Web GIS Human-Machine Interactive Interface Design with VISI

The fusion of VlSI （visual identity system Internet）, digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.

Research on the Man-machine Interactive Environment VR and the Applications on Vocational Education and Training under the Perspective of Interactivity

In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.

Human-machine interactive streaming anomaly detection by online self-adaptive forest

At nomaly detectors are used to distinguish differences between normal and abnormal data,which are usually implemented by evaluating and ranking the anomaly scores of each instance.A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation.In real scenarios,anomaly detection often needs to be regulated by human feedback,which benefits adjusting anomaly detectors.In this paper,we propose a human-machine interactive streaming anomaly detection method,named ISPForest,which can be adaptively updated online under the guidance of human feedback.In particular,the feedback will be used to adjust the anomaly score calculation and structure of the detector,ideally attaining more accurate anomaly scores in the future.Our main contribution is to improve the tree-based streaming anomaly detection model that can be updated online from perspectives of anomaly score calculation and model structure.Our approach is instantiated for the powerful class of tree-based streaming anomaly detectors,and we conduct experiments on a range of benchmark datasets.The results demonstrate that the utility of incorporating feedback can improve the performance of anomaly detectors with a few human efforts.

Designing interactive glazing through an engineering psychology approach:Six augmented reality scenarios that envision future car human-machine interface

Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

ST-Map:an Interactive Map for Discovering Spatial and Temporal Patterns in Bibliographic Data

Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.

Deep Learning for EMG-based Human-Machine Interaction:A Review

Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.

Research on menu-typed man-machine interaction system of digital TIG welding machine

A digital man-machine interaction system controlled by communications between two processors of TMS320F240 and AT98C2051 was researched in the paper. The system is easy to set and modify welding process parameters by keyboards, and display information of welding site by LCD (Liquid Crystal Display). As one part of multi-task system about TIG welding machine, the coordination of man-machine interaction system with other tasks is the main point to the stability and reliability of its operation. Experiments result indicates that the system is stable, operation-flexible, high precision, and anti-interfering.

MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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.

The Creative Design Research of Product Appearance Based on Human-machine Interaction and Interface

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.

Design Method for Optimizing the Interactive Interface of Live Broadcasting Platform for the Elderly Users

In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interaction design mode used is still mainly based on the interaction mode for young groups,and is not designed for elderly users.Therefore,a design method for optimizing the interaction interface of live broadcasting platform for elderly users was proposed in this study.Firstly,the case study method and Delphi expert survey method were used to determine the design needs of elderly users and the design mode was analysed.Secondly,the orthogonal design principle was used to design a test sample of the interactive interface of live broadcasting platform applicable for the elderly users,and then a user evaluation system was established to calculate the weights of the design elements using hierarchical analysis,and then the predictive relationship between the design mode of the interactive interface of live broadcasting platform and the elderly users was established by Quantitative Theory I.Finally,Genetic Algorithm was applied to generate the optimized design scheme.The results showed that the design method based on the Genetic Algorithm and the combination of Quantitative Theory can scientifically and effectively optimize the design of the interactive interface of the live broadcasting platform for the elderly users,and improve the experience of the elderly users.

Study on the interactive deformation of bone needles and circum-pelvic soft tissue

During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic surgery.In this paper,a layered rig-id-flexible coupling model is proposed,and the needle-tissue interactive deformation under the load-ing is analyzed by the Rayleigh-Ritz method,in accordance with the principle of minimum potential energy.The pelvic musculoskeletal tissue is reversely reconstructed,and the structure of the bone is segmented into cancellous bone and cortical bone.The Mooney-Rivlin five-parameter hyperelastic model is used to simulate muscle,and the Ogden hyperelastic model is used to simulate adipose tis-sue.Finite element simulation is performed by loading different magnitudes of forces.The accuracy of the rigid-flexible coupling model is 0.432 mm,which indicates the correctness of the needle-tis-sue interactive deformation theory analysis.

The Application of Formative Assessment in Interactive Comprehensive English Classroom Teaching

Teaching evaluation is an important part of the teaching process of college English courses,and effective formative assessment can reflect the entire teaching process from multiple perspectives and ensure the smooth achievement of teaching objectives.Formative assessment is an assessment that runs through the entire learning process,based on humanism and constructivism,with various forms of evaluation.

基于Interactive Physics的物理习题教学--以2023年高考全国乙卷25题和湖北卷15题为例

在传统高中物理教学中,多过程碰撞的物理过程很难在板书上展现出来,成为教学的一大难点。基于Interactive Physics仿真功能,以2023年高考全国乙卷25题和湖北卷15题为例,将多过程碰撞的物理过程可视化,直观展现物理模型,帮助学生理解题目的复杂情境,有效缩短学习时间,提高教学质量和教学效率,实现最优化的教学目标。

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.

Research on fault time prediction method for high speed rail BTM unit based on multi method interactive validation

The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board train control system.To conduct fault prediction for the BTM unit based on actual fault data,this study proposes a prediction method combining reliability statistics and machine learning,and achieves the fusion of prediction results from different dimensions through multi-method interactive validation.Firstly,a method for predicting equipment fault time targeting batch equipment is introduced.This method utilizes reliability statistics to construct a model of the remaining faultless operating time distribution considering uncertainty,thereby predicting the remaining faultless operating probability of the BTM unit.Secondly,considering the complexity of the BTM unit’s fault mechanism,the small sample size of fault cases,and the potential presence of multiple fault features in fault text records,an individual-oriented fault prediction method based on Bayesian-optimized Gradient Boosting Regression Tree(Bayes-GBRT)is proposed.This method achieves better prediction results compared to linear regression algorithms and random forest regression algorithms,with an average absolute error of only 0.224 years for predicting the fault time of this type of equipment.Finally,a multi-method interactive validation approach is proposed,enabling the fusion and validation of multi-dimensional results.The results indicate that the predicted fault time and the actual fault time conform to a log-normal distribution,and the parameter estimation results are basically consistent,verifying the accuracy and effectiveness of the prediction results.The above research findings can provide technical support for the maintenance and modification of BTM units,effectively reducing maintenance costs and ensuring the safe operation of high-speed railway,thus having practical engineering value for preventive maintenance.

A Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller Model Combined with an Improved Particle Swarm Optimization Method for Fall Detection

In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.

Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

Exploration and Practice of“Guiding Interactive”Teaching in Advanced Geochemistry Courses from the Perspective of Constructivist Theory

The construction of geochemical disciplines has brought new vitality to the development of traditional geology.In the new round of“Double First-Class”discipline construction at Central South University,the course of Advanced Geochemistry has effectively stimulated students’interest in learning and further improved their scientific thinking and research innovation skills through the implementation of“Guiding Interactive”teaching reform measures,which has important theoretical significance and practical value.

Catalyst–Support Interaction in Polyaniline‑Supported Ni_(3)Fe Oxide to Boost Oxygen Evolution Activities for Rechargeable Zn‑Air Batteries

Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe oxide.It is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe oxide.Considering the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.