Conventional Internet of Things(IoT)ecosystems involve data streaming from sensors,through Fog devices to a centralized Cloud server.Issues that arise include privacy concerns due to third party management of Cloud se...Conventional Internet of Things(IoT)ecosystems involve data streaming from sensors,through Fog devices to a centralized Cloud server.Issues that arise include privacy concerns due to third party management of Cloud servers,single points of failure,a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point of security and maintenance perspective.Blockchain technologies avoid trusted third parties and safeguard against a single point of failure and other issues.This has inspired researchers to investigate blockchain’s adoption into IoT ecosystem.In this paper,recent state-of-the-arts advances in blockchain for IoT,blockchain for Cloud IoT and blockchain for Fog IoT in the context of eHealth,smart cities,intelligent transport and other applications are analyzed.Obstacles,research gaps and potential solutions are also presented.展开更多
Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest...Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.展开更多
A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural langu...A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine （SVM） theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.展开更多
Let { W(t);t≥0 } be a standard Brownian motion.For a positive integer m ,define a Gaussian processX m(t)=1m!∫ t 0(t-s) m d W(s).In this paper the liminf behavior of the increments of this process is discu...Let { W(t);t≥0 } be a standard Brownian motion.For a positive integer m ,define a Gaussian processX m(t)=1m!∫ t 0(t-s) m d W(s).In this paper the liminf behavior of the increments of this process is discussed by establishing some probability inequalities.Some previous results are extended and improved.展开更多
Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features...Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features of their body,robots are often programmed to execute point-to-point precise but fxed patterns.This study proposes a new approach to interpreting and reproducing articulated and complex trajectories as a set of known robot-based primitives.Instead of achieving accurate reproductions,the proposed approach aims at interpreting data in an agent-centred fashion,according to an agent s primitive movements.The method improves the accuracy of a reproduction with an incremental process that seeks frst a rough approximation by capturing the most essential features of a demonstrated trajectory.Observing the discrepancy between the demonstrated and reproduced trajectories,the process then proceeds with incremental decompositions and new searches in sub-optimal parts of the trajectory.The aim is to achieve an agent-centred interpretation and progressive learning that fts in the frst place the robots capability,as opposed to a data-centred decomposition analysis.Tests on both geometric and human generated trajectories reveal that the use of own primitives results in remarkable robustness and generalisation properties of the method.In particular,because trajectories are understood and abstracted by means of agent-optimised primitives,the method has two main features： 1） Reproduced trajectories are general and represent an abstraction of the data.2） The algorithm is capable of reconstructing highly noisy or corrupted data without pre-processing thanks to an implicit and emergent noise suppression and feature detection.This study suggests a novel bio-inspired approach to interpreting,learning and reproducing articulated movements and trajectories.Possible applications include drawing,writing,movement generation,object manipulation,and other tasks where the performance requires human-like interpretation and gen展开更多
A 3D-view is helpful to instantly grasp what is presented in a drawing. There exist a variety of ways to present the same part with 3D-views. To facilitate the choice of an optimum one among them, the work divides com...A 3D-view is helpful to instantly grasp what is presented in a drawing. There exist a variety of ways to present the same part with 3D-views. To facilitate the choice of an optimum one among them, the work divides composite solid models into three categories, so as to convey the originality of design concisely and accurately by using the least ＂ engineering language＂.展开更多
The probability calculus and statistics as well permeate nearly every discipline and professional sector, while no theories underpinning this wide spreading field reached universal consensus so far. The probability in...The probability calculus and statistics as well permeate nearly every discipline and professional sector, while no theories underpinning this wide spreading field reached universal consensus so far. The probability interpretations present irreconcilable traits, so the concept of probability is still substantially unclear. <strong>Purpose of this work: </strong>The present paper intends to demonstrate how the different models of probability constitute the facial problem which conceals another hidden and more fundamental question. <strong>Method:</strong> We show how authors do not agree with the concept of probability <em>P</em> and moreover they have different ideas about the precise object qualified by <em>P</em>, which has priority from the point of logic. It is clear how the element <em>X</em> measured by <em>P</em>(<em>X</em>) influences its meaning. In consequence of the conflicting opinions, theorists tend toward a compromise. They use the outcome or result of an experiment as the argument <em>X</em> of <em>P</em>(<em>X</em>) and represent <em>X</em> as a subset of the event space. This paper suggests replacing the outcome-subset with the event-triad <strong>E</strong>, which provides a comprehensive mathematical support. <strong>Results:</strong> The last section shows how the triadic model is formally consistent with the conventional theories and can integrate the conflicting views on probability. This unifying result can help mathematicians to go beyond the present theoretical deadlock. In summary, this paper advocates a more explicit notation system for probability and points out how probability can be ambiguous without rigorous specification of the sample space and the experiment in general.展开更多
We present a step-by-step approach for constructing a framework for knowledge process analysis （KPA）. We intend to apply this framework to the analysis of own research projects in an exploratory way and elaborate it...We present a step-by-step approach for constructing a framework for knowledge process analysis （KPA）. We intend to apply this framework to the analysis of own research projects in an exploratory way and elaborate it through the accumulation of case studies. This study is based on a methodology consisting of knowledge process modeling, primitives synthesis, and reflective verification. We describe details of the methodology and present the results of case studies： a novel methodology, a practical work guide, and a tool for KPA; insights for improving future research projects and education; and the integration of existing knowledge creation theories.展开更多
文摘Conventional Internet of Things(IoT)ecosystems involve data streaming from sensors,through Fog devices to a centralized Cloud server.Issues that arise include privacy concerns due to third party management of Cloud servers,single points of failure,a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point of security and maintenance perspective.Blockchain technologies avoid trusted third parties and safeguard against a single point of failure and other issues.This has inspired researchers to investigate blockchain’s adoption into IoT ecosystem.In this paper,recent state-of-the-arts advances in blockchain for IoT,blockchain for Cloud IoT and blockchain for Fog IoT in the context of eHealth,smart cities,intelligent transport and other applications are analyzed.Obstacles,research gaps and potential solutions are also presented.
基金supported by Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2021]General 442)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 179)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 096).
文摘Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.
基金This work was partially supported by the Royal Society of UK and the National Natural Science Foundation of PRC (No. 60175028).
文摘A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine （SVM） theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.
基金Project Supported by National Science Fundation of China(1 9571 0 2 1 ) and Zhejiang Province
文摘Let { W(t);t≥0 } be a standard Brownian motion.For a positive integer m ,define a Gaussian processX m(t)=1m!∫ t 0(t-s) m d W(s).In this paper the liminf behavior of the increments of this process is discussed by establishing some probability inequalities.Some previous results are extended and improved.
基金supported by European Community s Seventh Framework Programme FP7/2007-2013,Challenge 2,Cognitive Systems,Interaction,Robotics(No.248311AMARSi)
文摘Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features of their body,robots are often programmed to execute point-to-point precise but fxed patterns.This study proposes a new approach to interpreting and reproducing articulated and complex trajectories as a set of known robot-based primitives.Instead of achieving accurate reproductions,the proposed approach aims at interpreting data in an agent-centred fashion,according to an agent s primitive movements.The method improves the accuracy of a reproduction with an incremental process that seeks frst a rough approximation by capturing the most essential features of a demonstrated trajectory.Observing the discrepancy between the demonstrated and reproduced trajectories,the process then proceeds with incremental decompositions and new searches in sub-optimal parts of the trajectory.The aim is to achieve an agent-centred interpretation and progressive learning that fts in the frst place the robots capability,as opposed to a data-centred decomposition analysis.Tests on both geometric and human generated trajectories reveal that the use of own primitives results in remarkable robustness and generalisation properties of the method.In particular,because trajectories are understood and abstracted by means of agent-optimised primitives,the method has two main features： 1） Reproduced trajectories are general and represent an abstraction of the data.2） The algorithm is capable of reconstructing highly noisy or corrupted data without pre-processing thanks to an implicit and emergent noise suppression and feature detection.This study suggests a novel bio-inspired approach to interpreting,learning and reproducing articulated movements and trajectories.Possible applications include drawing,writing,movement generation,object manipulation,and other tasks where the performance requires human-like interpretation and gen
文摘A 3D-view is helpful to instantly grasp what is presented in a drawing. There exist a variety of ways to present the same part with 3D-views. To facilitate the choice of an optimum one among them, the work divides composite solid models into three categories, so as to convey the originality of design concisely and accurately by using the least ＂ engineering language＂.
文摘The probability calculus and statistics as well permeate nearly every discipline and professional sector, while no theories underpinning this wide spreading field reached universal consensus so far. The probability interpretations present irreconcilable traits, so the concept of probability is still substantially unclear. <strong>Purpose of this work: </strong>The present paper intends to demonstrate how the different models of probability constitute the facial problem which conceals another hidden and more fundamental question. <strong>Method:</strong> We show how authors do not agree with the concept of probability <em>P</em> and moreover they have different ideas about the precise object qualified by <em>P</em>, which has priority from the point of logic. It is clear how the element <em>X</em> measured by <em>P</em>(<em>X</em>) influences its meaning. In consequence of the conflicting opinions, theorists tend toward a compromise. They use the outcome or result of an experiment as the argument <em>X</em> of <em>P</em>(<em>X</em>) and represent <em>X</em> as a subset of the event space. This paper suggests replacing the outcome-subset with the event-triad <strong>E</strong>, which provides a comprehensive mathematical support. <strong>Results:</strong> The last section shows how the triadic model is formally consistent with the conventional theories and can integrate the conflicting views on probability. This unifying result can help mathematicians to go beyond the present theoretical deadlock. In summary, this paper advocates a more explicit notation system for probability and points out how probability can be ambiguous without rigorous specification of the sample space and the experiment in general.
文摘We present a step-by-step approach for constructing a framework for knowledge process analysis （KPA）. We intend to apply this framework to the analysis of own research projects in an exploratory way and elaborate it through the accumulation of case studies. This study is based on a methodology consisting of knowledge process modeling, primitives synthesis, and reflective verification. We describe details of the methodology and present the results of case studies： a novel methodology, a practical work guide, and a tool for KPA; insights for improving future research projects and education; and the integration of existing knowledge creation theories.
