Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological b...Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.展开更多
A modeling method of extended knowledge hybrid Petri nets （EKHPNs）, incorporating object-oriented methods into hybrid Petri nets （HPNs）, was presented and used for the representation ~d modeling of semiconductor w...A modeling method of extended knowledge hybrid Petri nets （EKHPNs）, incorporating object-oriented methods into hybrid Petri nets （HPNs）, was presented and used for the representation ~d modeling of semiconductor wafer fabrication flows. To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs. Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow. Knowledge anno- tations were introduced to solve input and output conflicts of the EKHPNs. Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the model- ing procedure. The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently.展开更多
This paper aims to present and discuss the use of a power flow methodology based on Gauss elimination method to evaluate the performance of distribution network taking into account the neutral conductor absence at spe...This paper aims to present and discuss the use of a power flow methodology based on Gauss elimination method to evaluate the performance of distribution network taking into account the neutral conductor absence at specific sections, and a development of a methodology based on GA （genetic algorithm） capable of evaluating alternative solutions in different bars of the feeder, in order to propose appropriate solutions to improve the distribution network safety. Besides the technical aspects, the proposed GA methodology takes into account the economic feasibility analysis. The results of power flow simulations have shown that the presence of single-phase transformers along with the absence of the neutral conductor at specific sections of the MV （medium voltage） network may increase the Vng （neutral-to-ground voltage） levels of the feeders involved, jeopardizing the system＇s safety. On the other hand, the solutions proposed by the GA methodology may reduce the network Vng levels and improve the safety conditions, providing values close to the ones found before the neutral conductor theft.展开更多
This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacit...This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacitive current measured in the open-phase plus the currents in the two healthy phases in calculating the open-circuit fault distance. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open-conductor condition in HVTL （high voltage transmission line） but also to locate the place of this fault regardless the value of the pre-fault current loading. There is no need for especial communication schemes since the existing media could work properly for the needs of the proposed technique.展开更多
Complementary metal oxide semiconductor(CMOS) image sensors(CIS) are being widely used in digital video cameras, web cameras, digital single lens reflex camera(DSLR), smart phones and so on, owing to their high level ...Complementary metal oxide semiconductor(CMOS) image sensors(CIS) are being widely used in digital video cameras, web cameras, digital single lens reflex camera(DSLR), smart phones and so on, owing to their high level of integration, random accessibility, and low-power operation. It needs to be installed with the cover glass in practical applications to protect the sensor from damage, mechanical issues,and environmental conditions, which, however, limits the accuracy and usability of the sensor due to the reflection in the optical path from air-to-cover glass-to-air. In this work, the flexible 3D nanocone anti-reflection(AR) film with controlled aspect ratio was firstly employed to reduce the light reflection at air/cover glass/air interfaces by directly attaching onto the front and rear sides of the CIS cover glass.As both the front and rear sides of cover glass were coated by the AR film, the output image quality was found to be improved with external quantum efficiency increased by 7%, compared with that without AR film. The mean digital data value, root-mean-square contrast, and dynamic range are increased by45.14%, 38.61% and 57, respectively, for the output image with AR films. These results provide a novel and facile pathway to improve the CIS performance and also could be extended to rational design of other image sensors and optoelectronic devices.展开更多
基金The study was supported by Open Fund of State Key Laboratory of Coal Resources and Safe Mining(Grant No.SKLCRSM19ZZ02)the National Natural Science Foundation of China(No.41702173)。
文摘Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.
基金the National Natural Science Foundation of China(No.60574054)
文摘A modeling method of extended knowledge hybrid Petri nets （EKHPNs）, incorporating object-oriented methods into hybrid Petri nets （HPNs）, was presented and used for the representation ~d modeling of semiconductor wafer fabrication flows. To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs. Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow. Knowledge anno- tations were introduced to solve input and output conflicts of the EKHPNs. Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the model- ing procedure. The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently.
文摘This paper aims to present and discuss the use of a power flow methodology based on Gauss elimination method to evaluate the performance of distribution network taking into account the neutral conductor absence at specific sections, and a development of a methodology based on GA （genetic algorithm） capable of evaluating alternative solutions in different bars of the feeder, in order to propose appropriate solutions to improve the distribution network safety. Besides the technical aspects, the proposed GA methodology takes into account the economic feasibility analysis. The results of power flow simulations have shown that the presence of single-phase transformers along with the absence of the neutral conductor at specific sections of the MV （medium voltage） network may increase the Vng （neutral-to-ground voltage） levels of the feeders involved, jeopardizing the system＇s safety. On the other hand, the solutions proposed by the GA methodology may reduce the network Vng levels and improve the safety conditions, providing values close to the ones found before the neutral conductor theft.
文摘This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacitive current measured in the open-phase plus the currents in the two healthy phases in calculating the open-circuit fault distance. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open-conductor condition in HVTL （high voltage transmission line） but also to locate the place of this fault regardless the value of the pre-fault current loading. There is no need for especial communication schemes since the existing media could work properly for the needs of the proposed technique.
基金financially supported by the National Natural Science Foundation of China(61474128,21503261,61504155and 61404145)Youth Innovation Fund for Interdisciplinary Research of SARI(Y526453233,141004)+2 种基金Science & Technology Commission of Shanghai Municipality(14JC1492900,14511102302,15DZ1100502)Youth Innovation Promotion Association,CAS(2013302)Development Fund for Information communication and integrated circuit technology public service platform(No.2016-14)supported by Zhangjiang Adminstrative Committee
文摘Complementary metal oxide semiconductor(CMOS) image sensors(CIS) are being widely used in digital video cameras, web cameras, digital single lens reflex camera(DSLR), smart phones and so on, owing to their high level of integration, random accessibility, and low-power operation. It needs to be installed with the cover glass in practical applications to protect the sensor from damage, mechanical issues,and environmental conditions, which, however, limits the accuracy and usability of the sensor due to the reflection in the optical path from air-to-cover glass-to-air. In this work, the flexible 3D nanocone anti-reflection(AR) film with controlled aspect ratio was firstly employed to reduce the light reflection at air/cover glass/air interfaces by directly attaching onto the front and rear sides of the CIS cover glass.As both the front and rear sides of cover glass were coated by the AR film, the output image quality was found to be improved with external quantum efficiency increased by 7%, compared with that without AR film. The mean digital data value, root-mean-square contrast, and dynamic range are increased by45.14%, 38.61% and 57, respectively, for the output image with AR films. These results provide a novel and facile pathway to improve the CIS performance and also could be extended to rational design of other image sensors and optoelectronic devices.
