In order to improve the bit allocation efficiency of Directionlet coding,a modified Breiman,Friedman,Olshen and Stone(BFOS)algorithm is suggested for rate consistent truncation.Two modifications are:(1)Dominant direct...In order to improve the bit allocation efficiency of Directionlet coding,a modified Breiman,Friedman,Olshen and Stone(BFOS)algorithm is suggested for rate consistent truncation.Two modifications are:(1)Dominant direction adjustment is proposed to balance the cost of sparse description and segment artifacts caused by discontinuous adjacent direction pairs.(2)Priority related merging is also proposed in the BFOS distortion list to find an optimal trimming element for unequal-importance bit allocation.Experimental results show that block effects could be removed without obvious bpp increment by selecting the dominant direction and its adjustment according to neighborhood homogeneity,and combined multi-PRIority(PRI)based merging of the M-ordered list offers unequal importance allocation and leads to a Peak Signal-to-Noise Ratio(PSNR)gain of 0.4 dB~1.3 dB.展开更多
In this paper,we present a novel algorithm for odometry estimation based on ceiling vision.The main contribution of this algorithm is the introduction of principal direction detection that can greatly reduce error acc...In this paper,we present a novel algorithm for odometry estimation based on ceiling vision.The main contribution of this algorithm is the introduction of principal direction detection that can greatly reduce error accumulation problem in most visual odometry estimation approaches.The principal direction is defned based on the fact that our ceiling is flled with artifcial vertical and horizontal lines which can be used as reference for the current robot s heading direction.The proposed approach can be operated in real-time and it performs well even with camera s disturbance.A moving low-cost RGB-D camera（Kinect）,mounted on a robot,is used to continuously acquire point clouds.Iterative closest point（ICP） is the common way to estimate the current camera position by registering the currently captured point cloud to the previous one.However,its performance sufers from data association problem or it requires pre-alignment information.The performance of the proposed principal direction detection approach does not rely on data association knowledge.Using this method,two point clouds are properly pre-aligned.Hence,we can use ICP to fne-tune the transformation parameters and minimize registration error.Experimental results demonstrate the performance and stability of the proposed system under disturbance in real-time.Several indoor tests are carried out to show that the proposed visual odometry estimation method can help to signifcantly improve the accuracy of simultaneous localization and mapping（SLAM）.展开更多
This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize t...This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic concision, the VRML browser can offer better windows for man-computer interaction in real-time environment than ever before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and have a promising prospect in the fields of medical imaging.展开更多
Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis,characterization,and data-driven decisionmaking.We present a closed-l...Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis,characterization,and data-driven decisionmaking.We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles,enabling direct mapping from composition to nanoscale structure.Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs:(a)phase mapping,or identifying compositional regions with distinct structural behavior;and(b)material retrosynthesis,or optimizing compositions for target structure.Using functional data analysis,we develop a data-driven model with generative pre-training,active learning,and high-throughput experiments to predict spectral responses across composition space.We demonstrate the approach on seed-mediated growth of gold nanoparticles,showcasing its ability to extract design rules,reveal secondary interactions,and efficiently navigate morphology space.Gradient-based optimization of the models enables inverse design,making this a unified platform.展开更多
In this work we introduce the“Extensible Fish-tank Volume Model”that can reduce the complexity in the design and control of the Recirculating Aquaculture Systems.In the developed model we adjust the volume of a sing...In this work we introduce the“Extensible Fish-tank Volume Model”that can reduce the complexity in the design and control of the Recirculating Aquaculture Systems.In the developed model we adjust the volume of a single fish-tank to the prescribed values of stocking density,by controlling the necessary volume in each time step.Having developed an advantageous feeding,water exchange and oxygen supply strategy,as well as considering a compromise scheduling for the fingerling input and product fish output,we divide the volume vs.time function into equidistant parts and calculate the average volumes for these parts.Comparing these average values with the volumes of available tanks,we can plan the appropriate grades.The elaborated method is a good example for a case,where computational modeling is used to simulate a‘‘fictitious process model”that cannot be feasibly realized in the practice,but can simplify and accelerate the design and planning of real world processes by reducing the complexity.展开更多
基金Supported by The National Natural Science Foundation of China(No.60972133)Guangzhou Natural Science Foundation Team Project(No.9351064101000003&8451008901000615)
文摘In order to improve the bit allocation efficiency of Directionlet coding,a modified Breiman,Friedman,Olshen and Stone(BFOS)algorithm is suggested for rate consistent truncation.Two modifications are:(1)Dominant direction adjustment is proposed to balance the cost of sparse description and segment artifacts caused by discontinuous adjacent direction pairs.(2)Priority related merging is also proposed in the BFOS distortion list to find an optimal trimming element for unequal-importance bit allocation.Experimental results show that block effects could be removed without obvious bpp increment by selecting the dominant direction and its adjustment according to neighborhood homogeneity,and combined multi-PRIority(PRI)based merging of the M-ordered list offers unequal importance allocation and leads to a Peak Signal-to-Noise Ratio(PSNR)gain of 0.4 dB~1.3 dB.
文摘In this paper,we present a novel algorithm for odometry estimation based on ceiling vision.The main contribution of this algorithm is the introduction of principal direction detection that can greatly reduce error accumulation problem in most visual odometry estimation approaches.The principal direction is defned based on the fact that our ceiling is flled with artifcial vertical and horizontal lines which can be used as reference for the current robot s heading direction.The proposed approach can be operated in real-time and it performs well even with camera s disturbance.A moving low-cost RGB-D camera（Kinect）,mounted on a robot,is used to continuously acquire point clouds.Iterative closest point（ICP） is the common way to estimate the current camera position by registering the currently captured point cloud to the previous one.However,its performance sufers from data association problem or it requires pre-alignment information.The performance of the proposed principal direction detection approach does not rely on data association knowledge.Using this method,two point clouds are properly pre-aligned.Hence,we can use ICP to fne-tune the transformation parameters and minimize registration error.Experimental results demonstrate the performance and stability of the proposed system under disturbance in real-time.Several indoor tests are carried out to show that the proposed visual odometry estimation method can help to signifcantly improve the accuracy of simultaneous localization and mapping（SLAM）.
基金Postdoctoral Fund of China (No. 2003034518), Fund of Health Bureau of Zhejiang Province (No. 2004B042), China
文摘This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic concision, the VRML browser can offer better windows for man-computer interaction in real-time environment than ever before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and have a promising prospect in the fields of medical imaging.
基金funded primarily by the US Department of Energy (DOE), Office of Science, and Office of Basic Energy Sciences (BES) under award number DE-SC0019911Funding for H.T.C. was provided through the Energy Frontier Research Centers program: CSSAS—The Center for the Science of Synthesis Across Scales—under Award Number DE-SC0019288+2 种基金A.G. was supported by the University of Washington Molecular Engineering Materials Center (MEM-C, NSF grant DMR-2308979) as a part of the Academic Year Research Acceleration Research Experience for Undergraduates program. This work was also facilitated by the advanced computational, storage, and networking infrastructure provided by the Hyak supercomputer system and the Department of Chemical Engineering at the University of Washington. Part of this work was conducted at the Molecular Analysis Facility, a National Nanotechnology Coordinated Infrastructure (NNCI) site at the University of Washingtonsupported in part by funds from the National Science Foundation (awards NNCI-2025489, NNCI-1542101)the Molecular Engineering & Sciences Institute, and the Clean Energy Institute.
文摘Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis,characterization,and data-driven decisionmaking.We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles,enabling direct mapping from composition to nanoscale structure.Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs:(a)phase mapping,or identifying compositional regions with distinct structural behavior;and(b)material retrosynthesis,or optimizing compositions for target structure.Using functional data analysis,we develop a data-driven model with generative pre-training,active learning,and high-throughput experiments to predict spectral responses across composition space.We demonstrate the approach on seed-mediated growth of gold nanoparticles,showcasing its ability to extract design rules,reveal secondary interactions,and efficiently navigate morphology space.Gradient-based optimization of the models enables inverse design,making this a unified platform.
基金The research is supported by the Bilateral Chinese-Hungarian project in the frame of TE´T_12_CN-1-2012-0041 project.
文摘In this work we introduce the“Extensible Fish-tank Volume Model”that can reduce the complexity in the design and control of the Recirculating Aquaculture Systems.In the developed model we adjust the volume of a single fish-tank to the prescribed values of stocking density,by controlling the necessary volume in each time step.Having developed an advantageous feeding,water exchange and oxygen supply strategy,as well as considering a compromise scheduling for the fingerling input and product fish output,we divide the volume vs.time function into equidistant parts and calculate the average volumes for these parts.Comparing these average values with the volumes of available tanks,we can plan the appropriate grades.The elaborated method is a good example for a case,where computational modeling is used to simulate a‘‘fictitious process model”that cannot be feasibly realized in the practice,but can simplify and accelerate the design and planning of real world processes by reducing the complexity.
