Batteries play a critical role in electric vehicles and distributed energy generation.With the growing demand for energy storage solutions,new battery materials and systems are continually being developed.In this proc...Batteries play a critical role in electric vehicles and distributed energy generation.With the growing demand for energy storage solutions,new battery materials and systems are continually being developed.In this process,molecular dynamics(MD)simulations can reveal the microscopic mechanisms of battery processes,thereby boosting the design of batteries.Compared to other MD simulation techniques,the machine learning force field(MLFF)holds the advantages of first-principles accuracy along with large spatial and temporal scale,offering opportunities to uncover new mechanisms in battery systems.This review presents a detailed overview of the fundamental principles and model types of MLFFs,as well as their applications in simulating the structure,transport properties,and chemical reaction properties of bulk battery materials and interfaces.Notably,we emphasize the long-range interaction corrections and constant-potential methods in the model design of MLFFs.Finally,we discuss the challenges and prospects of applying MLFF models in the research of batteries.展开更多
We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraint...We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.展开更多
Today’s product creative design has rendered many fe atures and has brought a great change in our everyday life, there are many new c hallenges in its traditional theory and principle. According to the traditional de...Today’s product creative design has rendered many fe atures and has brought a great change in our everyday life, there are many new c hallenges in its traditional theory and principle. According to the traditional design theory, the FBS design model pays more attention to the function and stru cture of the product. But this model still couldn’t strengthen the relation bet ween product appearance design and human-machine design effectively. This paper adopt converse design thinking and presents an improved design thinking methodo logy based on C: FBS for product appearance design and give a general summarizat ion for the features, methods and technology based on human-machine interaction and interface. Meanwhile it also combines with the behavior design of product r elated IT fields and constructs a new outline to improve the design of product a ppearance supported by the technology of computer aided design. So the new metho d about design thinking for computer aided design, the new abstract product design model and the key problem of design thinking based on human-machine inte raction and interface are addressed in this paper. This kind of creative design theory that is driven by human-machine interaction and interface will help the development of CAD software system and the research of product design and manufa cture. Additionally, this paper gives some beneficial characters to address the theory based on human-machine interaction and interface. Meanwhile, combining with the developing of computer technology, the trends of design thinking based on t he technology of human-machine interaction and interface are also analyzed and discussed at the end of this paper.展开更多
OBJECTIVE:To enhance the understanding of identifying personalized pharmacotherapy options in Traditional Chinese Medicine(TCM),and further support the registration of new TCM drugs.METHODS:Generalized Boosted Models ...OBJECTIVE:To enhance the understanding of identifying personalized pharmacotherapy options in Traditional Chinese Medicine(TCM),and further support the registration of new TCM drugs.METHODS:Generalized Boosted Models and XGBoost were employed to construct a classification model to identify the bad prognosis factors in resistant hypertension(RH)patients.Furthermore,we used association analysis to explore the rules of"symptomsyndrome"and"symptom-herb"for the major influencing factors,in order to summarize prescription pattern and applicable patients of TCM.RESULTS:Patients with major adverse cardiac events mostly have complex symptoms of phlegm,stasis,deficiency and fire intermingled with each other,and finally summarized the human experience of using Chinese herbal medicine to precisely intervene in some symptoms of RH patients on the basis of conventional Western medical treatment.CONCLUSIONS:Machine learning algorithms can make full use of human use experience and evidence to save clinical trial resources and accelerate the development of TCM varieties.展开更多
Interface engineering is proved to be the most important strategy to push the device performance of the perovskite solar cell(PSC) to its limit, and numerous works have been conducted to screen efficient materials. He...Interface engineering is proved to be the most important strategy to push the device performance of the perovskite solar cell(PSC) to its limit, and numerous works have been conducted to screen efficient materials. Here, on the basis of the previous studies, we employ machine learning to map the relationship between the interface material and the device performance, leading to intelligently screening interface materials towards minimizing voltage losses in p-i-n type PSCs. To enhance the explainability of the machine learning models, molecular descriptors are used to represent the materials. Furthermore,experimental analysis with different characterization methods and device simulation based on the drift-diffusion physical model are conducted to get physical insights and validate the machine learning models. Accordingly, 3-thiophene ethylamine hydrochloride(Th EACl) is screened as an example, which enables remarkable improvements in VOCand PCE of the PSCs. Our work reveals the critical role of datadriven analysis in the high throughput screening of interface materials, which will significantly accelerate the exploration of new materials for high-efficiency PSCs.展开更多
The awareness detection in patients with disorders of consciousness currently relies on behavioral observations and CRS-R tests,however,the misdiagnosis rates have been relatively high.In this study,we applied brain-c...The awareness detection in patients with disorders of consciousness currently relies on behavioral observations and CRS-R tests,however,the misdiagnosis rates have been relatively high.In this study,we applied brain-computer interface(BCI)to awareness detection with a passive auditory stimulation paradigm.12 subjects with normal hearing were invited to collect electroencephalogram(EEG)based on a BCI communication system,in which EEG signals are transmitted wirelessly.After necessary preprocessing,RBF-SVM and EEGNet were used for algorithm realization and analysis.For a single subject,RBF-SVM can distinguish his(her)name stimuli awareness with classification accuracies ranging from 60-95%.EEGNet was used to learn all subjects'data and improved accuracy to 78.04%for characteristics finding and model generalization.Moreover,we completed the supplementary analysis work from the time domain and time-frequency domain.This study applied BCI communication to human awareness detection,proposed a passive auditory paradigm,and proved the effectiveness,which could be an inspiration for brain,mental or physical diseases diagnosis and detection.展开更多
GaP has been shown to be a promising photoelectrocatalyst for selective CO_(2)reduction to methanol.Due to the relevance of the interface structure to important processes such as electron/proton transfer,a detailed un...GaP has been shown to be a promising photoelectrocatalyst for selective CO_(2)reduction to methanol.Due to the relevance of the interface structure to important processes such as electron/proton transfer,a detailed understanding of the GaP(110)-water interfacial structure is of great importance.Ab initio molecular dynamics(AIMD)can be used for obtaining the microscopic information of the interfacial structure.However,the GaP(110)-water interface cannot converge to an equilibrated structure at the time scale of the AIMD simulation.In this work,we perform the machine learning accelerated molecular dynamics(MLMD)to overcome the difficulty of insufficient sampling by AIMD.With the help of MLMD,we unravel the microscopic information of the structure of the GaP(110)-water interface,and obtain a deeper understanding of the mechanisms of proton transfer at the GaP(110)-water interface,which will pave the way for gaining valuable insights into photoelectrocatalytic mechanisms and improving the performance of photoelectrochemical cells.展开更多
This paper describes the innovation schemes of the interface of a CNC machine which cannot communicate with a computer by a Direct Numerical Control(DNC)interface and the functions of a DNC interface system.One archit...This paper describes the innovation schemes of the interface of a CNC machine which cannot communicate with a computer by a Direct Numerical Control(DNC)interface and the functions of a DNC interface system.One architecture of hardware and software of a practi- cal single-chip computer based on DNC interface system developed by the authors is given. Without any change of the original hardware and software,this DNC interface system has been used to innovate the CNC machine's interface to implement the direct communication between a computer and a CNC machine and to achieve no tape transmission of a part program and ma- chine parameters.It has been demonstrated that this DNC interface system has certain practical values in improving the reliability,efficiency and production management of CNC/NC machine.展开更多
With the introduction of high-speed trains into chinese railway system, closeattention should be paid to the aspects of safety in hish-speed railways. Thereare many interfaces which are very important and directly rel...With the introduction of high-speed trains into chinese railway system, closeattention should be paid to the aspects of safety in hish-speed railways. Thereare many interfaces which are very important and directly related to drivmgsafety. This paper focuses on features of design and analyses the principles ofsafety.展开更多
As agricultural machines become more complex, it is increasingly critical that special attention be directed to the design of the user interface to ensure that the operator will have an adequate understanding of the s...As agricultural machines become more complex, it is increasingly critical that special attention be directed to the design of the user interface to ensure that the operator will have an adequate understanding of the status of the machine at all times. A user-centred design focus was employed to develop two conceptual designs (UCD1 & UCD2) for a user interface for an agricultural air seeder. The two concepts were compared against an existing user interface (baseline condition) using the metrics of situation awareness (Situation Awareness Global Assessment Technique), mental workload (Integrated Workload Scale), reaction time, and subjective feedback. There were no statistically significant differences among the three user interfaces based on the metric of situation awareness;however, UCD2 was deemed to be significantly better than either UCD1 or the baseline interface on the basis of mental workload, reaction time and subjective feedback. The research has demonstrated that a user-centred design focus will generate a better user interface for an agricultural machine.展开更多
The Brain-Computer Interfaces(BCIs)had been proposed and used in therapeutics for decades.However,the need of time-consuming calibration phase and the lack of robustness,which are caused by little-labeled data,are res...The Brain-Computer Interfaces(BCIs)had been proposed and used in therapeutics for decades.However,the need of time-consuming calibration phase and the lack of robustness,which are caused by little-labeled data,are restricting the advance and application of BCI,especially for the BCI based on motor imagery(MI).In this paper,we reviewed the recent development in the machine learning algorithm used in the MI-based BCI,which may provide potential solutions for addressing the issue.We classified these algorithms into two categories,namely,and enhancing the representation and expanding the training set.Specifically,these methods of enhancing the representation of features collected from few EEG trials are based on extracting features of multiple bands,regularization,and so on.The methods of expanding the training dataset include approaches of transfer learning(session to session transfer,subject to subject transfer)and generating artificial EEG data.The result of these techniques showed the resolution of the challenges to some extent.As a developing research area,the study of BCI algorithms in little-labeled data is increasingly requiring the advancement of human brain physiological structure research and more transfer learning algorithms research.展开更多
Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common d...Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.展开更多
Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However...Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However, the current systems should take advantage of the operator's attention to obtain the optimal solution.In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles(multi-UAVs) to recognize the targets in the images. Then,the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator's attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.展开更多
In the field of robotics and in the health sciences, transitions have been occurring in the control of robots operating with predetermined logic and rules. Robotics in health care are influencing human caring dynamics...In the field of robotics and in the health sciences, transitions have been occurring in the control of robots operating with predetermined logic and rules. Robotics in health care are influencing human caring dynamics in many ways such as enhancing dependency and surrender to machine technologies. Situations such as these are charged with possibilities of legal liabilities triggered by influences and consequences of advancing robotic technology dependency. The purpose of this paper is to identify, describe, and explain legal issues and/or dilemmas centered on robotics in healthcare while providing engaging opportunities to limit consequent legalities thus forming beneficial human health care outcomes. Laying bare these liabilities will provide critically informative data that can foster proactive encounters which can or may deter health care liabilities while ensuring quality healthcare outcomes. An attempt is made to re-conceptualize how to view agency, causality, liability responsibility, culpability, and autonomy for the new age of autonomous robots. While it is still not clear how this would turn out, a clear framing of the problem is the first step in the project.展开更多
Bio-based human computer interface (HCI) has attracted more and more attention of researches all over the world in recent years. In this paper, a HCI system which based on electrooculogram (EOG) is proposed. It transf...Bio-based human computer interface (HCI) has attracted more and more attention of researches all over the world in recent years. In this paper, a HCI system which based on electrooculogram (EOG) is proposed. It transforms electrical po-tentials recorded by horizontal and vertical EOG into a computer in order to control external equipment. The system consists of EOG acqui-sition unit, EOG pattern recognition part and control command output unit. Three plane elec-trodes are employed to detect EOG signals, which contain the information related to the eye blinking and vertical (or horizontal) eye move-ments referred to pre-designed command table. An online signal processing algorithm is de-signed to get the command information con-tained in EOG signals, and these commands could be used to control the computer or other instruments. Based on this HCI system, the remote control experiments driven by EOG are realized.展开更多
Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers.In this paper,we have presented methodology to recognize human behavior in thin crowd which may b...Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers.In this paper,we have presented methodology to recognize human behavior in thin crowd which may be very helpful in surveillance.Research have mostly focused the problem of human detection in thin crowd,overall behavior of the crowd and actions of individuals in video sequences.Vision based Human behavior modeling is a complex task as it involves human detection,tracking,classifying normal and abnormal behavior.The proposed methodology takes input video and applies Gaussian based segmentation technique followed by post processing through presenting hole filling algorithm i.e.,fill hole inside objects algorithm.Human detection is performed by presenting human detection algorithm and then geometrical features from human skeleton are extracted using feature extraction algorithm.The classification task is achieved using binary and multi class support vector machines.The proposed technique is validated through accuracy,precision,recall and F-measure metrics.展开更多
In this paper, a vibration motion control is proposed and implemented on a foamed polystyrene machining robot to suppress the generation of undesirable cusp marks, and the basic performance of the controller is verifi...In this paper, a vibration motion control is proposed and implemented on a foamed polystyrene machining robot to suppress the generation of undesirable cusp marks, and the basic performance of the controller is verified through machining experiments of foamed polystyrene. Then, a 3 dimensional （3D） printer-like data interface is proposed for the machining robot. The 3D data inter- face enables to control the machining robot directly using stereolithography （STL） data without conducting any computer-aided man- ufacturing （CAM） process. This is done by developing a robotic preprocessor that helps to remove the need for the conventional CAM process by directly converting the STL data into cutter location source data called cutter location （CL） or cutter location source （CLS） data. The STL is a file format proposed by 3D systems, and recently is supported by many computer aided design （CAD）/CAM soft- waxes. The STL is widely used for rapid prototyping with a 3D printer which is a typical additive manufacturing system. The STL deals with a triangular representation of a curved surface geometry. The developed 3D printer-like data interface allows to directly control the machining robot through a zigzag path, rectangular spiral path and circular spiral path generated according to the information included in STL data. The effectiveness and usefulness of the developed system are demonstrated through actual machining experiments.展开更多
This paper presents an image processing design flow for virtual fitting room (VFR) applications, targeting both personal computers and mobile devices. The proposed human friendly interface is implemented by a three-st...This paper presents an image processing design flow for virtual fitting room (VFR) applications, targeting both personal computers and mobile devices. The proposed human friendly interface is implemented by a three-stage algorithm: Detection and sizing of the user's body, detection of reference points based on face detection and augmented reality markers, and superimposition of the clothing over the user's image. Compared to other existing VFR systems, key difference is the lack of any proprietary hardware components or peripherals. Proposed VFR is software based and designed to be universally compatible as long as the device has a camera. Furthermore, JAVA implementation on Android based mobile systems is computationally efficient and it can run in real-time on existing mobile devices.展开更多
Exposure to environmental cadmium increases the health risk of residents.Early urine metabolic detection using high-resolution mass spectrometry and machine learning algorithms would be advantageous to predict the adv...Exposure to environmental cadmium increases the health risk of residents.Early urine metabolic detection using high-resolution mass spectrometry and machine learning algorithms would be advantageous to predict the adverse health effects.Here,we conducted machine learning approaches to screen potential biomarkers under cadmium exposure in 403 urine samples.In positive and negative ionization mode,4207 and 3558 features were extracted,respectively.We compared seven machine learning algorithms and found that the extreme gradient boosting(XGBoost)and random forest(RF)classifiers showed better accuracy and predictive performance than others.Following 5-fold cross-validation,the value of area under curve(AUC)was both 0.93 for positive and negative ionization modes in XGBoost classifier.In the RF classifier,AUC were 0.80 and 0.84 for positive and negative ionization modes,respectively.We then identified a biomarker panel based on XGBoost and RF classifiers.The incorporation of machine learning models into urine analysis using high-resolution mass spectrometry could allow a convenient assessment of cadmium exposure.展开更多
基金funding support from the National Natural Science Foundation of China(92472109,T2325012)the Program for HUST Academic Frontier Youth Team+1 种基金support from the Fundamental Research Funds for the Central Universities(HUST,5003120083)supported by the Postdoctoral Fellowship Program of CPSF(GZC20240532)。
文摘Batteries play a critical role in electric vehicles and distributed energy generation.With the growing demand for energy storage solutions,new battery materials and systems are continually being developed.In this process,molecular dynamics(MD)simulations can reveal the microscopic mechanisms of battery processes,thereby boosting the design of batteries.Compared to other MD simulation techniques,the machine learning force field(MLFF)holds the advantages of first-principles accuracy along with large spatial and temporal scale,offering opportunities to uncover new mechanisms in battery systems.This review presents a detailed overview of the fundamental principles and model types of MLFFs,as well as their applications in simulating the structure,transport properties,and chemical reaction properties of bulk battery materials and interfaces.Notably,we emphasize the long-range interaction corrections and constant-potential methods in the model design of MLFFs.Finally,we discuss the challenges and prospects of applying MLFF models in the research of batteries.
基金supported by the research project RORAS 2 of the Mediterranean Program funded by INRIA,France
文摘We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.
文摘Today’s product creative design has rendered many fe atures and has brought a great change in our everyday life, there are many new c hallenges in its traditional theory and principle. According to the traditional design theory, the FBS design model pays more attention to the function and stru cture of the product. But this model still couldn’t strengthen the relation bet ween product appearance design and human-machine design effectively. This paper adopt converse design thinking and presents an improved design thinking methodo logy based on C: FBS for product appearance design and give a general summarizat ion for the features, methods and technology based on human-machine interaction and interface. Meanwhile it also combines with the behavior design of product r elated IT fields and constructs a new outline to improve the design of product a ppearance supported by the technology of computer aided design. So the new metho d about design thinking for computer aided design, the new abstract product design model and the key problem of design thinking based on human-machine inte raction and interface are addressed in this paper. This kind of creative design theory that is driven by human-machine interaction and interface will help the development of CAD software system and the research of product design and manufa cture. Additionally, this paper gives some beneficial characters to address the theory based on human-machine interaction and interface. Meanwhile, combining with the developing of computer technology, the trends of design thinking based on t he technology of human-machine interaction and interface are also analyzed and discussed at the end of this paper.
基金the China Academy of Chinese Medical Sciences,Independent Topic Project:Application Research on Named Entity Recognition and Relationship Extraction of Case Records of Renowned Traditional Chinese Medicine Practitioners(No.Z0643).China Academy of Chinese Medical Sciences,Independent Topic Project:Analysis of Research Directions and Scope in the Discipline of Traditional Chinese Medicine Statistics(No.Z0723)China Academy of Chinese Medical Sciences,Science and Technology Innovation Project:Real-world Effectiveness Evaluation of Traditional Chinese Medicine and Translational Application Research on Causal Inference(No.CI2021A04706).China Academy of Chinese Medical Sciences,Science and Technology Innovation Project:Research on Causal Inference Methodology for Real-world Clinical Evaluation in Traditional Chinese Medicine(No.CI2021B003)National Key Research and Development Program of China:Integrated Evaluation Model and Key Technologies of"Syndrome-Disease-Prescription"for Traditional Chinese Medicine in the Prevention and Treatment of Coronary Heart Disease—Statistical Data Analysis and Data Mining(No.2017YFC1700406-2)。
文摘OBJECTIVE:To enhance the understanding of identifying personalized pharmacotherapy options in Traditional Chinese Medicine(TCM),and further support the registration of new TCM drugs.METHODS:Generalized Boosted Models and XGBoost were employed to construct a classification model to identify the bad prognosis factors in resistant hypertension(RH)patients.Furthermore,we used association analysis to explore the rules of"symptomsyndrome"and"symptom-herb"for the major influencing factors,in order to summarize prescription pattern and applicable patients of TCM.RESULTS:Patients with major adverse cardiac events mostly have complex symptoms of phlegm,stasis,deficiency and fire intermingled with each other,and finally summarized the human experience of using Chinese herbal medicine to precisely intervene in some symptoms of RH patients on the basis of conventional Western medical treatment.CONCLUSIONS:Machine learning algorithms can make full use of human use experience and evidence to save clinical trial resources and accelerate the development of TCM varieties.
基金supported by the National Natural Science Foundation of China (62075006)the National Key R&D Program of China (2018YFB1500200)。
文摘Interface engineering is proved to be the most important strategy to push the device performance of the perovskite solar cell(PSC) to its limit, and numerous works have been conducted to screen efficient materials. Here, on the basis of the previous studies, we employ machine learning to map the relationship between the interface material and the device performance, leading to intelligently screening interface materials towards minimizing voltage losses in p-i-n type PSCs. To enhance the explainability of the machine learning models, molecular descriptors are used to represent the materials. Furthermore,experimental analysis with different characterization methods and device simulation based on the drift-diffusion physical model are conducted to get physical insights and validate the machine learning models. Accordingly, 3-thiophene ethylamine hydrochloride(Th EACl) is screened as an example, which enables remarkable improvements in VOCand PCE of the PSCs. Our work reveals the critical role of datadriven analysis in the high throughput screening of interface materials, which will significantly accelerate the exploration of new materials for high-efficiency PSCs.
基金supported by the Science and Technology Commission of Shanghai Municipality(STCSM)Research Fund(21JC1405300)to Fan Minthe National Key Research and Development Program of China(2018YFC0831102)sponsored by the Shanghai Key Research Laboratory of NSAI。
文摘The awareness detection in patients with disorders of consciousness currently relies on behavioral observations and CRS-R tests,however,the misdiagnosis rates have been relatively high.In this study,we applied brain-computer interface(BCI)to awareness detection with a passive auditory stimulation paradigm.12 subjects with normal hearing were invited to collect electroencephalogram(EEG)based on a BCI communication system,in which EEG signals are transmitted wirelessly.After necessary preprocessing,RBF-SVM and EEGNet were used for algorithm realization and analysis.For a single subject,RBF-SVM can distinguish his(her)name stimuli awareness with classification accuracies ranging from 60-95%.EEGNet was used to learn all subjects'data and improved accuracy to 78.04%for characteristics finding and model generalization.Moreover,we completed the supplementary analysis work from the time domain and time-frequency domain.This study applied BCI communication to human awareness detection,proposed a passive auditory paradigm,and proved the effectiveness,which could be an inspiration for brain,mental or physical diseases diagnosis and detection.
基金the National Natural Science Foundation of China(22225302,21991151,21991150,22021001,92161113,91945301)the Fundamental Research Funds for the Central Universities(20720220009)+1 种基金the China Postdoctoral Science Foundation(2020 M682079)the Guangdong Basic and Applied Basic Research Foundation(2020A1515110539)。
文摘GaP has been shown to be a promising photoelectrocatalyst for selective CO_(2)reduction to methanol.Due to the relevance of the interface structure to important processes such as electron/proton transfer,a detailed understanding of the GaP(110)-water interfacial structure is of great importance.Ab initio molecular dynamics(AIMD)can be used for obtaining the microscopic information of the interfacial structure.However,the GaP(110)-water interface cannot converge to an equilibrated structure at the time scale of the AIMD simulation.In this work,we perform the machine learning accelerated molecular dynamics(MLMD)to overcome the difficulty of insufficient sampling by AIMD.With the help of MLMD,we unravel the microscopic information of the structure of the GaP(110)-water interface,and obtain a deeper understanding of the mechanisms of proton transfer at the GaP(110)-water interface,which will pave the way for gaining valuable insights into photoelectrocatalytic mechanisms and improving the performance of photoelectrochemical cells.
文摘This paper describes the innovation schemes of the interface of a CNC machine which cannot communicate with a computer by a Direct Numerical Control(DNC)interface and the functions of a DNC interface system.One architecture of hardware and software of a practi- cal single-chip computer based on DNC interface system developed by the authors is given. Without any change of the original hardware and software,this DNC interface system has been used to innovate the CNC machine's interface to implement the direct communication between a computer and a CNC machine and to achieve no tape transmission of a part program and ma- chine parameters.It has been demonstrated that this DNC interface system has certain practical values in improving the reliability,efficiency and production management of CNC/NC machine.
文摘With the introduction of high-speed trains into chinese railway system, closeattention should be paid to the aspects of safety in hish-speed railways. Thereare many interfaces which are very important and directly related to drivmgsafety. This paper focuses on features of design and analyses the principles ofsafety.
文摘As agricultural machines become more complex, it is increasingly critical that special attention be directed to the design of the user interface to ensure that the operator will have an adequate understanding of the status of the machine at all times. A user-centred design focus was employed to develop two conceptual designs (UCD1 & UCD2) for a user interface for an agricultural air seeder. The two concepts were compared against an existing user interface (baseline condition) using the metrics of situation awareness (Situation Awareness Global Assessment Technique), mental workload (Integrated Workload Scale), reaction time, and subjective feedback. There were no statistically significant differences among the three user interfaces based on the metric of situation awareness;however, UCD2 was deemed to be significantly better than either UCD1 or the baseline interface on the basis of mental workload, reaction time and subjective feedback. The research has demonstrated that a user-centred design focus will generate a better user interface for an agricultural machine.
文摘The Brain-Computer Interfaces(BCIs)had been proposed and used in therapeutics for decades.However,the need of time-consuming calibration phase and the lack of robustness,which are caused by little-labeled data,are restricting the advance and application of BCI,especially for the BCI based on motor imagery(MI).In this paper,we reviewed the recent development in the machine learning algorithm used in the MI-based BCI,which may provide potential solutions for addressing the issue.We classified these algorithms into two categories,namely,and enhancing the representation and expanding the training set.Specifically,these methods of enhancing the representation of features collected from few EEG trials are based on extracting features of multiple bands,regularization,and so on.The methods of expanding the training dataset include approaches of transfer learning(session to session transfer,subject to subject transfer)and generating artificial EEG data.The result of these techniques showed the resolution of the challenges to some extent.As a developing research area,the study of BCI algorithms in little-labeled data is increasingly requiring the advancement of human brain physiological structure research and more transfer learning algorithms research.
基金supported by National Natural Science Foundation of China(52202117,52232006,52072029,and 12102256)Collaborative Innovation Platform Project of Fu-Xia-Quan National Independent Innovation Demonstration Zone(3502ZCQXT2022005)+3 种基金Natural Science Foundation of Fujian Province of China(2022J01065)State Key Lab of Advanced Metals and Materials(2022-Z09)Fundamental Research Funds for the Central Universities(20720220075)the Ministry of Education,Singapore,under its MOE ARF Tier 2(MOE2019-T2-2-179).
文摘Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.
基金the National Natural Science Foundation of China(No.61403410)
文摘Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However, the current systems should take advantage of the operator's attention to obtain the optimal solution.In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles(multi-UAVs) to recognize the targets in the images. Then,the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator's attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.
文摘In the field of robotics and in the health sciences, transitions have been occurring in the control of robots operating with predetermined logic and rules. Robotics in health care are influencing human caring dynamics in many ways such as enhancing dependency and surrender to machine technologies. Situations such as these are charged with possibilities of legal liabilities triggered by influences and consequences of advancing robotic technology dependency. The purpose of this paper is to identify, describe, and explain legal issues and/or dilemmas centered on robotics in healthcare while providing engaging opportunities to limit consequent legalities thus forming beneficial human health care outcomes. Laying bare these liabilities will provide critically informative data that can foster proactive encounters which can or may deter health care liabilities while ensuring quality healthcare outcomes. An attempt is made to re-conceptualize how to view agency, causality, liability responsibility, culpability, and autonomy for the new age of autonomous robots. While it is still not clear how this would turn out, a clear framing of the problem is the first step in the project.
文摘Bio-based human computer interface (HCI) has attracted more and more attention of researches all over the world in recent years. In this paper, a HCI system which based on electrooculogram (EOG) is proposed. It transforms electrical po-tentials recorded by horizontal and vertical EOG into a computer in order to control external equipment. The system consists of EOG acqui-sition unit, EOG pattern recognition part and control command output unit. Three plane elec-trodes are employed to detect EOG signals, which contain the information related to the eye blinking and vertical (or horizontal) eye move-ments referred to pre-designed command table. An online signal processing algorithm is de-signed to get the command information con-tained in EOG signals, and these commands could be used to control the computer or other instruments. Based on this HCI system, the remote control experiments driven by EOG are realized.
文摘Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers.In this paper,we have presented methodology to recognize human behavior in thin crowd which may be very helpful in surveillance.Research have mostly focused the problem of human detection in thin crowd,overall behavior of the crowd and actions of individuals in video sequences.Vision based Human behavior modeling is a complex task as it involves human detection,tracking,classifying normal and abnormal behavior.The proposed methodology takes input video and applies Gaussian based segmentation technique followed by post processing through presenting hole filling algorithm i.e.,fill hole inside objects algorithm.Human detection is performed by presenting human detection algorithm and then geometrical features from human skeleton are extracted using feature extraction algorithm.The classification task is achieved using binary and multi class support vector machines.The proposed technique is validated through accuracy,precision,recall and F-measure metrics.
基金supported by the Japam Society for the Promotion of Science(JSPS)KAKENHI(Nos.25420232 and 16K06203)
文摘In this paper, a vibration motion control is proposed and implemented on a foamed polystyrene machining robot to suppress the generation of undesirable cusp marks, and the basic performance of the controller is verified through machining experiments of foamed polystyrene. Then, a 3 dimensional （3D） printer-like data interface is proposed for the machining robot. The 3D data inter- face enables to control the machining robot directly using stereolithography （STL） data without conducting any computer-aided man- ufacturing （CAM） process. This is done by developing a robotic preprocessor that helps to remove the need for the conventional CAM process by directly converting the STL data into cutter location source data called cutter location （CL） or cutter location source （CLS） data. The STL is a file format proposed by 3D systems, and recently is supported by many computer aided design （CAD）/CAM soft- waxes. The STL is widely used for rapid prototyping with a 3D printer which is a typical additive manufacturing system. The STL deals with a triangular representation of a curved surface geometry. The developed 3D printer-like data interface allows to directly control the machining robot through a zigzag path, rectangular spiral path and circular spiral path generated according to the information included in STL data. The effectiveness and usefulness of the developed system are demonstrated through actual machining experiments.
文摘This paper presents an image processing design flow for virtual fitting room (VFR) applications, targeting both personal computers and mobile devices. The proposed human friendly interface is implemented by a three-stage algorithm: Detection and sizing of the user's body, detection of reference points based on face detection and augmented reality markers, and superimposition of the clothing over the user's image. Compared to other existing VFR systems, key difference is the lack of any proprietary hardware components or peripherals. Proposed VFR is software based and designed to be universally compatible as long as the device has a camera. Furthermore, JAVA implementation on Android based mobile systems is computationally efficient and it can run in real-time on existing mobile devices.
基金supported by the National Key Research and Development Program of China(No.2017YFC1600500)。
文摘Exposure to environmental cadmium increases the health risk of residents.Early urine metabolic detection using high-resolution mass spectrometry and machine learning algorithms would be advantageous to predict the adverse health effects.Here,we conducted machine learning approaches to screen potential biomarkers under cadmium exposure in 403 urine samples.In positive and negative ionization mode,4207 and 3558 features were extracted,respectively.We compared seven machine learning algorithms and found that the extreme gradient boosting(XGBoost)and random forest(RF)classifiers showed better accuracy and predictive performance than others.Following 5-fold cross-validation,the value of area under curve(AUC)was both 0.93 for positive and negative ionization modes in XGBoost classifier.In the RF classifier,AUC were 0.80 and 0.84 for positive and negative ionization modes,respectively.We then identified a biomarker panel based on XGBoost and RF classifiers.The incorporation of machine learning models into urine analysis using high-resolution mass spectrometry could allow a convenient assessment of cadmium exposure.
