Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-sl...Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-slider mechanism was developed in Japan, and the joining time is less than 0.5 s, however the length of each bar are not reported and this mechanism is complex. A relatively simple 6-bar and 1-slider mechanism is put forward, which can realize the shearing and extrusion motion of the top and bottom blades with a speed approximately equal to the speed of the metal plates. In order to study the kinematics property of the double blades, based on complex vector method, the multi-rigid-body model is built, and the displacement and speed functions of the double blades, the joining time and joining thickness are deduced, the kinematics analysis shows that the initial parameters can＇t satisfy the joining process. Hence, optimization of this mechanism is employed using genetic algorithm（GA） and the optimization parameters of this mechanism are obtained, the kinematics analysis show that the joining time is less than 0.1 s, the joining thickness is more than 80% of the thickness of the solid-state metal, and the horizontal speeds of the blades are improved. A new mechanism is provided for the joining of the solid-state metal and a foundation is laid for the design of the device.展开更多
Dynamic programming(DP) is an effective query optimization approach to select an appropriate join order for relational database management system(RDBMS) in multi-table joins. This method was extended and made availabl...Dynamic programming(DP) is an effective query optimization approach to select an appropriate join order for relational database management system(RDBMS) in multi-table joins. This method was extended and made available in distributed DBMS(D-DBMS). The structure of this optimal solution was firstly characterized according to the distributing status of tables and data, and then the recurrence relations between a problem and its sub-problems were recursively defined. DP in D-DBMS has the same time-complexity with that in centralized DBMS, while it has the capability to solve a much more sophisticated optimal problem of multi-table join in D-DBMS. The effectiveness of this optimal strategy has been proved by experiments.展开更多
Optimization techniques are being applied to solve the problems of surface interpolation, approximation, smooth joining and fairing, aiming at corresponding objective functions. This paper focuses on the construction ...Optimization techniques are being applied to solve the problems of surface interpolation, approximation, smooth joining and fairing, aiming at corresponding objective functions. This paper focuses on the construction of fair surface interpolating the given mesh of curved boundaries with G 2 adjustment at comers and G 1, G 2 smoothness between adjacent patches. Many papers on surface blending have been presented, but almost all of them are restricted to the discussion of Bezier patches, there are no good results for B-spline surface. This paper gives a solution to the B-spline surface, allowing the surface to degenerate at comer in and have different parameterization along the common boundary of two patches.展开更多
Artificial intelligence-enabled database technology,known as AI4DB(Artificial Intelligence for Databases),is an active research area attracting significant attention and innovation.This survey first introduces the bac...Artificial intelligence-enabled database technology,known as AI4DB(Artificial Intelligence for Databases),is an active research area attracting significant attention and innovation.This survey first introduces the background of learning-based database techniques.It then reviews advanced query optimization methods for learning databases,focusing on four popular directions:cardinality/cost estimation,learningbased join order selection,learning-based end-to-end optimizers,and text-to-SQL models.Cardinality/cost estimation is classified into supervised and unsupervised methods based on learning models,with illustrative examples provided to explain the working mechanisms.Detailed descriptions of various query optimizers are also given to elucidate the working mechanisms of each component in learning query optimizers.Additionally,we discuss the challenges and development opportunities of learning query optimizers.The survey further explores text-to-SQL models,a new research area within AI4DB.Finally,we consider the future development prospects of learning databases.展开更多
This paper proposes a semi-greedy framework for optimizing multi-joinqueries in shared-nothing systems. The plan generated by the framework com-prises several pipelines, each performing several joins. The framework de...This paper proposes a semi-greedy framework for optimizing multi-joinqueries in shared-nothing systems. The plan generated by the framework com-prises several pipelines, each performing several joins. The framework deter-mines the 'optimal' number of joins to be performed in each pipeline. Thedecisions are made based on the cost estimation of the entire processing plan.Two ekisting optimization algorithms are extended under the framework. Ananalytical model is presented and used to compare the quality of plans producedby each optimization algorithm. Our study shows that the new algorithms out-perform their counterparts that are not extended.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51475139)
文摘Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-slider mechanism was developed in Japan, and the joining time is less than 0.5 s, however the length of each bar are not reported and this mechanism is complex. A relatively simple 6-bar and 1-slider mechanism is put forward, which can realize the shearing and extrusion motion of the top and bottom blades with a speed approximately equal to the speed of the metal plates. In order to study the kinematics property of the double blades, based on complex vector method, the multi-rigid-body model is built, and the displacement and speed functions of the double blades, the joining time and joining thickness are deduced, the kinematics analysis shows that the initial parameters can＇t satisfy the joining process. Hence, optimization of this mechanism is employed using genetic algorithm（GA） and the optimization parameters of this mechanism are obtained, the kinematics analysis show that the joining time is less than 0.1 s, the joining thickness is more than 80% of the thickness of the solid-state metal, and the horizontal speeds of the blades are improved. A new mechanism is provided for the joining of the solid-state metal and a foundation is laid for the design of the device.
文摘Dynamic programming(DP) is an effective query optimization approach to select an appropriate join order for relational database management system(RDBMS) in multi-table joins. This method was extended and made available in distributed DBMS(D-DBMS). The structure of this optimal solution was firstly characterized according to the distributing status of tables and data, and then the recurrence relations between a problem and its sub-problems were recursively defined. DP in D-DBMS has the same time-complexity with that in centralized DBMS, while it has the capability to solve a much more sophisticated optimal problem of multi-table join in D-DBMS. The effectiveness of this optimal strategy has been proved by experiments.
文摘Optimization techniques are being applied to solve the problems of surface interpolation, approximation, smooth joining and fairing, aiming at corresponding objective functions. This paper focuses on the construction of fair surface interpolating the given mesh of curved boundaries with G 2 adjustment at comers and G 1, G 2 smoothness between adjacent patches. Many papers on surface blending have been presented, but almost all of them are restricted to the discussion of Bezier patches, there are no good results for B-spline surface. This paper gives a solution to the B-spline surface, allowing the surface to degenerate at comer in and have different parameterization along the common boundary of two patches.
基金partially supported by the National Natural Science Foundation of China(Grant No.62272066)Open Research Fund of Guangxi Key Lab of Human-machine Interaction and Intelligent Decision(GXHIID2207)+5 种基金Sichuan Science and Technology Program(2025ZNSFSC0044,2025YFHZ0194)Chengdu Technological Innovation Research and Development Project(2024-YF05-01217-SN)Chengdu Regional Science and Technology Innovation Cooperation Project(2025-YF11-00050-HZ)Open Foundation of Key Laboratory of Cyberspace Security,Ministry of Education of China and Henan Key Laboratory of Cyberspace Situation Awareness(KLCS20240106)Ant Group through CCFAnt Research Fund(CCF-AFSG RF20240106)Open Research Fund of Key Laboratory of Cyberspace Big Data Intelligent Security(Chongqing University of Posts and Telecommunications),Ministry of Education of China(CBDIS202404).
文摘Artificial intelligence-enabled database technology,known as AI4DB(Artificial Intelligence for Databases),is an active research area attracting significant attention and innovation.This survey first introduces the background of learning-based database techniques.It then reviews advanced query optimization methods for learning databases,focusing on four popular directions:cardinality/cost estimation,learningbased join order selection,learning-based end-to-end optimizers,and text-to-SQL models.Cardinality/cost estimation is classified into supervised and unsupervised methods based on learning models,with illustrative examples provided to explain the working mechanisms.Detailed descriptions of various query optimizers are also given to elucidate the working mechanisms of each component in learning query optimizers.Additionally,we discuss the challenges and development opportunities of learning query optimizers.The survey further explores text-to-SQL models,a new research area within AI4DB.Finally,we consider the future development prospects of learning databases.
文摘This paper proposes a semi-greedy framework for optimizing multi-joinqueries in shared-nothing systems. The plan generated by the framework com-prises several pipelines, each performing several joins. The framework deter-mines the 'optimal' number of joins to be performed in each pipeline. Thedecisions are made based on the cost estimation of the entire processing plan.Two ekisting optimization algorithms are extended under the framework. Ananalytical model is presented and used to compare the quality of plans producedby each optimization algorithm. Our study shows that the new algorithms out-perform their counterparts that are not extended.
