The shop floor dynamic scheduling system based on human-computer interaction is the use of computer-aided decision-making and human-computer interaction to solve the dynamic scheduling problem.A human-computer interac...The shop floor dynamic scheduling system based on human-computer interaction is the use of computer-aided decision-making and human-computer interaction to solve the dynamic scheduling problem.A human-computer interaction interface based on Gantt chart is designed,which can not only comprehensively and quantitatively represent the scheduling process and scheduling scheme,but also have friendly human-computer interaction performance.The data transmission and interaction architecture is constructed to realize the rapid response to shop floor disturbance events.A priority calculation algorithm integrating priority rules and dispatcher preference is proposed,which realizes the automatic calculation of priority for the dispatcher's reference and reduces theirburden.A man-machine interactive shop floor dynamic scheduling strategy is proposed.When solving the dynamic flexible job shop scheduling problem caused by machine tool breakdown and urgent order,the origin moments obtained by using this strategy are 0.4190 and 0.3703 respectively.As can be seen from the origin moment indicator,the dynamic shop floor scheduling system based on the human-computer interaction is efficient and reliable in solving dynamic scheduling problems,and related strategies of this system are also feasible and stable.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
Indoor scene semantic segmentation is essential for enabling robots to understand and interact with their environments effectively.However,numerous challenges remain unresolved,particularly in single-robot systems,whi...Indoor scene semantic segmentation is essential for enabling robots to understand and interact with their environments effectively.However,numerous challenges remain unresolved,particularly in single-robot systems,which often struggle with the complexity and variability of indoor scenes.To address these limitations,we introduce a novel multi-robot collaborative framework based on multiplex interactive learning(MPIL)in which each robot specialises in a distinct visual task within a unified multitask architecture.During training,the framework employs task-specific decoders and cross-task feature sharing to enhance collaborative optimisation.At inference time,robots operate independently with optimised models,enabling scalable,asynchronous and efficient deployment in real-world scenarios.Specifically,MPIL employs specially designed modules that integrate RGB and depth data,refine feature representations and facilitate the simultaneous execution of multiple tasks,such as instance segmentation,scene classification and semantic segmentation.By leveraging these modules,distinct agents within multi-robot systems can effectively handle specialised tasks,thereby enhancing the overall system's flexibility and adaptability.This collaborative effort maximises the strengths of each robot,resulting in a more comprehensive understanding of environments.Extensive experiments on two public benchmark datasets demonstrate MPIL's competitive performance compared to state-of-the-art approaches,highlighting the effectiveness and robustness of our multi-robot system in complex indoor environments.展开更多
Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture ...Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture recognition could lead to more natural and intuitive HCI interactions.This paper reviews the state-of-the-art vision-based gestures recognition methods,from different stages of gesture recognition process,i.e.,(1)image acquisition and pre-processing,(2)gesture segmentation,(3)gesture tracking,(4)feature extraction,and(5)gesture classification.This paper also analyzes the advantages and disadvantages of these various methods in detail.Finally,the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.展开更多
To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA...To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.展开更多
Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates...Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theflexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.展开更多
The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remai...The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Xizang Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.展开更多
With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-...With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-Computer Interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.展开更多
Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide...Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.展开更多
A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the seg...A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.展开更多
Convolutional neural networks(CNNs)are prone to mis-segmenting image data of the liver when the background is complicated,which results in low segmentation accuracy and unsuitable results for clinical use.To address t...Convolutional neural networks(CNNs)are prone to mis-segmenting image data of the liver when the background is complicated,which results in low segmentation accuracy and unsuitable results for clinical use.To address this shortcoming,an interactive liver segmentation algorithm based on geodesic distance and V-net is proposed.The three-dimensional segmentation network V-net adequately considers the characteristics of the spatial context information to segment liver medical images and obtain preliminary segmentation results.An artificial algorithm based on geodesic distance is used to form artificial hard constraints to modify the image,and the superpixel piece created by the watershed algorithm is introduced as a sample point for operation,which significantly improves the efficiency of segmentation.Results from simulation of the liver tumor segmentation challenge(LiTS)dataset show that this algorithm can effectively refine the results of automatic liver segmentation,reduce user intervention,and enable a fast,interactive liver image segmentation that is convenient for doctors.展开更多
Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in v...Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in virtual environments is primarily realized using grounded force or vibration feedback devices.However,improvements are required in terms of the active space and feedback realism.Methods We propose a lightweight and flexible haptic feedback glove that can haptically render objects in VR environments via kinesthetic and vibration feedback,thereby enabling users to enjoy a rich virtual piano-playing experience.The kinesthetic feedback of the glove relies on a cable-pulling mechanism that rotates the mechanism and pulls the two cables connected to it,thereby changing the amount of force generated to simulate the hardness or softness of the object.Vibration feedback is provided by small vibration motors embedded in the bottom of the fingertips of the glove.We designed a piano-playing scenario in the virtual environment and conducted user tests.The evaluation metrics were clarity,realism,enjoyment,and satisfaction.Results A total of 14 subjects participated in the test,and the results showed that our proposed glove scored significantly higher on the four evaluation metrics than the nofeedback and vibration feedback methods.Conclusions Our proposed glove significantly enhances the user experience when interacting with virtual objects.展开更多
Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing.Despite the success of Convolutional Neural Networks(CNNs),they often fail to capture inter-layer feature relat...Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing.Despite the success of Convolutional Neural Networks(CNNs),they often fail to capture inter-layer feature relationships and fully leverage contextual information,leading to the loss of important details.Additionally,due to significant intraclass variation and small inter-class differences in remote sensing images,CNNs may experience class confusion.To address these issues,we propose a novel Category-Guided Feature Collaborative Learning Network(CG-FCLNet),which enables fine-grained feature extraction and adaptive fusion.Specifically,we design a Feature Collaborative Learning Module(FCLM)to facilitate the tight interaction of multi-scale features.We also introduce a Scale-Aware Fusion Module(SAFM),which iteratively fuses features from different layers using a spatial attention mechanism,enabling deeper feature fusion.Furthermore,we design a Category-Guided Module(CGM)to extract category-aware information that guides feature fusion,ensuring that the fused featuresmore accurately reflect the semantic information of each category,thereby improving detailed segmentation.The experimental results show that CG-FCLNet achieves a Mean Intersection over Union(mIoU)of 83.46%,an mF1 of 90.87%,and an Overall Accuracy(OA)of 91.34% on the Vaihingen dataset.On the Potsdam dataset,it achieves a mIoU of 86.54%,an mF1 of 92.65%,and an OA of 91.29%.These results highlight the superior performance of CG-FCLNet compared to existing state-of-the-art methods.展开更多
Electron-wall interaction is always recognized as an important physical problem because of its remarkable influences on thruster discharge and performance. Based on existing theories, an electrode is predicted to weak...Electron-wall interaction is always recognized as an important physical problem because of its remarkable influences on thruster discharge and performance. Based on existing theories, an electrode is predicted to weaken electron-wall interaction due to its low secondary electron emission characteristic. In this paper, the electron-wall interaction in an Aton-type Hall thruster with low-emissive electrodes placed near the exit of discharge channel is studied by a fully kinetic particle-in cell method. The results show that the electron-wall interaction in the region of segmented electrode is indeed weakened, but it is significantly enhanced in the remaining region of discharge channel. It is mainly caused by electrode conductive property which makes equipotential lines convex toward channel exit and even parallel to wall surface in near-wall re- gion; this convex equipotential configuration results in significant physical effects such as repelling electrons, which causes the electrons to move toward the channel center, and the electrons emitted from electrodes to be remarkably accelerated, thereby increasing electron temperature in the discharge channel, etc. Furthermore, the results also indicate that the discharge current in the segmented electrode case is larger than in the non-segmented electrode case, which is qualitatively in accordance with previous experimental results.展开更多
neural network model based on backbone propagation was applied to Learn-ing and predicting the interaction between antiparallelly interactive peptide seg-ments in proteins.Hydrophobic properties pf residues were found...neural network model based on backbone propagation was applied to Learn-ing and predicting the interaction between antiparallelly interactive peptide seg-ments in proteins.Hydrophobic properties pf residues were found dominant in in-terpeptides.Weights of each kind of residues, obtained by this work,suggestedsome different scales for the hydrophobicity of the residue.These will be helpful in understanding polypeptide structure and protein folding.展开更多
The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are ...The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.展开更多
Polyurethane elastomers exhibit high dielectric constants owing to their polar groups,and can be used as energy storage capacitors.Energy storage depends not only on the dielectric constant but also on the dielectric ...Polyurethane elastomers exhibit high dielectric constants owing to their polar groups,and can be used as energy storage capacitors.Energy storage depends not only on the dielectric constant but also on the dielectric loss.However,the relationship between chain structure and dielectric properties is not yet clear.Ketal-containing crosslinked polyurethane elastomers were prepared using cyclic ketal diol as a chain extender.The effect of the soft segment length on the dielectric properties and energy storage was investigated.The cause of the change in the dipolar polarization with the soft segment length was analyzed.As the soft segment length increased,the hard-soft hydrogen bonding decreased,whereas the hard-hard hydrogen bonding increased.Under the action of an electric field,the polar bonds in the ketal-containing polyurethane elastomer overcome the hydrogen bonding between hard-soft segments to produce polarization;meanwhile,they also experience crankshaft motions to generate polarization.The former has a relatively high relaxation activation energy of approximately 10-20 k J·mol^(-1),resulting in a large dielectric loss.The latter has a relatively low relaxation activation energy,approximately 0.7-1.7 kJ·mol^(-1),leading to low dielectric loss.As a result,the dielectric constant showed a decreasing trend,and the dielectric loss gradually decreased.This study provides a theoretical foundation for improving the dielectric properties of polyurethane elastomers.展开更多
Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability o...Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability of these robots.Therefore,this study proposes a variable stiffness humancomputer interaction contact unit module(VSHCUM)based on the granular jamming mechanism.It is characterized by a double-layer chamber structure:the inner layer is a granular chamber,and the outer layer is an air chamber.The interaction force is transmitted by embedding a rigid support in the inner layer.Unlike the common flexible-belt interactive contact unit,when the exoskeleton is bound to the patient's limb,vSHCUM can realize adaptive fitting of the patient's limb shape using the pressure change in the double-chamber structure.Simultaneously,by adjusting the vacuum level of the granular chamber,the stiffness of the interactive contact unit can be adjusted by a factor of more than five,and the internal work loss caused by self-pulling deformation during the auxiliary force transfer process can be reduced.展开更多
Face recognition provides a natural visual interface for human computer interaction （HCI） applications. The process of face recognition, however, is inhibited by variations in the appearance of face images caused by...Face recognition provides a natural visual interface for human computer interaction （HCI） applications. The process of face recognition, however, is inhibited by variations in the appearance of face images caused by changes in lighting, expression, viewpoint, aging and introduction of occlusion. Although various algorithms have been presented for face recognition, face recognition is still a very challenging topic. A novel approach of real time face recognition for HCI is proposed in the paper. In view of the limits of the popular approaches to foreground segmentation, wavelet multi-scale transform based background subtraction is developed to extract foreground objects. The optimal selection of the threshold is automatically determined, which does not require any complex supervised training or manual experimental calibration. A robust real time face recognition algorithm is presented, which combines the projection matrixes without iteration and kernel Fisher discriminant analysis （KFDA） to overcome some difficulties existing in the real face recognition. Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments. The proposed algorithm can also be applied to the video image sequences of natural HCI.展开更多
基金supported by the Tianjin Enterprise Science and Technology Commissioner Project(Grant No.23YDTPJC00740,Grant No.24YDTPJC00610)the Tianjin Tiankai Higher Education Science and Technology Innovation Park Enterprise R&D Special Project(Grant No.23YFZXYC00027).
文摘The shop floor dynamic scheduling system based on human-computer interaction is the use of computer-aided decision-making and human-computer interaction to solve the dynamic scheduling problem.A human-computer interaction interface based on Gantt chart is designed,which can not only comprehensively and quantitatively represent the scheduling process and scheduling scheme,but also have friendly human-computer interaction performance.The data transmission and interaction architecture is constructed to realize the rapid response to shop floor disturbance events.A priority calculation algorithm integrating priority rules and dispatcher preference is proposed,which realizes the automatic calculation of priority for the dispatcher's reference and reduces theirburden.A man-machine interactive shop floor dynamic scheduling strategy is proposed.When solving the dynamic flexible job shop scheduling problem caused by machine tool breakdown and urgent order,the origin moments obtained by using this strategy are 0.4190 and 0.3703 respectively.As can be seen from the origin moment indicator,the dynamic shop floor scheduling system based on the human-computer interaction is efficient and reliable in solving dynamic scheduling problems,and related strategies of this system are also feasible and stable.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
基金supported by the National Natural Science Foundation of China under Grant 62373009.
文摘Indoor scene semantic segmentation is essential for enabling robots to understand and interact with their environments effectively.However,numerous challenges remain unresolved,particularly in single-robot systems,which often struggle with the complexity and variability of indoor scenes.To address these limitations,we introduce a novel multi-robot collaborative framework based on multiplex interactive learning(MPIL)in which each robot specialises in a distinct visual task within a unified multitask architecture.During training,the framework employs task-specific decoders and cross-task feature sharing to enhance collaborative optimisation.At inference time,robots operate independently with optimised models,enabling scalable,asynchronous and efficient deployment in real-world scenarios.Specifically,MPIL employs specially designed modules that integrate RGB and depth data,refine feature representations and facilitate the simultaneous execution of multiple tasks,such as instance segmentation,scene classification and semantic segmentation.By leveraging these modules,distinct agents within multi-robot systems can effectively handle specialised tasks,thereby enhancing the overall system's flexibility and adaptability.This collaborative effort maximises the strengths of each robot,resulting in a more comprehensive understanding of environments.Extensive experiments on two public benchmark datasets demonstrate MPIL's competitive performance compared to state-of-the-art approaches,highlighting the effectiveness and robustness of our multi-robot system in complex indoor environments.
基金Supported by the National Natural Science Foundation of China(61773205,61773219)the Fundamental Research Funds for the Central Universities(NS2016032,NS2019018,Nanjing University of Aeronautics and Astronautics)+1 种基金the Scholarship from China Scholarship Council(201906835020)the Fundamental Research Funds for the Central Universities(the Graduate Student Innovation Base Open Fund Project of NUAA,kfjj20190307)。
文摘Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture recognition could lead to more natural and intuitive HCI interactions.This paper reviews the state-of-the-art vision-based gestures recognition methods,from different stages of gesture recognition process,i.e.,(1)image acquisition and pre-processing,(2)gesture segmentation,(3)gesture tracking,(4)feature extraction,and(5)gesture classification.This paper also analyzes the advantages and disadvantages of these various methods in detail.Finally,the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.
基金supported by the National Key Research and Development Program of China(2021YFB1600601)the Joint Funds of the National Natural Science Foundation of China and the Civil Aviation Administration of China(U1933106)+2 种基金the Scientific Research Project of Tianjin Educational Committee(2019KJ134)the Natural Science Foundation of TianjinIntelligent Civil Aviation Program(21JCQNJ C00900)。
文摘To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.
基金supported by the China Fundamental Research Funds for the Central Universities(2022JBQY006)。
文摘Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theflexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.
基金supported by the National Key Research and Development Program of China(2021YFB3901205)National Institute of Natural Hazards,Ministry of Emergency Management of China(2023-JBKY-57)。
文摘The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Xizang Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.
文摘With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-Computer Interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.
文摘Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.
文摘A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.
基金the Project of China Scholarship Council(No.201708615011)the Xi’an Science and Technology Plan Project(No.GXYD1.7)。
文摘Convolutional neural networks(CNNs)are prone to mis-segmenting image data of the liver when the background is complicated,which results in low segmentation accuracy and unsuitable results for clinical use.To address this shortcoming,an interactive liver segmentation algorithm based on geodesic distance and V-net is proposed.The three-dimensional segmentation network V-net adequately considers the characteristics of the spatial context information to segment liver medical images and obtain preliminary segmentation results.An artificial algorithm based on geodesic distance is used to form artificial hard constraints to modify the image,and the superpixel piece created by the watershed algorithm is introduced as a sample point for operation,which significantly improves the efficiency of segmentation.Results from simulation of the liver tumor segmentation challenge(LiTS)dataset show that this algorithm can effectively refine the results of automatic liver segmentation,reduce user intervention,and enable a fast,interactive liver image segmentation that is convenient for doctors.
基金This work was supported in part by the-National Natural Science Foundation of China （61403342, 61273286, U1509207, 61325019, 113 02195）, and Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering （2014KLA09）.
基金Supported by the Natienal Natural Science Foundation of China(U23A20287).
文摘Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in virtual environments is primarily realized using grounded force or vibration feedback devices.However,improvements are required in terms of the active space and feedback realism.Methods We propose a lightweight and flexible haptic feedback glove that can haptically render objects in VR environments via kinesthetic and vibration feedback,thereby enabling users to enjoy a rich virtual piano-playing experience.The kinesthetic feedback of the glove relies on a cable-pulling mechanism that rotates the mechanism and pulls the two cables connected to it,thereby changing the amount of force generated to simulate the hardness or softness of the object.Vibration feedback is provided by small vibration motors embedded in the bottom of the fingertips of the glove.We designed a piano-playing scenario in the virtual environment and conducted user tests.The evaluation metrics were clarity,realism,enjoyment,and satisfaction.Results A total of 14 subjects participated in the test,and the results showed that our proposed glove scored significantly higher on the four evaluation metrics than the nofeedback and vibration feedback methods.Conclusions Our proposed glove significantly enhances the user experience when interacting with virtual objects.
基金funded by National Natural Science Foundation of China(61603245).
文摘Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing.Despite the success of Convolutional Neural Networks(CNNs),they often fail to capture inter-layer feature relationships and fully leverage contextual information,leading to the loss of important details.Additionally,due to significant intraclass variation and small inter-class differences in remote sensing images,CNNs may experience class confusion.To address these issues,we propose a novel Category-Guided Feature Collaborative Learning Network(CG-FCLNet),which enables fine-grained feature extraction and adaptive fusion.Specifically,we design a Feature Collaborative Learning Module(FCLM)to facilitate the tight interaction of multi-scale features.We also introduce a Scale-Aware Fusion Module(SAFM),which iteratively fuses features from different layers using a spatial attention mechanism,enabling deeper feature fusion.Furthermore,we design a Category-Guided Module(CGM)to extract category-aware information that guides feature fusion,ensuring that the fused featuresmore accurately reflect the semantic information of each category,thereby improving detailed segmentation.The experimental results show that CG-FCLNet achieves a Mean Intersection over Union(mIoU)of 83.46%,an mF1 of 90.87%,and an Overall Accuracy(OA)of 91.34% on the Vaihingen dataset.On the Potsdam dataset,it achieves a mIoU of 86.54%,an mF1 of 92.65%,and an OA of 91.29%.These results highlight the superior performance of CG-FCLNet compared to existing state-of-the-art methods.
基金supported by the Fundamental Research Funds for the Central Universities,China(Grant No.0903005203189)the National Natural Science Foundation of China(Grant Nos.11005025,10975026,and 11275034)+1 种基金the Scientific Research Innovation Foundation of Harbin Institution of Technology,China(GrantNo.HITNSRIF2009044)the Key Project of the Scientific Technology Program of Liaoning Province,China(Grant No.2011224007)
文摘Electron-wall interaction is always recognized as an important physical problem because of its remarkable influences on thruster discharge and performance. Based on existing theories, an electrode is predicted to weaken electron-wall interaction due to its low secondary electron emission characteristic. In this paper, the electron-wall interaction in an Aton-type Hall thruster with low-emissive electrodes placed near the exit of discharge channel is studied by a fully kinetic particle-in cell method. The results show that the electron-wall interaction in the region of segmented electrode is indeed weakened, but it is significantly enhanced in the remaining region of discharge channel. It is mainly caused by electrode conductive property which makes equipotential lines convex toward channel exit and even parallel to wall surface in near-wall re- gion; this convex equipotential configuration results in significant physical effects such as repelling electrons, which causes the electrons to move toward the channel center, and the electrons emitted from electrodes to be remarkably accelerated, thereby increasing electron temperature in the discharge channel, etc. Furthermore, the results also indicate that the discharge current in the segmented electrode case is larger than in the non-segmented electrode case, which is qualitatively in accordance with previous experimental results.
文摘neural network model based on backbone propagation was applied to Learn-ing and predicting the interaction between antiparallelly interactive peptide seg-ments in proteins.Hydrophobic properties pf residues were found dominant in in-terpeptides.Weights of each kind of residues, obtained by this work,suggestedsome different scales for the hydrophobicity of the residue.These will be helpful in understanding polypeptide structure and protein folding.
基金funded by National Natural Science Foundation of China No.62062003Ningxia Natural Science Foundation Project No.2023AAC03293.
文摘The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.
基金financially supported by the Hubei Key Laboratory of Pollutant Analysis&Reuse Technology(No.PA230102)。
文摘Polyurethane elastomers exhibit high dielectric constants owing to their polar groups,and can be used as energy storage capacitors.Energy storage depends not only on the dielectric constant but also on the dielectric loss.However,the relationship between chain structure and dielectric properties is not yet clear.Ketal-containing crosslinked polyurethane elastomers were prepared using cyclic ketal diol as a chain extender.The effect of the soft segment length on the dielectric properties and energy storage was investigated.The cause of the change in the dipolar polarization with the soft segment length was analyzed.As the soft segment length increased,the hard-soft hydrogen bonding decreased,whereas the hard-hard hydrogen bonding increased.Under the action of an electric field,the polar bonds in the ketal-containing polyurethane elastomer overcome the hydrogen bonding between hard-soft segments to produce polarization;meanwhile,they also experience crankshaft motions to generate polarization.The former has a relatively high relaxation activation energy of approximately 10-20 k J·mol^(-1),resulting in a large dielectric loss.The latter has a relatively low relaxation activation energy,approximately 0.7-1.7 kJ·mol^(-1),leading to low dielectric loss.As a result,the dielectric constant showed a decreasing trend,and the dielectric loss gradually decreased.This study provides a theoretical foundation for improving the dielectric properties of polyurethane elastomers.
基金Supported by National Key R&D Program of China(Grant Nos.2022YFC3601704,2023YFB4706100)National Natural Science Foundation of China(Grant Nos.U23A20338,62203149).
文摘Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability of these robots.Therefore,this study proposes a variable stiffness humancomputer interaction contact unit module(VSHCUM)based on the granular jamming mechanism.It is characterized by a double-layer chamber structure:the inner layer is a granular chamber,and the outer layer is an air chamber.The interaction force is transmitted by embedding a rigid support in the inner layer.Unlike the common flexible-belt interactive contact unit,when the exoskeleton is bound to the patient's limb,vSHCUM can realize adaptive fitting of the patient's limb shape using the pressure change in the double-chamber structure.Simultaneously,by adjusting the vacuum level of the granular chamber,the stiffness of the interactive contact unit can be adjusted by a factor of more than five,and the internal work loss caused by self-pulling deformation during the auxiliary force transfer process can be reduced.
基金supported by the National Natural Science Foundation of China (Grant No.60872117)the Leading Academic Discipline Project of Shanghai Municipal Education Commission (Grant No.J50104)
文摘Face recognition provides a natural visual interface for human computer interaction （HCI） applications. The process of face recognition, however, is inhibited by variations in the appearance of face images caused by changes in lighting, expression, viewpoint, aging and introduction of occlusion. Although various algorithms have been presented for face recognition, face recognition is still a very challenging topic. A novel approach of real time face recognition for HCI is proposed in the paper. In view of the limits of the popular approaches to foreground segmentation, wavelet multi-scale transform based background subtraction is developed to extract foreground objects. The optimal selection of the threshold is automatically determined, which does not require any complex supervised training or manual experimental calibration. A robust real time face recognition algorithm is presented, which combines the projection matrixes without iteration and kernel Fisher discriminant analysis （KFDA） to overcome some difficulties existing in the real face recognition. Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments. The proposed algorithm can also be applied to the video image sequences of natural HCI.
