor is zero because it is integrated in whole ring, but if some part of the ring is blocked,the first factor will be the main error.Simulation verifies the result of the a- nalysis.At last,a compensation method to the error when some part of the ring is lost is presented based on neural network.The results of experiment show that the compensation will make the absolute maximum error descend to half,and the standard deviation of error descends to 1/3.
文摘Accuracy is one of the most important key indices to evaluate multi-axis systems’ (MAS’s) characteristics and performances. The accuracy of MAS’s such as machine tools, measuring machines and robots is adversely affected by various error sources, including geometric imperfections, thermal deformations, load effects, and dynamic disturbances. The increasing demand for higher dimensional accuracy in various industrial applications has created the need to develop cost-effective methods for enhancing the overall performance of these mechanisms. Improving the accuracy of a MAS by upgrading the physical structure would lead to an exponential increase in manufacturing costs without totally eliminating geometrical deviations and thermal deformations of MAS components. Hence, the idea of reducing MAS’s error by a software-based alternative approach to provide real-time prediction and correction of geometric and thermally induced errors is considered a strategic step toward achieving the full potential of the MAS. This paper presents a structured approach designed to improve the accuracy of Cartesian MAS’s through software error compensation. Four steps are required to develop and implement this approach: (i) measurement of error components using a multidimensional laser interferometer system, (ii) tridimensional volumetric error mapping using rigid body kinematics, (iii) volumetric error prediction via an artificial neural network model, and finally (iv) implementation of the on-line error compensation. An illustrative example using a bridge type coordinate measuring machine is presented.
基金Project supported by the National Natural Science Foundation of China(Grant No.11004092)the Natural Science Foundation of Liaoning Province,China(Grant Nos.2015020079 and 201602455)the Foundation of Education Department of Liaoning Province,China(Grant No.L201683665)
文摘A new synchronization technique of inner and outer couplings is proposed in this work to investigate the synchro- nization of network group. Some Haken-Lorenz lasers with chaos behaviors are taken as the nodes to construct a few nearest neighbor complex networks and those sub-networks are also connected to form a network group. The effective node controllers are designed based on Lyapunov function and the complete synchronization among the sub-networks is realized perfectly under inner and outer couplings. The work is of potential applications in the cooperation output of lasers and the communication network.
文摘In this paper, we put emphasis on the analysis the mechanism of the photon induced frequency conversion β BaB 2O 4 crystal inside a borate glass using femtosecond laser. Because of the nature of femtosecond laser's ultra short pulse duration and high energy density, in essence the laser glass interaction mechanism is changed. Based on multiphoton ionization, collisional ionization and the network depolymerization in the borate glass, production of the plasma drives the microstructure rearrangement near the laser beam focusing area. From the structure of glass and crystal analysis, we conclude that the complicated borate groups containing BO 3 and BO 4 units inside the glass are converted into(B 3O 6) -3 anion rings.
基金Funded by the Natural Science Foundation of Guangdong Prov ince(013013) and the Science and Technology Plan of Guangdong Province(2002B11604)
文摘The integrated absorption cross section Σ abs, peak emis sion cross section σ emi, Judd-Ofeld intensity parameters Ω t(t=2,4,6), and spontaneous emission probability A R of Er 3+ ions were determined fo r Erbium doped alkali and alkaline earth phosphate glasses. It is found the comp ositional dependence of σ emi is almost similar to that of Σ abs, wh ich is determined by the sum of Ω t (3Ω 2+10Ω 4+21Ω 6). In addition, the compositional dependence of Ω t was studied in these glass systems. As a resu lt, compared with Ω 4 and Ω 6, the Ω 2 has a stronger compositional depend ence on the ionic radius and content of modifiers. The covalency of Er-O bonds in phosphate glass is weaker than that in silicate glass, germanate glass, alumi nate glass, and tellurate glass, since Ω 6 of phosphate glass is relatively la rge. A R is affected by the covalency of the Er 3+ ion sites and correspon ds to the Ω 6 value.
基金Supported by Foundation for Young Mainstay TeachersEducation Ministry of China.
文摘The radial basis function networks were applied to bacterial classification based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometric (MALDI-TOF-MS) data. The classification of bacteria cultured at different time was discussed and the effect of the network parameters on the classification was investigated. The cross-validation method was used to test the trained networks. The correctness of the classification of different bacteria investigated changes in a wide range from 61.5% to 92.8%. Owing to the complexity of biological effects in bacterial growth, the more rigid control of bacterial culture conditions seems to be a critical factor for improving the rate of correctness for bacterial classification.
