The human mind’s evolution owes much to its companion phenomena of intelligence, sapience, wisdom, awareness and consciousness. In this paper we take the concepts of intelligence and sa-pience as the starting point o...The human mind’s evolution owes much to its companion phenomena of intelligence, sapience, wisdom, awareness and consciousness. In this paper we take the concepts of intelligence and sa-pience as the starting point of a route towards elucidation of the conscious mind. There is much disagreement and confusion associated with the word intelligence. A lot of this results from its use in diverse contexts, where it is called upon to represent different ideas and to justify different ar-guments. Addition of the word sapience to the mix merely complicates matters, unless we can relate both of these words to different concepts in a way which acceptably crosses contextual boundaries. We have established a connection between information processing and processor “architecture” which provides just such a linguistic separation, and which is applicable in either a computational or conceptual form to any context. This paper reports the argumentation leading up to a distinction between intelligence and sapience, and relates this distinction to human “cognitive” activities. Information is always contextual. Information processing in a system always takes place between “architectural” scales: intelligence is the “tool” which permits an “overview” of the relevance of individual items of information. System unity presumes a degree of coherence across all the scales of a system: sapience is the “tool” which permits an evaluation of the relevance of both individual items and individual scales of information to a common purpose. This hyperscalar coherence is created through mutual inter-scalar observation, whose recursive nature generates the independence of high-level consciousness, making humans human. We conclude that intelligence and sapience are distinct and necessary properties of all information processing systems, and that the degree of their availability controls a system’s or a human’s cognitive capacity, if not its appli-cation. This establishes intelligence and sapience as prime ancestors of the conscious mind. How-ever, to our knowledge, there is no current mathematical approach which can satisfactorily deal with the native irrationalities of information integration across multiple scales, and therefore of formally modeling the mind.展开更多
Oil-filled transformers are critical assets in electrical power systems,both economically and operationally.Their condition is assessed through insulation system,which is greatly affected by various degradation mechan...Oil-filled transformers are critical assets in electrical power systems,both economically and operationally.Their condition is assessed through insulation system,which is greatly affected by various degradation mechanisms.Hence,effective fault diagnosis is essential to prolong their lifespan.Early detection and correction of incipient faults through Dissolved Gas Analysis(DGA)are crucial to prevent irreversible damage.Current measurement systems have significant limitations that impede their use in routine monitoring and underscore the need for new,accessible technologies that are both technically and economically viable to efficiently detect incipient faults.This study evaluates the performance of various Machine Learning(ML)techniques to predict the concentrations of hydrogen(H₂),methane(CH₄),acetylene(C₂H₂),ethylene(C₂H₄),and ethane(C₂H₆)in oil samples subjected to different types of electrical faults,using data from a novel electronic nose(E-Nose)equipped with eleven MOS-type gas sensors.The evaluated ML techniques include Linear Regression(LR),Multivariate Linear Regression(MLR),Principal Component Regression(PCR),Multilayer Perceptron(MLP),Partial Least Squares Regression(PLS),Support Vector Regression(SVR),and Random Forest Regression(RFR).Experimental results from 218 measurement processes revealed that RFR and MLP models exhibited superior performance,with RFR achieving the highest accuracy for predicting H₂,C₂H₂,and C₂H₆,while MLP excelled for CH₄and C₂H₄.A comparison with a commercial DGA system using the Duval Pentagon Method confirmed the effectiveness of these models in diagnosing transformer faults.These findings underscore the potential of combining E-Noses with ML techniques as an innovative and efficient solution for early fault diagnosis.展开更多
Holographic displays have the promise to be the ultimate 3D display technology,able to account for all visual cues.Recent advances in photonics and electronics gave rise to high-resolution holographic display prototyp...Holographic displays have the promise to be the ultimate 3D display technology,able to account for all visual cues.Recent advances in photonics and electronics gave rise to high-resolution holographic display prototypes,indicating that they may become widely available in the near future.One major challenge in driving those display systems is computational:computer generated holography(CGH)consists of numerically simulating diffraction,which is very computationally intensive.Our goal in this paper is to give a broad overview of the state-of-the-art in CGH.We make a classification of modern CGH algorithms,we describe different algorithmic CGH acceleration techniques,discuss the latest dedicated hardware solutions and indicate how to evaluate the perceptual quality of CGH.We summarize our findings,discuss remaining challenges and make projections on the future of CGH.展开更多
Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users c...Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.展开更多
Numerical Fresnel diffraction is broadly used in optics and holography in particular.So far,it has been implemented using convolutional approaches,spatial convolutions,or the fast Fourier transform.We propose a new wa...Numerical Fresnel diffraction is broadly used in optics and holography in particular.So far,it has been implemented using convolutional approaches,spatial convolutions,or the fast Fourier transform.We propose a new way,to our knowledge,of computing Fresnel diffraction using Gabor frames and chirplets.Contrary to previous techniques,the algorithm has linear-time complexity,does not exhibit aliasing,does not need zero padding,has no constraints on changing shift/resolution/pixel pitch between source and destination planes,and works at any propagation distance.We provide theoretical and numerical analyses,detail the algorithm,and report simulation results with an accelerated GPU implementation.This algorithm may serve as a basis for more flexible,faster,and memory-efficient computer-generated holography methods.展开更多
In this paper,we present an interactive static image composition approach,namely color retargeting,to flexibly represent time-varying color editing effect based on time-lapse video sequences.Instead of performing prec...In this paper,we present an interactive static image composition approach,namely color retargeting,to flexibly represent time-varying color editing effect based on time-lapse video sequences.Instead of performing precise image matting or blending techniques,our approach treats the color composition as a pixel-level resampling problem. In order to both satisfy the user's editing requirements and avoid visual artifacts,we construct a globally optimized interpolation field. This field defines from which input video frames the output pixels should be resampled.Our proposed resampling solution ensures that(i) the global color transition in the output image is as smooth as possible,(ii) the desired colors/objects specified by the user from different video frames are well preserved,and(iii) additional local color transition directions in the image space assigned by the user are also satisfied.Various examples have been shown to demonstrate that our efficient solution enables the user to easily create time-varying color image composition results.展开更多
AutoDock Vina(Vina)is a widely adopted molecular docking tool,often regarded as a standard or used as a baseline in numerous studies.However,its computational process is highly time-consuming.The pioneering field-prog...AutoDock Vina(Vina)is a widely adopted molecular docking tool,often regarded as a standard or used as a baseline in numerous studies.However,its computational process is highly time-consuming.The pioneering field-programmable gate array(FPGA)-based accelerator of Vina,known as Vina-FPGA,offers a high energy-efficiency approach to speed up the docking process.However,the computation modules in the Vina-FPGA design are not efficiently used.This is due to Vina exhibiting irregular behaviors in the form of nested loops with changing upper bounds and differing control flows.Fortunately,Vina employs the Monte Carlo iterative search method,which requires independent computations for different random initial inputs.This characteristic provides an opportunity to implement further parallel computation designs.To this end,this paper proposes Vina-FPGA2,an inter-module pipeline design for further accelerating Vina-FPGA.First,we use individual computational task(Task)independence by sequentially filling Tasks into computation modules.Then,we implement an inter-module pipeline parallel design by the Tag Checker module and architectural modifications,named Vina-FPGA2-Baseline.Next,to achieve resource-efficient hardware implementation,we describe it as an optimization problem and develop a reinforcement learning-based solver.Targeting the Xilinx UltraScale XCKU060 platform,this solver yields a more efficient implementation,named Vina-FPGA2-Enhanced.Finally,experiments show that Vina-FPGA2-Enhanced achieves an average 12.6×performance improvement over the central processing unit(CPU)and a 3.3×improvement over Vina-FPGA.Compared to Vina-GPU,Vina-FPGA2 achieves a 7.2×enhancement in energy efficiency.展开更多
文摘The human mind’s evolution owes much to its companion phenomena of intelligence, sapience, wisdom, awareness and consciousness. In this paper we take the concepts of intelligence and sa-pience as the starting point of a route towards elucidation of the conscious mind. There is much disagreement and confusion associated with the word intelligence. A lot of this results from its use in diverse contexts, where it is called upon to represent different ideas and to justify different ar-guments. Addition of the word sapience to the mix merely complicates matters, unless we can relate both of these words to different concepts in a way which acceptably crosses contextual boundaries. We have established a connection between information processing and processor “architecture” which provides just such a linguistic separation, and which is applicable in either a computational or conceptual form to any context. This paper reports the argumentation leading up to a distinction between intelligence and sapience, and relates this distinction to human “cognitive” activities. Information is always contextual. Information processing in a system always takes place between “architectural” scales: intelligence is the “tool” which permits an “overview” of the relevance of individual items of information. System unity presumes a degree of coherence across all the scales of a system: sapience is the “tool” which permits an evaluation of the relevance of both individual items and individual scales of information to a common purpose. This hyperscalar coherence is created through mutual inter-scalar observation, whose recursive nature generates the independence of high-level consciousness, making humans human. We conclude that intelligence and sapience are distinct and necessary properties of all information processing systems, and that the degree of their availability controls a system’s or a human’s cognitive capacity, if not its appli-cation. This establishes intelligence and sapience as prime ancestors of the conscious mind. How-ever, to our knowledge, there is no current mathematical approach which can satisfactorily deal with the native irrationalities of information integration across multiple scales, and therefore of formally modeling the mind.
基金supported by Agencia Nacional de Investigación y Desarrollo (ANID), through Fondecyt Regular 1230135 and Fondef TA24I10002the Programa de Iniciación a la Investigación Científica (PIIC) from the Dirección de Postgrado y Programas, Universidad Técnica Federico Santa María, Chile+1 种基金the FIC-R IA 40036152-0 Project of the Regional Government of Biobíoand the invaluable contributions of Elohim G. and the Genesis (1/1) Project.
文摘Oil-filled transformers are critical assets in electrical power systems,both economically and operationally.Their condition is assessed through insulation system,which is greatly affected by various degradation mechanisms.Hence,effective fault diagnosis is essential to prolong their lifespan.Early detection and correction of incipient faults through Dissolved Gas Analysis(DGA)are crucial to prevent irreversible damage.Current measurement systems have significant limitations that impede their use in routine monitoring and underscore the need for new,accessible technologies that are both technically and economically viable to efficiently detect incipient faults.This study evaluates the performance of various Machine Learning(ML)techniques to predict the concentrations of hydrogen(H₂),methane(CH₄),acetylene(C₂H₂),ethylene(C₂H₄),and ethane(C₂H₆)in oil samples subjected to different types of electrical faults,using data from a novel electronic nose(E-Nose)equipped with eleven MOS-type gas sensors.The evaluated ML techniques include Linear Regression(LR),Multivariate Linear Regression(MLR),Principal Component Regression(PCR),Multilayer Perceptron(MLP),Partial Least Squares Regression(PLS),Support Vector Regression(SVR),and Random Forest Regression(RFR).Experimental results from 218 measurement processes revealed that RFR and MLP models exhibited superior performance,with RFR achieving the highest accuracy for predicting H₂,C₂H₂,and C₂H₆,while MLP excelled for CH₄and C₂H₄.A comparison with a commercial DGA system using the Duval Pentagon Method confirmed the effectiveness of these models in diagnosing transformer faults.These findings underscore the potential of combining E-Noses with ML techniques as an innovative and efficient solution for early fault diagnosis.
基金This research was funded by the Research Foundation-Flanders(FWO),Junior postdoctoral fellowship(12ZQ220N),the joint JSPS-FWO scientific cooperation program(VS07820N)the Japan Society for the Promotion of Science(19H04132 and JPJSBP120202302)。
文摘Holographic displays have the promise to be the ultimate 3D display technology,able to account for all visual cues.Recent advances in photonics and electronics gave rise to high-resolution holographic display prototypes,indicating that they may become widely available in the near future.One major challenge in driving those display systems is computational:computer generated holography(CGH)consists of numerically simulating diffraction,which is very computationally intensive.Our goal in this paper is to give a broad overview of the state-of-the-art in CGH.We make a classification of modern CGH algorithms,we describe different algorithmic CGH acceleration techniques,discuss the latest dedicated hardware solutions and indicate how to evaluate the perceptual quality of CGH.We summarize our findings,discuss remaining challenges and make projections on the future of CGH.
基金partially supported by Innoviris(3-DLicornea project)FWO(project G.0256.15)+3 种基金supported by the National Natural Science Foundation of China(Nos.61272226 and 61373069)Research Grant of Beijing Higher Institution Engineering Research CenterTsinghua-Tencent Joint Laboratory for Internet Innovation TechnologyTsinghua University Initiative Scientific Research Program
文摘Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.
基金Fonds Wetenschappelijk Onderzoek(12ZQ223N,G089424N,G0A3O24N)Japan Society for the Promotion of Science(International research fellow P22752)。
文摘Numerical Fresnel diffraction is broadly used in optics and holography in particular.So far,it has been implemented using convolutional approaches,spatial convolutions,or the fast Fourier transform.We propose a new way,to our knowledge,of computing Fresnel diffraction using Gabor frames and chirplets.Contrary to previous techniques,the algorithm has linear-time complexity,does not exhibit aliasing,does not need zero padding,has no constraints on changing shift/resolution/pixel pitch between source and destination planes,and works at any propagation distance.We provide theoretical and numerical analyses,detail the algorithm,and report simulation results with an accelerated GPU implementation.This algorithm may serve as a basis for more flexible,faster,and memory-efficient computer-generated holography methods.
基金supported by the iMinds visualization research program(HIVIZ)
文摘In this paper,we present an interactive static image composition approach,namely color retargeting,to flexibly represent time-varying color editing effect based on time-lapse video sequences.Instead of performing precise image matting or blending techniques,our approach treats the color composition as a pixel-level resampling problem. In order to both satisfy the user's editing requirements and avoid visual artifacts,we construct a globally optimized interpolation field. This field defines from which input video frames the output pixels should be resampled.Our proposed resampling solution ensures that(i) the global color transition in the output image is as smooth as possible,(ii) the desired colors/objects specified by the user from different video frames are well preserved,and(iii) additional local color transition directions in the image space assigned by the user are also satisfied.Various examples have been shown to demonstrate that our efficient solution enables the user to easily create time-varying color image composition results.
基金Project supported by the National Natural Science Foundation of China(No.92464301)the Big Data Computing Center of Southeast University。
文摘AutoDock Vina(Vina)is a widely adopted molecular docking tool,often regarded as a standard or used as a baseline in numerous studies.However,its computational process is highly time-consuming.The pioneering field-programmable gate array(FPGA)-based accelerator of Vina,known as Vina-FPGA,offers a high energy-efficiency approach to speed up the docking process.However,the computation modules in the Vina-FPGA design are not efficiently used.This is due to Vina exhibiting irregular behaviors in the form of nested loops with changing upper bounds and differing control flows.Fortunately,Vina employs the Monte Carlo iterative search method,which requires independent computations for different random initial inputs.This characteristic provides an opportunity to implement further parallel computation designs.To this end,this paper proposes Vina-FPGA2,an inter-module pipeline design for further accelerating Vina-FPGA.First,we use individual computational task(Task)independence by sequentially filling Tasks into computation modules.Then,we implement an inter-module pipeline parallel design by the Tag Checker module and architectural modifications,named Vina-FPGA2-Baseline.Next,to achieve resource-efficient hardware implementation,we describe it as an optimization problem and develop a reinforcement learning-based solver.Targeting the Xilinx UltraScale XCKU060 platform,this solver yields a more efficient implementation,named Vina-FPGA2-Enhanced.Finally,experiments show that Vina-FPGA2-Enhanced achieves an average 12.6×performance improvement over the central processing unit(CPU)and a 3.3×improvement over Vina-FPGA.Compared to Vina-GPU,Vina-FPGA2 achieves a 7.2×enhancement in energy efficiency.
