A new method based on human-likeness assessment and optimization concept to solve the problem of human-like ma- nipulation planning for articulated robot is proposed in this paper. This method intrinsically formulates...A new method based on human-likeness assessment and optimization concept to solve the problem of human-like ma- nipulation planning for articulated robot is proposed in this paper. This method intrinsically formulates the problem as a con- strained optimization problem in robot configuration space. The robot configuration space is divided into different subregions by human likeness assessment. A widely used strategy, Rapid Upper Limb Assessment （RULA） in applied ergonomics, is adopted here to evaluate the human likeness of robot configuration. A task compatibility measurement of the robot velocity transmission ratio along a specified direction is used as the target function for the optimization problem. Simple illustrative examples of this method applied to a two Degree of Freedom （DOF） planar robot that resembles the upper limb of a human are presented. Further applications to a humanoid industrial robot SDA10D are also presented. The reasonable planning results for these applications assert the effectiveness of our method.展开更多
The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compound...The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein.The use of virtual screening in pharmaceutical research is growing in popularity.During the early phases of medication research and development,it is crucial.Chemical compound searches are nowmore narrowly targeted.Because the databases containmore andmore ligands,thismethod needs to be quick and exact.Neural network fingerprints were created more effectively than the well-known Extended Connectivity Fingerprint(ECFP).Only the largest sub-graph is taken into consideration to learn the representation,despite the fact that the conventional graph network generates a better-encoded fingerprint.When using the average or maximum pooling layer,it also contains unrelated data.This article suggested the Graph Convolutional Attention Network(GCAN),a graph neural network with an attention mechanism,to address these problems.Additionally,it makes the nodes or sub-graphs that are used to create the molecular fingerprint more significant.The generated fingerprint is used to classify drugs using ensemble learning.As base classifiers,ensemble stacking is applied to Support Vector Machines(SVM),Random Forest,Nave Bayes,Decision Trees,AdaBoost,and Gradient Boosting.When compared to existing models,the proposed GCAN fingerprint with an ensemble model achieves relatively high accuracy,sensitivity,specificity,and area under the curve.Additionally,it is revealed that our ensemble learning with generated molecular fingerprint yields 91%accuracy,outperforming earlier approaches.展开更多
This study endeavour assesses agromorphological likeness between initial introductions and regenerated accessions at the International Coconut Genebank for Africa and the Indian Ocean (ICG-AIO) based in C?te d’Ivoire...This study endeavour assesses agromorphological likeness between initial introductions and regenerated accessions at the International Coconut Genebank for Africa and the Indian Ocean (ICG-AIO) based in C?te d’Ivoire. Ten couples of parental (G0) and regenerated (G1) accessions of Tall coconut palms were analyzed using Principal Component Analysis (PCA) and Multiple Analysis of Variance (MANOVA) from 26 agromorphological characters. The main results showed a relative decrease in the expression of the phenotypical traits concerning the component of the fruit, height and vigor of the stem and yield of bunches and fruits after one regeneration cycle. But, a high proportion (69%) of studied characters from leaf, inflorescence and nut components showed likeness between G0 and G1 accessions. After one regeneration cycle, the controlled pollination method guarantees significant conservation of the expression of the majority of agromorphological traits. Consequently, regenerated accessions of Tall coconut palms can be used to pursue research and development programs in C?te d’Ivoire.展开更多
The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and t...The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and the “interpunctions channel”. The theory can “measure” how the author shapes a character speaking to different audiences, by modulating deep-language parameters. To show its power, we have applied the theory to the literary corpus of Maria Valtorta, an Italian mystic of the XX-century. The likeness index , ranging from 0 to 1, allows to “measure” how two linguistic channels are similar, therefore implying that a character speaks to different audiences in the same way. A 6-dB difference between the signal-to-noise ratios of two channels already gives I<sub>L</sub> ≈ 0.5, a threshold below which the two channels depend very little on each other, therefore implying that the character addresses different audiences differently. In conclusion, multiple linguistic channels can describe the “fine tuning” that a literary author uses to diversify characters or distinguish the behavior of the same character in different situations. The theory can be applied to literary corpora written in any alphabetical language.展开更多
基金The National Natural Science Foundation of China，National High Technology Research and Development Program of China，The Research Innovation Program for College Graduates of Jiangsu Province，The Excellent Doctoral Dissertation Foundation of Southeast University
文摘A new method based on human-likeness assessment and optimization concept to solve the problem of human-like ma- nipulation planning for articulated robot is proposed in this paper. This method intrinsically formulates the problem as a con- strained optimization problem in robot configuration space. The robot configuration space is divided into different subregions by human likeness assessment. A widely used strategy, Rapid Upper Limb Assessment （RULA） in applied ergonomics, is adopted here to evaluate the human likeness of robot configuration. A task compatibility measurement of the robot velocity transmission ratio along a specified direction is used as the target function for the optimization problem. Simple illustrative examples of this method applied to a two Degree of Freedom （DOF） planar robot that resembles the upper limb of a human are presented. Further applications to a humanoid industrial robot SDA10D are also presented. The reasonable planning results for these applications assert the effectiveness of our method.
文摘The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein.The use of virtual screening in pharmaceutical research is growing in popularity.During the early phases of medication research and development,it is crucial.Chemical compound searches are nowmore narrowly targeted.Because the databases containmore andmore ligands,thismethod needs to be quick and exact.Neural network fingerprints were created more effectively than the well-known Extended Connectivity Fingerprint(ECFP).Only the largest sub-graph is taken into consideration to learn the representation,despite the fact that the conventional graph network generates a better-encoded fingerprint.When using the average or maximum pooling layer,it also contains unrelated data.This article suggested the Graph Convolutional Attention Network(GCAN),a graph neural network with an attention mechanism,to address these problems.Additionally,it makes the nodes or sub-graphs that are used to create the molecular fingerprint more significant.The generated fingerprint is used to classify drugs using ensemble learning.As base classifiers,ensemble stacking is applied to Support Vector Machines(SVM),Random Forest,Nave Bayes,Decision Trees,AdaBoost,and Gradient Boosting.When compared to existing models,the proposed GCAN fingerprint with an ensemble model achieves relatively high accuracy,sensitivity,specificity,and area under the curve.Additionally,it is revealed that our ensemble learning with generated molecular fingerprint yields 91%accuracy,outperforming earlier approaches.
文摘This study endeavour assesses agromorphological likeness between initial introductions and regenerated accessions at the International Coconut Genebank for Africa and the Indian Ocean (ICG-AIO) based in C?te d’Ivoire. Ten couples of parental (G0) and regenerated (G1) accessions of Tall coconut palms were analyzed using Principal Component Analysis (PCA) and Multiple Analysis of Variance (MANOVA) from 26 agromorphological characters. The main results showed a relative decrease in the expression of the phenotypical traits concerning the component of the fruit, height and vigor of the stem and yield of bunches and fruits after one regeneration cycle. But, a high proportion (69%) of studied characters from leaf, inflorescence and nut components showed likeness between G0 and G1 accessions. After one regeneration cycle, the controlled pollination method guarantees significant conservation of the expression of the majority of agromorphological traits. Consequently, regenerated accessions of Tall coconut palms can be used to pursue research and development programs in C?te d’Ivoire.
文摘The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and the “interpunctions channel”. The theory can “measure” how the author shapes a character speaking to different audiences, by modulating deep-language parameters. To show its power, we have applied the theory to the literary corpus of Maria Valtorta, an Italian mystic of the XX-century. The likeness index , ranging from 0 to 1, allows to “measure” how two linguistic channels are similar, therefore implying that a character speaks to different audiences in the same way. A 6-dB difference between the signal-to-noise ratios of two channels already gives I<sub>L</sub> ≈ 0.5, a threshold below which the two channels depend very little on each other, therefore implying that the character addresses different audiences differently. In conclusion, multiple linguistic channels can describe the “fine tuning” that a literary author uses to diversify characters or distinguish the behavior of the same character in different situations. The theory can be applied to literary corpora written in any alphabetical language.
