Shape irregularity,a sub-factor of parcel fragmentation is a problem that hinders sustainable agriculture and is solved using land consolidation projects.Determination of the parcel shape degree contributes significan...Shape irregularity,a sub-factor of parcel fragmentation is a problem that hinders sustainable agriculture and is solved using land consolidation projects.Determination of the parcel shape degree contributes significantly to spatial prioritization where there is also a high probability of achieving positive effects of consolidation projects.This study aims to determine the shape degree of the agricultural parcels both at singular and rural county scales in Tekirdag Province,Turkey in 2020 by combining the parcel shape index(PSI) with the minimum bounding geometry index(MBG) to improve parcel scores.Hot-spot zones of the highly irregular and near optimum parcels were also determined using Getis-Ord G_(i)^(*) statistic.The parcel degrees were classified into four categories,namely highly irregular,irregular,regular and near optimum.The obtained unweighted scores of the parameters exhibit deviations from the expected values.After weighting by pairwise comparison,the values approached ideal scores.Among 346 740 parcels,53% were highly irregular and irregular and 47% were regular and near optimum shapes after weighting whereas these were 70% and 30%,respectively before weighting.The average parcel degree of 63 rural counties was regular while the average parcel degree of the remaining 264 rural counties was irregular.The combined use of PSI and MBG index improved the correctness of the parcel shape score.It could be suggested to use as a tool in land consolidation prioritization.展开更多
Damage to parcels reduces customer satisfactionwith delivery services and increases return-logistics costs.This can be prevented by detecting and addressing the damage before the parcels reach the customer.Consequentl...Damage to parcels reduces customer satisfactionwith delivery services and increases return-logistics costs.This can be prevented by detecting and addressing the damage before the parcels reach the customer.Consequently,various studies have been conducted on deep learning techniques related to the detection of parcel damage.This study proposes a deep learning-based damage detectionmethod for various types of parcels.Themethod is intended to be part of a parcel information-recognition systemthat identifies the volume and shipping information of parcels,and determines whether they are damaged;this method is intended for use in the actual parcel-transportation process.For this purpose,1)the study acquired image data in an environment simulating the actual parcel-transportation process,and 2)the training dataset was expanded based on StyleGAN3 with adaptive discriminator augmentation.Additionally,3)a preliminary distinction was made between the appearance of parcels and their damage status to enhance the performance of the parcel damage detection model and analyze the causes of parcel damage.Finally,using the dataset constructed based on the proposed method,a damage type detection model was trained,and its mean average precision was confirmed.This model can improve customer satisfaction and reduce return costs for parcel delivery companies.展开更多
The human striatum is essential for both lowand high-level functions and has been implicated in the pathophysiology of various prevalent disorders,including Parkinson's disease(PD)and schizophrenia(SCZ).It is know...The human striatum is essential for both lowand high-level functions and has been implicated in the pathophysiology of various prevalent disorders,including Parkinson's disease(PD)and schizophrenia(SCZ).It is known to consist of structurally and functionally divergent subdivisions.However,previous parcellations are based on a single neuroimaging modality,leaving the extent of the multi-modal organization of the striatum unknown.Here,we investigated the organization of the striatum across three modalities—resting-state functional connectivity,probabilistic diffusion tractography,and structural covariance—to provide a holistic convergent view of its structure and function.We found convergent clusters in the dorsal,dorsolateral,rostral,ventral,and caudal striatum.Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions,while the caudal striatum was related to action execution.Interestingly,significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ,but atrophy in the dorsolateral striatum was specifically attributable to PD.Our study revealed a cross-modal convergent organization of the striatum,representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.展开更多
Recently, restingstate functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain ...Recently, restingstate functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, so functional connectivity maps contain redundant information, which not only impairs the computational efficiency during clustering, but also reduces the accuracy of clustering results. The aim of this study was to propose featurereduction approaches to reduce the redundancy and to develop semisimulated data with defined ground truth to evaluate these approaches. We proposed a featurereduction approach based on the Affinity Propagation Algorithm （APA） and compared it with the classic feature reduction approach based on Principal Component Analysis （PCA）. We tested the two approaches to the parcellation of both semisimulated and real seed regions using the Kmeans algorithm and designed two experiments to evaluate their noise resistance. We found that all functional connectivitymaps （with/without feature reduction） provided correct information for the parcellation of the semi simulated seed region and the computational efficiency was greatly improved by both feature reduction approaches. Meanwhile, the APAbased featurereduction approach outperformed the PCA based approach in noiseresistance. The results suggested that functional connectivity maps can provide correct information for cortical parcellation, and featurereduction does not significantly change the information. Considering the improvement in computational efficiency and the noiseresistance, featurereduction of functional connectivity maps before cortical parcellation is both feasible and necessary.展开更多
Heavy rains occur in China frequently, which often bring us floods and serious disasters in the summer half-year. The meso-scale heavy rain parcels (MHRP) in the mid-latitude are usually developed in following cases:I...Heavy rains occur in China frequently, which often bring us floods and serious disasters in the summer half-year. The meso-scale heavy rain parcels (MHRP) in the mid-latitude are usually developed in following cases:I.By the approaching, meeting and / or overlapping of different weather systems, when two or more different rainfall systems are getting to conjugate, some MHRPs could be developed, such as: 1) a new cold/warm front or squall line approaches an old front or squall, even when the old one is somewhat decrepit; 2) at the places where two or more synoptic systems with different characteristics are meeting together, such as the meeting of tropical cyclone with the cold airs coming from the mid- and / or high-latitudes, or the low latitude vortex meeting with the westerly trough; 3) at the intersections of some different weather systems, such as the intersection of drylines, squall lines or fronts moving from different directions; and 4) by the overlapping of rainfall parcels produced continuously from a meso-generation centre.II.Resonance Effect and Tibetan Plateau Influence are two reasons why high frequency of heavy and torrential rains arround the meiyu front is discussed also.展开更多
Mapping abandoned land is very important for accurate agricultural management.However,in karst mountainous areas,continuous high-resolution optical images are difficult to obtain in rainy weather,and the land is fragm...Mapping abandoned land is very important for accurate agricultural management.However,in karst mountainous areas,continuous high-resolution optical images are difficult to obtain in rainy weather,and the land is fragmented,which poses a great challenge for remote sensing monitoring of agriculture activities.In this study,a new method for identifying abandoned land is proposed:firstly,a few Google Earth images are used to transform arable land into accurate vectorized geo-parcels;secondly,a time-series data set was constructed using Sentinel-1A Alpha parameters for 2020 on each farmland geoparcel;thirdly,the semi-variation function(SVF)was used to analyze the spatial-temporal characteristics,then identify abandoned land.The results show:(1)On the basis of accurate spatial information and boundary of farmland land,the SAR time-series dataset reflects the structure and time-series response.abandoned land with an accuracy of 80.25%.The problem of remote sensing monitoring in rainy regions and complex surface areas is well-resolved.(2)The spatial heterogeneity of abandoned land is more obvious than that of cultivated land within geoparcels.The step size for significant changes in the SVF of abandoned land is shorter than that of cultivated land.(3)The SVF time sequence curve presented a strong peak feature when farmland was abandoned.This reveals that the internal spatial structure of abandoned land is more disordered and complex.It showed that time-series variations of spatial structure within cultivated land have broader applications in remote sensing monitoring of agriculture in complex imaging environments.展开更多
This paper presents a systematic view of most up-to-date tools, technologies and techniques which is appropriate not only for effective decision making, but also helpful for competent administration to provide efficie...This paper presents a systematic view of most up-to-date tools, technologies and techniques which is appropriate not only for effective decision making, but also helpful for competent administration to provide efficient resolution for spatial troubles of Khasra and Parcel management. Different Data collection techniques have been applied on different data sources. Worldview II of 0.5 resolution image, scanned Master Plan and Cadastral/Khasra Maps was used for development of geodatabase for spatial and non-spatial entities using ArcGIS 10.2. Multiple processing on Satellite Imagery using ERDAS Imagine was performed like Image enhancement, Mosaicking and Color Balancing, Image Geo-referencing and Raster Cataloging. Development of Customize Graphical User Interface (GUI) for DHA’s officials and administrator makes efficient decision in society matters. This is the first spatial GUI, for DHA to plan and maintain society’s activities efficiently, in the form of ArcMap Add-Ins. These Add-Ins are written in C#.Net using ArcObjects APIs within MSVS 2012.展开更多
In recent years,with the rapid development of cross-border e-commerce,international postal parcels have been increasing sharply,thus giving rise to a new way for alien biological invasion.According to the"animal ...In recent years,with the rapid development of cross-border e-commerce,international postal parcels have been increasing sharply,thus giving rise to a new way for alien biological invasion.According to the"animal and plant quarantine information platform"of the General Adminis-tration of Customs,postal inspection system intercepted a total of 4975 harmful organisms nationwide.There were 219 quarantine organisms,including 142 insects,27 weeds,12 nematodes,29 fungi,1 bacterium and 8 viruses.Insects accounted for 64.84%of the quarantine organisms,among which Hypothenemus hampei had the highest interception frequency.Up to 71.36%of those harmful organisms were from seedlings,yet47.31%organisms came from products exported from India.These analyses indicate the direction of future portal quarantine work and lay a theoret-ical foundation for better guarding the biological security.展开更多
Nowadays, many different kinds of delivery companies transport their own kinds of parcels and offer their own services, which have caused a lot waste of resources. In addition, the volume of parcels in all cities that...Nowadays, many different kinds of delivery companies transport their own kinds of parcels and offer their own services, which have caused a lot waste of resources. In addition, the volume of parcels in all cities that need to be delivered has been grown dramatically. To cope with these problems, a uniform parcel delivery system in a smart city which can offer service to all kinds of customers in the city including manufactures, department stores, restaurants, individual people and so forth was designed. This system uses IoT (Internet of Things) and RFID technology, combining computer network technology, wireless communication and cloud computing. With this system, the whole package delivery process including classification of packages, vehicle scheduling, path planning, transportation monitoring can be intellectualized as well as managed automatically, and the use of both material resources and manpower resources can be reduced accordingly.展开更多
Objective.Objective of this work is the development and evaluation of a cortical parcellation framework based on tractography-derived brain structural connectivity.Impact Statement.The proposed framework utilizes nove...Objective.Objective of this work is the development and evaluation of a cortical parcellation framework based on tractography-derived brain structural connectivity.Impact Statement.The proposed framework utilizes novel spatial-graph representation learning methods for solving the task of cortical parcellation,an important medical image analysis and neuroscientific problem.Introduction.The concept of“connectional fingerprint”has motivated many investigations on the connectivity-based cortical parcellation,especially with the technical advancement of diffusion imaging.Previous studies on multiple brain regions have been conducted with promising results.However,performance and applicability of these models are limited by the relatively simple computational scheme and the lack of effective representation of brain imaging data.Methods.We propose the Spatial-graph Convolution Parcellation(SGCP)framework,a two-stage deep learning-based modeling for the graph representation brain imaging.In the first stage,SGCP learns an effective embedding of the input data through a self-supervised contrastive learning scheme with the backbone encoder of a spatial-graph convolution network.In the second stage,SGCP learns a supervised classifier to perform voxel-wise classification for parcellating the desired brain region.Results.SGCP is evaluated on the parcellation task for 5 brain regions in a 15-subject DWI dataset.Performance comparisons between SGCP,traditional parcellation methods,and other deep learning-based methods show that SGCP can achieve superior performance in all the cases.Conclusion.Consistent good performance of the proposed SGCP framework indicates its potential to be used as a general solution for investigating the regional/subregional composition of human brain based on one or more connectivity measurements.展开更多
The quantity of the imported parcels in China has increased rapidly,becoming an important means for criminals to hide the prohibited animal and plant quarantine objects.The x-ray applied to the port of post inspection...The quantity of the imported parcels in China has increased rapidly,becoming an important means for criminals to hide the prohibited animal and plant quarantine objects.The x-ray applied to the port of post inspection can speed up inspection and better protect the ecological safety of China by mastering its method of judging animal and plant quarantine objects.展开更多
Objective Accurate infant brain parcellation is crucial for understanding early brain development;however,it is challenging due to the inherent low tissue contrast,high noise,and severe partial volume effects in infan...Objective Accurate infant brain parcellation is crucial for understanding early brain development;however,it is challenging due to the inherent low tissue contrast,high noise,and severe partial volume effects in infant magnetic resonance images(MRIs).The aim of this study was to develop an end-to-end pipeline that enabled accurate parcellation of infant brain MRIs.Methods We proposed an end-to-end pipeline that employs a two-stage global-to-local approach for accurate parcellation of infant brain MRIs.Specifically,in the global regions of interest(ROIs)localization stage,a combination of transformer and convolution operations was employed to capture both global spatial features and fine texture features,enabling an approximate localization of the ROIs across the whole brain.In the local ROIs refinement stage,leveraging the position priors from the first stage along with the raw MRIs,the boundaries of the ROIs are refined for a more accurate parcellation.Results We utilized the Dice ratio to evaluate the accuracy of parcellation results.Results on 263 subjects from National Database for Autism Research(NDAR),Baby Connectome Project(BCP)and Cross-site datasets demonstrated the better accuracy and robustness of our method than other competing methods.Conclusion Our end-to-end pipeline may be capable of accurately parcellating 6-month-old infant brain MRIs.展开更多
The e-commerce industry has experienced significant growth in the past decade,particu-larly post-COVID.To accommodate such growth,the parcel delivery sector has also grown rapidly.However,there is a lack of study that...The e-commerce industry has experienced significant growth in the past decade,particu-larly post-COVID.To accommodate such growth,the parcel delivery sector has also grown rapidly.However,there is a lack of study that properly evaluates its social and environ-mental impacts at a large scale.A model is proposed to analyze such impacts.A parcel gen-eration process is presented to convert public data into parcel volumes and stops.A continuous approximation model is fitted to estimate the length of parcel service tours.A case study is conducted using New York City(NYC)data.The parcel generation is shown to be a valid fit.The continuous approximation model parameters have R2 values of 98%or higher.The model output is validated against UPS truck trips.Application of the model to 2021 suggests residential parcel deliveries contributed to 0.05%of total daily vehicle-kilometer-traveled(VKT)in NYC corresponding to 14.4 metric tons of carbon equivalent(MTCE)emissions per day.COVID-19 contributed to an increase in parcel deliveries that led to up to 1064.3 MTCE of annual greenhouse gas(GHG)emissions in NYC(which could power 532 standard US households for a year).The existing bike lane infrastructure can support the substitution of 17%of parcel deliveries by cargo bikes,which would reduce VKT by 11%.Adding 3 km of bike lanes to connect Amazon facilities can expand their cargo bike substitution benefit from a VKT reduction of 5%up to 30%.If 28 km of additional bike lanes are made,parcel delivery substitution citywide could increase from 17%to 34%via cargo bike and save an additional 2.3 MTCE per day.Cargo bike priorities can be set to reduce GHG emissions for lower-income neighborhoods including Harlem,Sunset Park,and Bushwick.展开更多
精细的田块数据是现代农业的重要基础资料,该研究针对从高分辨率遥感影像中提取田块精细数据的需求,建立了一种先验知识融合语义特征的冬小麦田块精细提取方法(prior knowledge and semantic features integration-based farmland parce...精细的田块数据是现代农业的重要基础资料,该研究针对从高分辨率遥感影像中提取田块精细数据的需求,建立了一种先验知识融合语义特征的冬小麦田块精细提取方法(prior knowledge and semantic features integration-based farmland parcel extraction methodology,PKFFPE),PKFFPE以遥感图像和相应的边缘图像作为输入,采用编码器-解码器结构进行特征提取,利用多尺度注意力模块捕获不同尺度的关键特征,使用SoftMax对图像进行初步分割;通过深入分析同一田块内颜色、纹理等特征的分布规律获取先验知识,利用先验知识建立后处理方法,对初分割结果进行优化,生成田块精细数据。选择河北省邯郸市馆陶县和山东省泰安市宁阳县作为试验区,用于验证PKFFPE方法在平原地区和丘陵地区的适用性;选择UNet、ErfNet、SegNet、EIGNet,以及面向对象分类的方法作为初分割的对比方法,选择条件随机场和形态学处理作为的后处理的对比方法开展对比试验。试验结果表明,PKFFPE方法在馆陶县、宁阳县结果的准确率(96.1%、93.2%)、精确率(90.6%、87.6%)、召回率(93.2%、90.6%)、和F1分数(91.9%,89.0%)均优于对比方法,证明了PKFFPE方法在从高分辨遥感影像中提取田块精细数据方面具有突出的优势,能够应用于科研和生产实践。展开更多
文摘Shape irregularity,a sub-factor of parcel fragmentation is a problem that hinders sustainable agriculture and is solved using land consolidation projects.Determination of the parcel shape degree contributes significantly to spatial prioritization where there is also a high probability of achieving positive effects of consolidation projects.This study aims to determine the shape degree of the agricultural parcels both at singular and rural county scales in Tekirdag Province,Turkey in 2020 by combining the parcel shape index(PSI) with the minimum bounding geometry index(MBG) to improve parcel scores.Hot-spot zones of the highly irregular and near optimum parcels were also determined using Getis-Ord G_(i)^(*) statistic.The parcel degrees were classified into four categories,namely highly irregular,irregular,regular and near optimum.The obtained unweighted scores of the parameters exhibit deviations from the expected values.After weighting by pairwise comparison,the values approached ideal scores.Among 346 740 parcels,53% were highly irregular and irregular and 47% were regular and near optimum shapes after weighting whereas these were 70% and 30%,respectively before weighting.The average parcel degree of 63 rural counties was regular while the average parcel degree of the remaining 264 rural counties was irregular.The combined use of PSI and MBG index improved the correctness of the parcel shape score.It could be suggested to use as a tool in land consolidation prioritization.
基金supported by a Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure,and Transport(Grant 1615013176)(https://www.kaia.re.kr/eng/main.do,accessed on 01/06/2024)supported by a Korea Evaluation Institute of Industrial Technology(KEIT)grant funded by the Korean Government(MOTIE)(141518499)(https://www.keit.re.kr/index.es?sid=a2,accessed on 01/06/2024).
文摘Damage to parcels reduces customer satisfactionwith delivery services and increases return-logistics costs.This can be prevented by detecting and addressing the damage before the parcels reach the customer.Consequently,various studies have been conducted on deep learning techniques related to the detection of parcel damage.This study proposes a deep learning-based damage detectionmethod for various types of parcels.Themethod is intended to be part of a parcel information-recognition systemthat identifies the volume and shipping information of parcels,and determines whether they are damaged;this method is intended for use in the actual parcel-transportation process.For this purpose,1)the study acquired image data in an environment simulating the actual parcel-transportation process,and 2)the training dataset was expanded based on StyleGAN3 with adaptive discriminator augmentation.Additionally,3)a preliminary distinction was made between the appearance of parcels and their damage status to enhance the performance of the parcel damage detection model and analyze the causes of parcel damage.Finally,using the dataset constructed based on the proposed method,a damage type detection model was trained,and its mean average precision was confirmed.This model can improve customer satisfaction and reduce return costs for parcel delivery companies.
基金This work was supported by the Deutsche Forschungsgemeinschaft(GE 2835/1-1,El 816/4-1)the Helmholtz Portfolio Theme 4 Supercomputing and Modelling for the Human Brain'and the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No.785907(HBP SGA2)We gratefully acknowledge financial support from the China Scholarship Council(201606750003).
文摘The human striatum is essential for both lowand high-level functions and has been implicated in the pathophysiology of various prevalent disorders,including Parkinson's disease(PD)and schizophrenia(SCZ).It is known to consist of structurally and functionally divergent subdivisions.However,previous parcellations are based on a single neuroimaging modality,leaving the extent of the multi-modal organization of the striatum unknown.Here,we investigated the organization of the striatum across three modalities—resting-state functional connectivity,probabilistic diffusion tractography,and structural covariance—to provide a holistic convergent view of its structure and function.We found convergent clusters in the dorsal,dorsolateral,rostral,ventral,and caudal striatum.Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions,while the caudal striatum was related to action execution.Interestingly,significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ,but atrophy in the dorsolateral striatum was specifically attributable to PD.Our study revealed a cross-modal convergent organization of the striatum,representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.
基金supported by the National Basic Research Development Program (973 Program) of China (2012CBA01304, 2011CB707800)the National High Technology Research and Development Program (863 Program) of China (2012AA020701)+2 种基金the National Natural Science Foundation of China (31271167, 31271168, 81271495, 31070963, 31070965)the Strategic Priority Research Program of the Chinese Academy of Science, China (XDB02020500)the Development and Reform Project of Yunnan Province, China
文摘Recently, restingstate functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, so functional connectivity maps contain redundant information, which not only impairs the computational efficiency during clustering, but also reduces the accuracy of clustering results. The aim of this study was to propose featurereduction approaches to reduce the redundancy and to develop semisimulated data with defined ground truth to evaluate these approaches. We proposed a featurereduction approach based on the Affinity Propagation Algorithm （APA） and compared it with the classic feature reduction approach based on Principal Component Analysis （PCA）. We tested the two approaches to the parcellation of both semisimulated and real seed regions using the Kmeans algorithm and designed two experiments to evaluate their noise resistance. We found that all functional connectivitymaps （with/without feature reduction） provided correct information for the parcellation of the semi simulated seed region and the computational efficiency was greatly improved by both feature reduction approaches. Meanwhile, the APAbased featurereduction approach outperformed the PCA based approach in noiseresistance. The results suggested that functional connectivity maps can provide correct information for cortical parcellation, and featurereduction does not significantly change the information. Considering the improvement in computational efficiency and the noiseresistance, featurereduction of functional connectivity maps before cortical parcellation is both feasible and necessary.
文摘Heavy rains occur in China frequently, which often bring us floods and serious disasters in the summer half-year. The meso-scale heavy rain parcels (MHRP) in the mid-latitude are usually developed in following cases:I.By the approaching, meeting and / or overlapping of different weather systems, when two or more different rainfall systems are getting to conjugate, some MHRPs could be developed, such as: 1) a new cold/warm front or squall line approaches an old front or squall, even when the old one is somewhat decrepit; 2) at the places where two or more synoptic systems with different characteristics are meeting together, such as the meeting of tropical cyclone with the cold airs coming from the mid- and / or high-latitudes, or the low latitude vortex meeting with the westerly trough; 3) at the intersections of some different weather systems, such as the intersection of drylines, squall lines or fronts moving from different directions; and 4) by the overlapping of rainfall parcels produced continuously from a meso-generation centre.II.Resonance Effect and Tibetan Plateau Influence are two reasons why high frequency of heavy and torrential rains arround the meiyu front is discussed also.
基金supported by the Guizhou Provincial Science and Technology Foundation(Qiankehe ZK[2022]-302)the National Natural Science Foundation of China,(Grant NO.41661088,41631179 and 42071316)+2 种基金the National Key Research and Development Program of China(Grant NO.2017YFB0503600)the Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China,Ministry of Natural Resources(No.2022NRM0004)Excellent Youth Project of Hunan Provincial Education Department(22B0725)。
文摘Mapping abandoned land is very important for accurate agricultural management.However,in karst mountainous areas,continuous high-resolution optical images are difficult to obtain in rainy weather,and the land is fragmented,which poses a great challenge for remote sensing monitoring of agriculture activities.In this study,a new method for identifying abandoned land is proposed:firstly,a few Google Earth images are used to transform arable land into accurate vectorized geo-parcels;secondly,a time-series data set was constructed using Sentinel-1A Alpha parameters for 2020 on each farmland geoparcel;thirdly,the semi-variation function(SVF)was used to analyze the spatial-temporal characteristics,then identify abandoned land.The results show:(1)On the basis of accurate spatial information and boundary of farmland land,the SAR time-series dataset reflects the structure and time-series response.abandoned land with an accuracy of 80.25%.The problem of remote sensing monitoring in rainy regions and complex surface areas is well-resolved.(2)The spatial heterogeneity of abandoned land is more obvious than that of cultivated land within geoparcels.The step size for significant changes in the SVF of abandoned land is shorter than that of cultivated land.(3)The SVF time sequence curve presented a strong peak feature when farmland was abandoned.This reveals that the internal spatial structure of abandoned land is more disordered and complex.It showed that time-series variations of spatial structure within cultivated land have broader applications in remote sensing monitoring of agriculture in complex imaging environments.
文摘This paper presents a systematic view of most up-to-date tools, technologies and techniques which is appropriate not only for effective decision making, but also helpful for competent administration to provide efficient resolution for spatial troubles of Khasra and Parcel management. Different Data collection techniques have been applied on different data sources. Worldview II of 0.5 resolution image, scanned Master Plan and Cadastral/Khasra Maps was used for development of geodatabase for spatial and non-spatial entities using ArcGIS 10.2. Multiple processing on Satellite Imagery using ERDAS Imagine was performed like Image enhancement, Mosaicking and Color Balancing, Image Geo-referencing and Raster Cataloging. Development of Customize Graphical User Interface (GUI) for DHA’s officials and administrator makes efficient decision in society matters. This is the first spatial GUI, for DHA to plan and maintain society’s activities efficiently, in the form of ArcMap Add-Ins. These Add-Ins are written in C#.Net using ArcObjects APIs within MSVS 2012.
基金Supported by Public Welfare Project of Ningbo City(2019C10087)。
文摘In recent years,with the rapid development of cross-border e-commerce,international postal parcels have been increasing sharply,thus giving rise to a new way for alien biological invasion.According to the"animal and plant quarantine information platform"of the General Adminis-tration of Customs,postal inspection system intercepted a total of 4975 harmful organisms nationwide.There were 219 quarantine organisms,including 142 insects,27 weeds,12 nematodes,29 fungi,1 bacterium and 8 viruses.Insects accounted for 64.84%of the quarantine organisms,among which Hypothenemus hampei had the highest interception frequency.Up to 71.36%of those harmful organisms were from seedlings,yet47.31%organisms came from products exported from India.These analyses indicate the direction of future portal quarantine work and lay a theoret-ical foundation for better guarding the biological security.
文摘Nowadays, many different kinds of delivery companies transport their own kinds of parcels and offer their own services, which have caused a lot waste of resources. In addition, the volume of parcels in all cities that need to be delivered has been grown dramatically. To cope with these problems, a uniform parcel delivery system in a smart city which can offer service to all kinds of customers in the city including manufactures, department stores, restaurants, individual people and so forth was designed. This system uses IoT (Internet of Things) and RFID technology, combining computer network technology, wireless communication and cloud computing. With this system, the whole package delivery process including classification of packages, vehicle scheduling, path planning, transportation monitoring can be intellectualized as well as managed automatically, and the use of both material resources and manpower resources can be reduced accordingly.
文摘Objective.Objective of this work is the development and evaluation of a cortical parcellation framework based on tractography-derived brain structural connectivity.Impact Statement.The proposed framework utilizes novel spatial-graph representation learning methods for solving the task of cortical parcellation,an important medical image analysis and neuroscientific problem.Introduction.The concept of“connectional fingerprint”has motivated many investigations on the connectivity-based cortical parcellation,especially with the technical advancement of diffusion imaging.Previous studies on multiple brain regions have been conducted with promising results.However,performance and applicability of these models are limited by the relatively simple computational scheme and the lack of effective representation of brain imaging data.Methods.We propose the Spatial-graph Convolution Parcellation(SGCP)framework,a two-stage deep learning-based modeling for the graph representation brain imaging.In the first stage,SGCP learns an effective embedding of the input data through a self-supervised contrastive learning scheme with the backbone encoder of a spatial-graph convolution network.In the second stage,SGCP learns a supervised classifier to perform voxel-wise classification for parcellating the desired brain region.Results.SGCP is evaluated on the parcellation task for 5 brain regions in a 15-subject DWI dataset.Performance comparisons between SGCP,traditional parcellation methods,and other deep learning-based methods show that SGCP can achieve superior performance in all the cases.Conclusion.Consistent good performance of the proposed SGCP framework indicates its potential to be used as a general solution for investigating the regional/subregional composition of human brain based on one or more connectivity measurements.
基金National key research and development projects(2018YFC0809200).
文摘The quantity of the imported parcels in China has increased rapidly,becoming an important means for criminals to hide the prohibited animal and plant quarantine objects.The x-ray applied to the port of post inspection can speed up inspection and better protect the ecological safety of China by mastering its method of judging animal and plant quarantine objects.
基金funded by National Institutes of Health(Grant Nos.MH117943,MH109773,MH116225,and MH123202)Additionally,the work leverages approaches developed through an National Institutes of Health(Grant No.1U01MH110274)the efforts of the Baby Connectome Project Consortium at UNC/UMIN.
文摘Objective Accurate infant brain parcellation is crucial for understanding early brain development;however,it is challenging due to the inherent low tissue contrast,high noise,and severe partial volume effects in infant magnetic resonance images(MRIs).The aim of this study was to develop an end-to-end pipeline that enabled accurate parcellation of infant brain MRIs.Methods We proposed an end-to-end pipeline that employs a two-stage global-to-local approach for accurate parcellation of infant brain MRIs.Specifically,in the global regions of interest(ROIs)localization stage,a combination of transformer and convolution operations was employed to capture both global spatial features and fine texture features,enabling an approximate localization of the ROIs across the whole brain.In the local ROIs refinement stage,leveraging the position priors from the first stage along with the raw MRIs,the boundaries of the ROIs are refined for a more accurate parcellation.Results We utilized the Dice ratio to evaluate the accuracy of parcellation results.Results on 263 subjects from National Database for Autism Research(NDAR),Baby Connectome Project(BCP)and Cross-site datasets demonstrated the better accuracy and robustness of our method than other competing methods.Conclusion Our end-to-end pipeline may be capable of accurately parcellating 6-month-old infant brain MRIs.
基金support from C2SMART University Transportation Center(USDOT#69A3551747124).
文摘The e-commerce industry has experienced significant growth in the past decade,particu-larly post-COVID.To accommodate such growth,the parcel delivery sector has also grown rapidly.However,there is a lack of study that properly evaluates its social and environ-mental impacts at a large scale.A model is proposed to analyze such impacts.A parcel gen-eration process is presented to convert public data into parcel volumes and stops.A continuous approximation model is fitted to estimate the length of parcel service tours.A case study is conducted using New York City(NYC)data.The parcel generation is shown to be a valid fit.The continuous approximation model parameters have R2 values of 98%or higher.The model output is validated against UPS truck trips.Application of the model to 2021 suggests residential parcel deliveries contributed to 0.05%of total daily vehicle-kilometer-traveled(VKT)in NYC corresponding to 14.4 metric tons of carbon equivalent(MTCE)emissions per day.COVID-19 contributed to an increase in parcel deliveries that led to up to 1064.3 MTCE of annual greenhouse gas(GHG)emissions in NYC(which could power 532 standard US households for a year).The existing bike lane infrastructure can support the substitution of 17%of parcel deliveries by cargo bikes,which would reduce VKT by 11%.Adding 3 km of bike lanes to connect Amazon facilities can expand their cargo bike substitution benefit from a VKT reduction of 5%up to 30%.If 28 km of additional bike lanes are made,parcel delivery substitution citywide could increase from 17%to 34%via cargo bike and save an additional 2.3 MTCE per day.Cargo bike priorities can be set to reduce GHG emissions for lower-income neighborhoods including Harlem,Sunset Park,and Bushwick.
文摘精细的田块数据是现代农业的重要基础资料,该研究针对从高分辨率遥感影像中提取田块精细数据的需求,建立了一种先验知识融合语义特征的冬小麦田块精细提取方法(prior knowledge and semantic features integration-based farmland parcel extraction methodology,PKFFPE),PKFFPE以遥感图像和相应的边缘图像作为输入,采用编码器-解码器结构进行特征提取,利用多尺度注意力模块捕获不同尺度的关键特征,使用SoftMax对图像进行初步分割;通过深入分析同一田块内颜色、纹理等特征的分布规律获取先验知识,利用先验知识建立后处理方法,对初分割结果进行优化,生成田块精细数据。选择河北省邯郸市馆陶县和山东省泰安市宁阳县作为试验区,用于验证PKFFPE方法在平原地区和丘陵地区的适用性;选择UNet、ErfNet、SegNet、EIGNet,以及面向对象分类的方法作为初分割的对比方法,选择条件随机场和形态学处理作为的后处理的对比方法开展对比试验。试验结果表明,PKFFPE方法在馆陶县、宁阳县结果的准确率(96.1%、93.2%)、精确率(90.6%、87.6%)、召回率(93.2%、90.6%)、和F1分数(91.9%,89.0%)均优于对比方法,证明了PKFFPE方法在从高分辨遥感影像中提取田块精细数据方面具有突出的优势,能够应用于科研和生产实践。
