With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused o...With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
目前大多数软件开发都采用面向对象技术,而数据仍然保存在关系数据库中。由于对象模型和关系模型存在阻抗不匹配,因此实现对象与关系的映射已成为软件开发领域的关键问题。采用O/R M app ing(对象/关系映射)技术、XM L技术和软件分层的...目前大多数软件开发都采用面向对象技术,而数据仍然保存在关系数据库中。由于对象模型和关系模型存在阻抗不匹配,因此实现对象与关系的映射已成为软件开发领域的关键问题。采用O/R M app ing(对象/关系映射)技术、XM L技术和软件分层的设计思想,实现了一个有效的数据库访问中间件,解决了利用ADO.NET开发应用程序遇到的数据表示和存取问题。展开更多
In this paper,we developed a hybrid model for the steam turbines of a utility system,which combines an improved neural network model with the thermodynamic model.Then,a nonlinear programming(NLP) model of the steam tu...In this paper,we developed a hybrid model for the steam turbines of a utility system,which combines an improved neural network model with the thermodynamic model.Then,a nonlinear programming(NLP) model of the steam turbine network is formulated by utilizing the developed steam turbine models to minimize the total steam cost for the whole steam turbine network.Finally,this model is applied to optimize the steam turbine network of an ethylene plant.The obtained results demonstrate that this hybrid model can accurately estimate and evaluate the performance of steam turbines,and the significant cost savings can be made by optimizing the steam turbine network operation at no capital cost.展开更多
A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several sha...A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several shape retrieval technologies have been developed, little attention has been given to the points on human＇s sense and impression （as known as Kansei） in the conventional techniques, In this paper, the authors propose a novel method of shape retrieval based on shape impression of human＇s Kansei. The key to the method is the Gaussian curvature distribution from 3D models as features for shape retrieval. Then it classifies the 3D models by extracted feature and measures similarity among models in storage.展开更多
The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Alt...The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Although the basic concept of the Internet of Things sounds simple, its application is difficult and, so far, the respective existing architectural models are rather monolithic and are dominated by several limitations. The paper introduces a generic Internet of Things architecture trying to resolve the existing restrictions of current architectural models by integrating both RFID and smart object-based infrastructures, while also exploring a third parameter, i.e. the social potentialities of the Internet of Things building blocks towards shaping the “Social Internet of Things”. The proposed architecture is based on a layered lightweight and open middle-ware solution following the paradigm of Service Oriented Architecture and the Semantic Model Driven Ap-proach, which is realized at both design-time and deployment–time covering the whole service lifecycle for the corresponding services and applications provided.展开更多
This review investigates the recent developments of heterogeneous objects modeling in additive manufacturing(AM),as well as general problems and widespread solutions to the modeling methods of heterogeneous objects.Pr...This review investigates the recent developments of heterogeneous objects modeling in additive manufacturing(AM),as well as general problems and widespread solutions to the modeling methods of heterogeneous objects.Prevalent heterogeneous object representations are generally categorized based on the different expression or data structure employed therein,and the state-of-the-art of process planning procedures for AM is reviewed via different vigorous solutions for part orientation,slicing methods,and path planning strategies.Finally,some evident problems and possible future directions of investigation are discussed.展开更多
基金supported in part by theThe Planning Subject Project of Guangdong Power Grid Co.,Ltd.(62273104).
文摘With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
文摘目前大多数软件开发都采用面向对象技术,而数据仍然保存在关系数据库中。由于对象模型和关系模型存在阻抗不匹配,因此实现对象与关系的映射已成为软件开发领域的关键问题。采用O/R M app ing(对象/关系映射)技术、XM L技术和软件分层的设计思想,实现了一个有效的数据库访问中间件,解决了利用ADO.NET开发应用程序遇到的数据表示和存取问题。
基金Supported by the Major State Basic Research Development Program of China（2012CB720500）the National Natural Science Foundation of China（U1162202）,the National Natural Science Foundation of China（21276078,61174118,21206037）the National Science Fund for Outstanding Young Scholars（61222303）
文摘In this paper,we developed a hybrid model for the steam turbines of a utility system,which combines an improved neural network model with the thermodynamic model.Then,a nonlinear programming(NLP) model of the steam turbine network is formulated by utilizing the developed steam turbine models to minimize the total steam cost for the whole steam turbine network.Finally,this model is applied to optimize the steam turbine network of an ethylene plant.The obtained results demonstrate that this hybrid model can accurately estimate and evaluate the performance of steam turbines,and the significant cost savings can be made by optimizing the steam turbine network operation at no capital cost.
文摘A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several shape retrieval technologies have been developed, little attention has been given to the points on human＇s sense and impression （as known as Kansei） in the conventional techniques, In this paper, the authors propose a novel method of shape retrieval based on shape impression of human＇s Kansei. The key to the method is the Gaussian curvature distribution from 3D models as features for shape retrieval. Then it classifies the 3D models by extracted feature and measures similarity among models in storage.
文摘The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Although the basic concept of the Internet of Things sounds simple, its application is difficult and, so far, the respective existing architectural models are rather monolithic and are dominated by several limitations. The paper introduces a generic Internet of Things architecture trying to resolve the existing restrictions of current architectural models by integrating both RFID and smart object-based infrastructures, while also exploring a third parameter, i.e. the social potentialities of the Internet of Things building blocks towards shaping the “Social Internet of Things”. The proposed architecture is based on a layered lightweight and open middle-ware solution following the paradigm of Service Oriented Architecture and the Semantic Model Driven Ap-proach, which is realized at both design-time and deployment–time covering the whole service lifecycle for the corresponding services and applications provided.
基金supported by the National Nature Science Foundation of China,Nos.51575483 and U1609207.
文摘This review investigates the recent developments of heterogeneous objects modeling in additive manufacturing(AM),as well as general problems and widespread solutions to the modeling methods of heterogeneous objects.Prevalent heterogeneous object representations are generally categorized based on the different expression or data structure employed therein,and the state-of-the-art of process planning procedures for AM is reviewed via different vigorous solutions for part orientation,slicing methods,and path planning strategies.Finally,some evident problems and possible future directions of investigation are discussed.
