A Bayes discriminant analysis method to identify the risky of complicated goaf in mines was presented. Nine factors influencing the stability of goaf risky, including uniaxial compressive strength of rock, elastic mod...A Bayes discriminant analysis method to identify the risky of complicated goaf in mines was presented. Nine factors influencing the stability of goaf risky, including uniaxial compressive strength of rock, elastic modulus of rock, rock quality designation （RQD）, area ratio of pillar, ratio of width to height of pillar, depth of ore body, volume of goaf, dip of ore body and area of goal, were selected as discriminant indexes in the stability analysis of goal. The actual data of 40 goals were used as training samples to establish a discriminant analysis model to identify the stability of goaf. The results show that this discriminant analysis model has high precision and misdiscriminant ratio is 0.025 in re-substitution process. The instability identification of a metal mine was distinguished by using this model and the identification result is identical with that of practical situation.展开更多
As a result of the recently increasing demands on high-performance aero-engine,the machining accuracy of blade profile is becoming more stringent. However,in the current profile,precision milling,grinding or near-nets...As a result of the recently increasing demands on high-performance aero-engine,the machining accuracy of blade profile is becoming more stringent. However,in the current profile,precision milling,grinding or near-netshape technology has to undergo a tedious iterative error compensation. Thus,if the profile error area and boundary can be determined automatically and quickly,it will help to improve the efficiency of subsequent re-machining correction process. To this end,an error boundary intersection approach is presented aiming at the error area determination of complex profile,including the phaseⅠof cross sectional non-rigid registration based on the minimum error area and the phaseⅡof boundary identification based on triangular meshes intersection. Some practical cases are given to demonstrate the effectiveness and superiority of the proposed approach.展开更多
Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-...Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-made objects. Knowing where these avian migration ＂hot-spots＂ occur in time and space is vital to improve flight safety and inform the spatial planning process （e.g. environmental assessments for offshore windfarms）. We developed a simple spatial model to identify avian migration hot- spots in coastal areas based on prevailing migration orientation and coastline features known, from visual and radar observations, to concentrate migrating landbirds around land masses. Regional scale model validation was achieved by combining nocturnal passerine movement data gathered from two tier radar coverage （long-range dual-polarization Doppler weather radar and short- range marine surveillance radar） and standardised bird ringing. Applied on a national scale, the model correctly identified the ten most important Danish coastal hot-spots for spring migrants and predicted the relative numbers of birds that concentrated at each site. These bird numbers corresponded well with historical observational data. Here, we provide a potential framework for the es- tablishment of the first three-dimensional avian airspace sanctuaries, which could contribute to more effective conservation of long-distance migratory birds [Current Zoology 60 （5）： 680-691, 2014].展开更多
基金Project (2010CB732004) supported by the National Basic Research Program of China
文摘A Bayes discriminant analysis method to identify the risky of complicated goaf in mines was presented. Nine factors influencing the stability of goaf risky, including uniaxial compressive strength of rock, elastic modulus of rock, rock quality designation （RQD）, area ratio of pillar, ratio of width to height of pillar, depth of ore body, volume of goaf, dip of ore body and area of goal, were selected as discriminant indexes in the stability analysis of goal. The actual data of 40 goals were used as training samples to establish a discriminant analysis model to identify the stability of goaf. The results show that this discriminant analysis model has high precision and misdiscriminant ratio is 0.025 in re-substitution process. The instability identification of a metal mine was distinguished by using this model and the identification result is identical with that of practical situation.
基金supported by the Aeronautical Science Foundation of China (No.20200016112001)。
文摘As a result of the recently increasing demands on high-performance aero-engine,the machining accuracy of blade profile is becoming more stringent. However,in the current profile,precision milling,grinding or near-netshape technology has to undergo a tedious iterative error compensation. Thus,if the profile error area and boundary can be determined automatically and quickly,it will help to improve the efficiency of subsequent re-machining correction process. To this end,an error boundary intersection approach is presented aiming at the error area determination of complex profile,including the phaseⅠof cross sectional non-rigid registration based on the minimum error area and the phaseⅡof boundary identification based on triangular meshes intersection. Some practical cases are given to demonstrate the effectiveness and superiority of the proposed approach.
文摘Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-made objects. Knowing where these avian migration ＂hot-spots＂ occur in time and space is vital to improve flight safety and inform the spatial planning process （e.g. environmental assessments for offshore windfarms）. We developed a simple spatial model to identify avian migration hot- spots in coastal areas based on prevailing migration orientation and coastline features known, from visual and radar observations, to concentrate migrating landbirds around land masses. Regional scale model validation was achieved by combining nocturnal passerine movement data gathered from two tier radar coverage （long-range dual-polarization Doppler weather radar and short- range marine surveillance radar） and standardised bird ringing. Applied on a national scale, the model correctly identified the ten most important Danish coastal hot-spots for spring migrants and predicted the relative numbers of birds that concentrated at each site. These bird numbers corresponded well with historical observational data. Here, we provide a potential framework for the es- tablishment of the first three-dimensional avian airspace sanctuaries, which could contribute to more effective conservation of long-distance migratory birds [Current Zoology 60 （5）： 680-691, 2014].
