Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and di...Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and differences of various surface features.Currently,topographic maps are mainly stored in raster and vector formats.Extraction of the spatio-temporal knowledge in the maps—such as spatial distribution patterns,feature relationships,and dynamic evolution—still primarily relies on manual interpretation.However,manual interpretation is time-consuming and laborious,especially for large-scale,long-term map knowledge extraction and application.With the development of artificial intelligence technology,it is possible to improve the automation level of map knowledge interpretation.Therefore,the present study proposes an automatic interpretation method for raster topographic map knowledge based on deep learning.To address the limitations of current data-driven intelligent technology in learning map spatial relations and cognitive logic,we establish a formal description of map knowledge by mapping the relationship between map knowledge and features,thereby ensuring interpretation accuracy.Subsequently,deep learning techniques are employed to extract map features automatically,and the spatio-temporal knowledge is constructed by combining formal descriptions of geographic feature knowledge.Validation experiments demonstrate that the proposed method effectively achieves automatic interpretation of spatio-temporal knowledge of geographic features in maps,with an accuracy exceeding 80%.The findings of the present study contribute to machine understanding of spatio-temporal differences in map knowledge and advances the intelligent interpretation and utilization of cartographic information.展开更多
Vector-to-raster conversion is a process accompanied with errors.The errors are classified into predicted errors before rasterization and actual errors after that.Accurate prediction of the errors is beneficial to dev...Vector-to-raster conversion is a process accompanied with errors.The errors are classified into predicted errors before rasterization and actual errors after that.Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality.Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.In this study,land cover data of China at a scale of 1:250 000 were taken as an example for analyzing the relationship between rasterization errors and the density of arc length(DA),the density of polygon(DP) and the size of grid cells(SG).Significant correlations were found between the errors and DA,DP and SG.The correlation coefficient(R2) of a model established based on samples collected in a small region(Beijing) reaches 0.95,and the value of R2 is equal to 0.91 while the model was validated with samples from the whole nation.On the other hand,the R2 of a model established based on nationwide samples reaches 0.96,and R2 is equal to 0.91 while it was validated with the samples in Beijing.These models depict well the relationships between rasterization errors and their affecting factors(DA,DP and SG).The analyzing method established in this study can be applied to effectively predicting rasterization errors in other cases as well.展开更多
Raster type of forest inventory data with site and growing stock variables interpreted for small squareshaped grid cells are increasingly available for forest planning.In Finland,there are two sources of this type of ...Raster type of forest inventory data with site and growing stock variables interpreted for small squareshaped grid cells are increasingly available for forest planning.In Finland,there are two sources of this type of lattice data:the multisource national forest inventory and the inventory that is based on airborne laser scanning(ALS).In both cases,stand variables are interpreted for 16 m×16 m cells.Both data sources cover all private forests of Finland and are freely available for forest planning.This study analyzed different ways to use the ALS raster data in forest planning.The analyses were conducted for a grid of 375×375 cells(140,625 cells,of which 97,893 were productive forest).The basic alternatives were to use the cells as calculation units throughout the planning process,or aggregate the cells into segments before planning calculations.The use of cells made it necessary to use spatial optimization to aggregate cuttings and other treatments into blocks that were large enough for the practical implementation of the plan.In addition,allowing premature cuttings in a part of the cells was a prerequisite for compact treatment areas.The use of segments led to 5–9%higher growth predictions than calculations based on cells.In addition,the areas of the most common fertility classes were overestimated and the areas of rare site classes were underestimated when segments were used.The shape of the treatment blocks was more irregular in cell-based planning.Using cells as calculation units instead of segments led to 20 times longer computing time of the whole planning process than the use of segments when the number of grid cells was approximately 100,000.展开更多
Rasterization is a conversion process accompanied with information loss, which includes the loss of features＇ shape, structure, position, attribute and so on. Two chief factors that affect estimating attribute accura...Rasterization is a conversion process accompanied with information loss, which includes the loss of features＇ shape, structure, position, attribute and so on. Two chief factors that affect estimating attribute accuracy loss in rasterization are grid cell size and evaluating method. That is, attribute accuracy loss in rasterization has a close relationship with grid cell size; besides, it is also influenced by evaluating methods. Therefore, it is significant to analyze these two influencing factors comprehensively. Taking land cover data of Sichuan at the scale of 1：250,000 in 2005 as a case, in view of data volume and its processing time of the study region, this study selects 16 spatial scales from 600 m to 30 km, uses rasterizing method based on the Rule of Maximum Area （RMA） in ArcGIS and two evaluating methods of attribute accuracy loss, which are Normal Analysis Method （NAM） and a new Method Based on Grid Cell （MBGC）, respectively, and analyzes the scale effect of attribute （it is area here） accuracy loss at 16 different scales by these two evaluating methods comparatively. The results show that： （1） At the same scale, average area accuracy loss of the entire study region evaluated by MBGC is significantly larger than the one estimated using NAM. Moreover, this discrepancy between the two is obvious in the range of 1 km to 10 km. When the grid cell is larger than 10 km, average area accuracy losses calculated by the two evaluating methods are stable, even tended to parallel. （2） MBGC can not only estimate RMA rasterization attribute accuracy loss accurately, but can express the spatial distribution of the loss objectively. （3） The suitable scale domain for RMA rasterization of land cover data of Sichuan at the scale of 1：250,000 in 2005 is better equal to or less than 800 m, in which the data volume is favorable and the processina time is not too Iona. as well as the area accuracv loss is less than 2.5%.展开更多
A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, si...A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, single layer/raster CNN array is implemented by incorporating the proposed technique. Simulation results have been obtained, and comparison has also been carried out to show the efficiency of the proposed numerical integration algorithm. The analytic expressions for local truncation error and global truncation error are derived. It is seen that the RK-embedded root mean square outperforms the RK-embedded Heronian mean and RK-embedded harmonic mean.展开更多
Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentat...Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentation method,the relationship between SWE and environmental factors in the central part of the Tibetan Plateau was explored using the eigenvector spatial filtering(ESF)regression model,and the influence of different factors on the SWE was explored.Three sizes of 16×16,24×24 and 32×32 were selected to segment raster datasets into blocks.The eigenvectors of the spatial adjacency matrix of the segmented size were selected to be added into the model as spatial factors,and the ESF regression model was constructed for each block in parallel.Results show that precipitation has a great influence on SWE,while surface temperature and NDVI have little influence.Air temperature,elevation and surface temperature have completely different effects in different areas.Compared with the ordinary least square(OLS)linear regression model,geographically weighted regression(GWR)model,spatial lag model(SLM)and spatial error model(SEM),ESF model can eliminate spatial autocorrelation with the highest accuracy.As the segmentation size increases,the complexity of ESF model increases,but the accuracy is improved.展开更多
Semi qualitative index based methods using rankings and ratings are commonly used in susceptibility estimations over a wide area. However, generalized ranking and ratings are not applicable for one single landslide. T...Semi qualitative index based methods using rankings and ratings are commonly used in susceptibility estimations over a wide area. However, generalized ranking and ratings are not applicable for one single landslide. This paper gives an easy and transferable approach to a susceptibility assessment of Huangtupo landslide(P.R. China), using raster addition without taking account for ranking and ratings. Slope, aspect, curvature, location and drainage buffer distance raster data sets have been obtained out of open source digital elevation models using ESRI's Arc GIS. These conditioning factor raster data sets have been translated into raster data sets including simple yes or no criteria, referring to triggering or not. Subsequently they have been added by raster math to acquire a simple raster overlay map.After that this map is compared to initial displacement measurements, obtained by using a ground based synthetic aperture radar device. Acquired data is recalculated to a raster data set using the same spatial extent, to provide the possibility of comparison of the two raster data sets. The results reveal, that 76.35% of all measured movements occur in areas where raster cells include three or more conditioning factors, indicating that easy raster math operations can lead to satisfying results in local scale.展开更多
Among the various scanning techniques, spot and raster scanning are the most frequently adopted. Raster scanning turns off the beam only when each isoenergy slice irradiation is completed. This feature intrinsically s...Among the various scanning techniques, spot and raster scanning are the most frequently adopted. Raster scanning turns off the beam only when each isoenergy slice irradiation is completed. This feature intrinsically solves the leakage dose and frequent beam-switching problems encountered during spot scanning. However, to shorten the delivery time of raster scanning, a sophisticated dose control strategy is required to guarantee dose distribution.In this study, a real-time compensation method with raster scanning for synchrotron systems was designed. It is characterized by a small spot-spacing planning strategy and real-time subtraction of the transient number of particles delivered between two planning-spot positions from the planned number of particles of the subsequent raster point.The efficacy of the compensation method was demonstrated by performing accurate raster scanning simulations with an in-house simulation code and accurate final dose evaluations with a commercial treatment planning system.Given the similar dose evaluation criteria under a practical high scanning speed, compared with the spot scanning method, the total delivery time of the compensated raster scanning method was significantly shortened by 53.3% in the case of irradiating a cubical target and by 28.8% in a pelvic case. Therefore, it can be concluded that real-time compensated raster scanning with a fast scanning configuration can significantly shorten the delivery time compared to that of spot scanning. It is important to reduce the pressure on patients caused by prolonged immobilization and to improve patient throughput capacity at particle therapy centers.展开更多
Office automation （OA） has evolved with the development of computer science,improving staff efficiency.Unstructured information processing is an important aspect of OA; therefore,in this paper,we propose an efficien...Office automation （OA） has evolved with the development of computer science,improving staff efficiency.Unstructured information processing is an important aspect of OA; therefore,in this paper,we propose an efficient method for distinguishing scanned and rasterized document images which can be used in this process.To ensure the efficiency and precision of our method,two steps are included：rapid processing and classification using noise features.In the first step,color,skew,and isolated noise features are used to identify the source of the images.In the second step,noise features are extracted from the input image and a support vector machine （SVM） classifier is used for classification.Our experiments show that our method has high precision and speed for distinguishing scanned and rasterized document images.展开更多
Due to the advances in Web technologies,various raster maps are available through Web Map Services such as Google maps and Yahoo maps.These online maps are used to visualize diverse types of disasters.Understanding di...Due to the advances in Web technologies,various raster maps are available through Web Map Services such as Google maps and Yahoo maps.These online maps are used to visualize diverse types of disasters.Understanding disasters with these online maps has become an important research issue.In this article,we propose a map-based general-purpose emergency management support system based on a computational model of generalized(multiplicatively weighted,order-k,and Minkowski-metric)Voronoi diagrams.The proposed system tessellates Web maps and models disasters(or emergency response units)having different weights in the complete order from 1 to k-1 in the three popular Minkowski metrics(Euclidean,Manhattan,and Maximum distance)pro-vide insightful information for various what-if emergency scenarios.The proposed map-based emergency management support system systematically supports neighboring queries,districting queries,location optimization queries,and routing queries.We pro-vide specific examples to illustrate how our system supports these queries.展开更多
We have applied Raster Image Correlation Spectroscopy (RICS) technique to characterize the dynamics of protein 53 (p53) in living cells before and after the treatment with DNA damaging agents. HeLa cells expressing Gr...We have applied Raster Image Correlation Spectroscopy (RICS) technique to characterize the dynamics of protein 53 (p53) in living cells before and after the treatment with DNA damaging agents. HeLa cells expressing Green Fluores-cent Protein (GFP) tagged p53 were incubated with and without DNA damaging agents, cisplatin or eptoposide, which are widely used as chemotherapeutic drugs. Then, the diffusion coefficient of GFP-p53 was determined by RICS and it was significantly reduced after the drug treatment while that of the one without drug treatment was not. It is suggested that the drugs induced the interaction of p53 with either other proteins or DNA. Together, our results demonstrated that RICS is able to detect the protein dynamics which may be associated with protein-protein or protein-DNA interactions in living cells and it may be useful for the drug screening.展开更多
Recent development and recognition methods of raster to vector conversion for engineering drawings are presented. The advantages and disadvantages of all existing models are analyzed. Some research challenges and futu...Recent development and recognition methods of raster to vector conversion for engineering drawings are presented. The advantages and disadvantages of all existing models are analyzed. Some research challenges and future directions are discussed.展开更多
In the design of a graphic processing unit(GPU),the processing speed of triangle rasterization is an important factor that determines the performance of the GPU.An architecture of a multi-tile parallel-scan rasterizat...In the design of a graphic processing unit(GPU),the processing speed of triangle rasterization is an important factor that determines the performance of the GPU.An architecture of a multi-tile parallel-scan rasterization accelerator was proposed in this paper.The accelerator uses a bounding box algorithm to improve scanning efficiency.It rasterizes multiple tiles in parallel and scans multiple lines at the same time within each tile.This highly parallel approach drastically improves the performance of rasterization.Using the 65 nm process standard cell library of Semiconductor Manufacturing International Corporation(SMIC),the accelerator can be synthesized to a maximum clock frequency of 220 MHz.An implementation on the Genesys2 field programmable gate array(FPGA)board fully verifies the functionality of the accelerator.The implementation shows a significant improvement in rendering speed and efficiency and proves its suitability for high-performance rasterization.展开更多
针对跳点搜索算法(jump point search,JPS)在路径规划过程中出现的穿越墙角的不安全行为,提出了一种基于蜂窝栅格地图的跳点搜索算法(honeycomb raster map-JPS,H-JPS)。构建蜂窝栅格地图代替传统栅格地图,在JPS算法的基础上结合蜂窝栅...针对跳点搜索算法(jump point search,JPS)在路径规划过程中出现的穿越墙角的不安全行为,提出了一种基于蜂窝栅格地图的跳点搜索算法(honeycomb raster map-JPS,H-JPS)。构建蜂窝栅格地图代替传统栅格地图,在JPS算法的基础上结合蜂窝栅格修改了剪枝规则与跳点判断规则,再利用蜂窝栅格特点设计了新的启发式函数来提高搜索效率,通过找寻最远节点的节点更新规则来优化生成的轨迹。利用Matlab仿真平台验证算法的搜索效率和安全性,结果表明,相较于传统JPS算法,采用H-JPS算法进行路径规划能够完全消除危险节点,路径规划时间和长度分别缩短了41.9%和11.1%,显著提高了搜索效率。展开更多
基金Deep-time Digital Earth(DDE)Big Science Program(No.GJ-C03-SGF-2025-004)National Natural Science Foundation of China(No.42394063)Sichuan Science and Technology Program(No.2025ZNSFSC0325).
文摘Topographic maps,as essential tools and sources of information for geographic research,contain precise spatial locations and rich map features,and they illustrate spatio-temporal information on the distribution and differences of various surface features.Currently,topographic maps are mainly stored in raster and vector formats.Extraction of the spatio-temporal knowledge in the maps—such as spatial distribution patterns,feature relationships,and dynamic evolution—still primarily relies on manual interpretation.However,manual interpretation is time-consuming and laborious,especially for large-scale,long-term map knowledge extraction and application.With the development of artificial intelligence technology,it is possible to improve the automation level of map knowledge interpretation.Therefore,the present study proposes an automatic interpretation method for raster topographic map knowledge based on deep learning.To address the limitations of current data-driven intelligent technology in learning map spatial relations and cognitive logic,we establish a formal description of map knowledge by mapping the relationship between map knowledge and features,thereby ensuring interpretation accuracy.Subsequently,deep learning techniques are employed to extract map features automatically,and the spatio-temporal knowledge is constructed by combining formal descriptions of geographic feature knowledge.Validation experiments demonstrate that the proposed method effectively achieves automatic interpretation of spatio-temporal knowledge of geographic features in maps,with an accuracy exceeding 80%.The findings of the present study contribute to machine understanding of spatio-temporal differences in map knowledge and advances the intelligent interpretation and utilization of cartographic information.
基金Under the auspices of Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA05050000)Special Program for Informatization of Chinese Academy of Sciences(No.INF0-115-C01-SDB3-02)
文摘Vector-to-raster conversion is a process accompanied with errors.The errors are classified into predicted errors before rasterization and actual errors after that.Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality.Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.In this study,land cover data of China at a scale of 1:250 000 were taken as an example for analyzing the relationship between rasterization errors and the density of arc length(DA),the density of polygon(DP) and the size of grid cells(SG).Significant correlations were found between the errors and DA,DP and SG.The correlation coefficient(R2) of a model established based on samples collected in a small region(Beijing) reaches 0.95,and the value of R2 is equal to 0.91 while the model was validated with samples from the whole nation.On the other hand,the R2 of a model established based on nationwide samples reaches 0.96,and R2 is equal to 0.91 while it was validated with the samples in Beijing.These models depict well the relationships between rasterization errors and their affecting factors(DA,DP and SG).The analyzing method established in this study can be applied to effectively predicting rasterization errors in other cases as well.
基金Open access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital
文摘Raster type of forest inventory data with site and growing stock variables interpreted for small squareshaped grid cells are increasingly available for forest planning.In Finland,there are two sources of this type of lattice data:the multisource national forest inventory and the inventory that is based on airborne laser scanning(ALS).In both cases,stand variables are interpreted for 16 m×16 m cells.Both data sources cover all private forests of Finland and are freely available for forest planning.This study analyzed different ways to use the ALS raster data in forest planning.The analyses were conducted for a grid of 375×375 cells(140,625 cells,of which 97,893 were productive forest).The basic alternatives were to use the cells as calculation units throughout the planning process,or aggregate the cells into segments before planning calculations.The use of cells made it necessary to use spatial optimization to aggregate cuttings and other treatments into blocks that were large enough for the practical implementation of the plan.In addition,allowing premature cuttings in a part of the cells was a prerequisite for compact treatment areas.The use of segments led to 5–9%higher growth predictions than calculations based on cells.In addition,the areas of the most common fertility classes were overestimated and the areas of rare site classes were underestimated when segments were used.The shape of the treatment blocks was more irregular in cell-based planning.Using cells as calculation units instead of segments led to 20 times longer computing time of the whole planning process than the use of segments when the number of grid cells was approximately 100,000.
基金The Independent Research of the State Key Laboratory of Resource and Environmental Information System,No.O88RA100SAThe Third Innovative and Cutting-edge Projects of Institute of Geographic Sciences andNatural Resources Research, CAS, No.O66U0309SZ
文摘Rasterization is a conversion process accompanied with information loss, which includes the loss of features＇ shape, structure, position, attribute and so on. Two chief factors that affect estimating attribute accuracy loss in rasterization are grid cell size and evaluating method. That is, attribute accuracy loss in rasterization has a close relationship with grid cell size; besides, it is also influenced by evaluating methods. Therefore, it is significant to analyze these two influencing factors comprehensively. Taking land cover data of Sichuan at the scale of 1：250,000 in 2005 as a case, in view of data volume and its processing time of the study region, this study selects 16 spatial scales from 600 m to 30 km, uses rasterizing method based on the Rule of Maximum Area （RMA） in ArcGIS and two evaluating methods of attribute accuracy loss, which are Normal Analysis Method （NAM） and a new Method Based on Grid Cell （MBGC）, respectively, and analyzes the scale effect of attribute （it is area here） accuracy loss at 16 different scales by these two evaluating methods comparatively. The results show that： （1） At the same scale, average area accuracy loss of the entire study region evaluated by MBGC is significantly larger than the one estimated using NAM. Moreover, this discrepancy between the two is obvious in the range of 1 km to 10 km. When the grid cell is larger than 10 km, average area accuracy losses calculated by the two evaluating methods are stable, even tended to parallel. （2） MBGC can not only estimate RMA rasterization attribute accuracy loss accurately, but can express the spatial distribution of the loss objectively. （3） The suitable scale domain for RMA rasterization of land cover data of Sichuan at the scale of 1：250,000 in 2005 is better equal to or less than 800 m, in which the data volume is favorable and the processina time is not too Iona. as well as the area accuracv loss is less than 2.5%.
基金supported as a part of Technical Quality Improvement Programme (TEQIP)
文摘A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, single layer/raster CNN array is implemented by incorporating the proposed technique. Simulation results have been obtained, and comparison has also been carried out to show the efficiency of the proposed numerical integration algorithm. The analytic expressions for local truncation error and global truncation error are derived. It is seen that the RK-embedded root mean square outperforms the RK-embedded Heronian mean and RK-embedded harmonic mean.
基金funded by the National Key S&T Special Projects of China(grant number:2018YFB0505302)the National Nature Science Foundation of China(grant number:41671380)。
文摘Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentation method,the relationship between SWE and environmental factors in the central part of the Tibetan Plateau was explored using the eigenvector spatial filtering(ESF)regression model,and the influence of different factors on the SWE was explored.Three sizes of 16×16,24×24 and 32×32 were selected to segment raster datasets into blocks.The eigenvectors of the spatial adjacency matrix of the segmented size were selected to be added into the model as spatial factors,and the ESF regression model was constructed for each block in parallel.Results show that precipitation has a great influence on SWE,while surface temperature and NDVI have little influence.Air temperature,elevation and surface temperature have completely different effects in different areas.Compared with the ordinary least square(OLS)linear regression model,geographically weighted regression(GWR)model,spatial lag model(SLM)and spatial error model(SEM),ESF model can eliminate spatial autocorrelation with the highest accuracy.As the segmentation size increases,the complexity of ESF model increases,but the accuracy is improved.
基金a part of the interdisciplinary "YANGTZE-Project" which is supported by the German Federal Ministry of Education and Research (BMBF)the BMBF for the great financial support
文摘Semi qualitative index based methods using rankings and ratings are commonly used in susceptibility estimations over a wide area. However, generalized ranking and ratings are not applicable for one single landslide. This paper gives an easy and transferable approach to a susceptibility assessment of Huangtupo landslide(P.R. China), using raster addition without taking account for ranking and ratings. Slope, aspect, curvature, location and drainage buffer distance raster data sets have been obtained out of open source digital elevation models using ESRI's Arc GIS. These conditioning factor raster data sets have been translated into raster data sets including simple yes or no criteria, referring to triggering or not. Subsequently they have been added by raster math to acquire a simple raster overlay map.After that this map is compared to initial displacement measurements, obtained by using a ground based synthetic aperture radar device. Acquired data is recalculated to a raster data set using the same spatial extent, to provide the possibility of comparison of the two raster data sets. The results reveal, that 76.35% of all measured movements occur in areas where raster cells include three or more conditioning factors, indicating that easy raster math operations can lead to satisfying results in local scale.
基金supported by the National Key Research and Development Program of China(No.2016YFC0105408)。
文摘Among the various scanning techniques, spot and raster scanning are the most frequently adopted. Raster scanning turns off the beam only when each isoenergy slice irradiation is completed. This feature intrinsically solves the leakage dose and frequent beam-switching problems encountered during spot scanning. However, to shorten the delivery time of raster scanning, a sophisticated dose control strategy is required to guarantee dose distribution.In this study, a real-time compensation method with raster scanning for synchrotron systems was designed. It is characterized by a small spot-spacing planning strategy and real-time subtraction of the transient number of particles delivered between two planning-spot positions from the planned number of particles of the subsequent raster point.The efficacy of the compensation method was demonstrated by performing accurate raster scanning simulations with an in-house simulation code and accurate final dose evaluations with a commercial treatment planning system.Given the similar dose evaluation criteria under a practical high scanning speed, compared with the spot scanning method, the total delivery time of the compensated raster scanning method was significantly shortened by 53.3% in the case of irradiating a cubical target and by 28.8% in a pelvic case. Therefore, it can be concluded that real-time compensated raster scanning with a fast scanning configuration can significantly shorten the delivery time compared to that of spot scanning. It is important to reduce the pressure on patients caused by prolonged immobilization and to improve patient throughput capacity at particle therapy centers.
文摘Office automation （OA） has evolved with the development of computer science,improving staff efficiency.Unstructured information processing is an important aspect of OA; therefore,in this paper,we propose an efficient method for distinguishing scanned and rasterized document images which can be used in this process.To ensure the efficiency and precision of our method,two steps are included：rapid processing and classification using noise features.In the first step,color,skew,and isolated noise features are used to identify the source of the images.In the second step,noise features are extracted from the input image and a support vector machine （SVM） classifier is used for classification.Our experiments show that our method has high precision and speed for distinguishing scanned and rasterized document images.
基金Supported by the Collaboration Across Boundary Grant within James Cook University
文摘Due to the advances in Web technologies,various raster maps are available through Web Map Services such as Google maps and Yahoo maps.These online maps are used to visualize diverse types of disasters.Understanding disasters with these online maps has become an important research issue.In this article,we propose a map-based general-purpose emergency management support system based on a computational model of generalized(multiplicatively weighted,order-k,and Minkowski-metric)Voronoi diagrams.The proposed system tessellates Web maps and models disasters(or emergency response units)having different weights in the complete order from 1 to k-1 in the three popular Minkowski metrics(Euclidean,Manhattan,and Maximum distance)pro-vide insightful information for various what-if emergency scenarios.The proposed map-based emergency management support system systematically supports neighboring queries,districting queries,location optimization queries,and routing queries.We pro-vide specific examples to illustrate how our system supports these queries.
文摘We have applied Raster Image Correlation Spectroscopy (RICS) technique to characterize the dynamics of protein 53 (p53) in living cells before and after the treatment with DNA damaging agents. HeLa cells expressing Green Fluores-cent Protein (GFP) tagged p53 were incubated with and without DNA damaging agents, cisplatin or eptoposide, which are widely used as chemotherapeutic drugs. Then, the diffusion coefficient of GFP-p53 was determined by RICS and it was significantly reduced after the drug treatment while that of the one without drug treatment was not. It is suggested that the drugs induced the interaction of p53 with either other proteins or DNA. Together, our results demonstrated that RICS is able to detect the protein dynamics which may be associated with protein-protein or protein-DNA interactions in living cells and it may be useful for the drug screening.
文摘Recent development and recognition methods of raster to vector conversion for engineering drawings are presented. The advantages and disadvantages of all existing models are analyzed. Some research challenges and future directions are discussed.
基金the Scientific Research Program Funded by Shaanxi Provincial Education Department(20JY058)。
文摘In the design of a graphic processing unit(GPU),the processing speed of triangle rasterization is an important factor that determines the performance of the GPU.An architecture of a multi-tile parallel-scan rasterization accelerator was proposed in this paper.The accelerator uses a bounding box algorithm to improve scanning efficiency.It rasterizes multiple tiles in parallel and scans multiple lines at the same time within each tile.This highly parallel approach drastically improves the performance of rasterization.Using the 65 nm process standard cell library of Semiconductor Manufacturing International Corporation(SMIC),the accelerator can be synthesized to a maximum clock frequency of 220 MHz.An implementation on the Genesys2 field programmable gate array(FPGA)board fully verifies the functionality of the accelerator.The implementation shows a significant improvement in rendering speed and efficiency and proves its suitability for high-performance rasterization.
文摘针对跳点搜索算法(jump point search,JPS)在路径规划过程中出现的穿越墙角的不安全行为,提出了一种基于蜂窝栅格地图的跳点搜索算法(honeycomb raster map-JPS,H-JPS)。构建蜂窝栅格地图代替传统栅格地图,在JPS算法的基础上结合蜂窝栅格修改了剪枝规则与跳点判断规则,再利用蜂窝栅格特点设计了新的启发式函数来提高搜索效率,通过找寻最远节点的节点更新规则来优化生成的轨迹。利用Matlab仿真平台验证算法的搜索效率和安全性,结果表明,相较于传统JPS算法,采用H-JPS算法进行路径规划能够完全消除危险节点,路径规划时间和长度分别缩短了41.9%和11.1%,显著提高了搜索效率。
