Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

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.

Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.

Improving Students’Participation and Collaboration With Adjusting Cloud Education Platform During the Real-Time Interactive Class

The purpose of this study was to find a way to promote the collaboration and interaction of students and bring about the growth of learners through feedback while taking advantage of real-time interactive class via video conferencing tools.Although real-time interactive class with using video conferencing tools had great advantages,but there were also limitations of active interaction.To this end,real-time interactive tool and cloud-based educational platform were applied to create cases of learner participation classes and analyze the cases.The convergence of real-time interactive class tools and cloud tools has been able to draw students’participation and collaboration in non-face-to-face situations,and it can be seen that it is very helpful in creating learner-centered educational activities based on communication and interaction with students.Through this,the application of the cloud-based educational platform in real-time interactive class could lead students to participate and collaborate even in non-face-to-face situations.

Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real‑Time Gesture Interaction

In human-machine interaction,robotic hands are useful in many scenarios.To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction.Here,we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand.With a finger’s traction movement of flexion or extension,the sensor can induce positive/negative pulse signals.Through counting the pulses in unit time,the degree,speed,and direction of finger motion can be judged in realtime.The magnetic array plays an important role in generating the quantifiable pulses.The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway,respectively,thus improve the durability,low speed signal amplitude,and stability of the system.This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural,intuitive,and real-time human-robotic interaction.

Real-time forward modeling and inversion of logging-while-drilling electromagnetic measurements in horizontal wells

Based on the pseudo-analytical equation of electromagnetic log for layered formation,an optimal boundary match method is proposed to adaptively truncate the encountered formation structures.An efficient integral method is put forward to significantly accelerate the convergence of Sommerfeld integral.By asymptotically approximating and subtracting the first reflection/transmission waves from the scattered field,the new Sommerfeld integral method has addressed difficulties encountered by the traditional digital filtering method,such as low computational precision and limited operating range,and realized the acceleration of the computation speed of logging-while-drilling electromagnetic measurements(LWD EM).By making use of the priori information from the offset/pilot wells and interactively adjusting the formation model,the optimum initial guesses of the inversion model is determined in order to predict the nearby formation boundaries.The gradient optimization algorithm is developed and an interactive inversion system for the LWD EM data from the horizontal wells is established.The inverted results of field data demonstrated that the real-time interactive inversion method is capable of providing the accurate boundaries of layers around the wellbore from the LWD EM,and it will benefit the wellbore trajectory optimization and reservoir interpretation.

Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive simulations.CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are imperative.Despite ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems.To address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD processes.The HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision events.Extensive experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex models.The optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual systems.These findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

Gesture Recognition Based on Time-of-Flight Sensor and Residual Neural Network

With the advancement of technology and the increase in user demands, gesture recognition played a pivotal role in the field of human-computer interaction. Among various sensing devices, Time-of-Flight (ToF) sensors were widely applied due to their low cost. This paper explored the implementation of a human hand posture recognition system using ToF sensors and residual neural networks. Firstly, this paper reviewed the typical applications of human hand recognition. Secondly, this paper designed a hand gesture recognition system using a ToF sensor VL53L5. Subsequently, data preprocessing was conducted, followed by training the constructed residual neural network. Then, the recognition results were analyzed, indicating that gesture recognition based on the residual neural network achieved an accuracy of 98.5% in a 5-class classification scenario. Finally, the paper discussed existing issues and future research directions.

FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle.The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars.In this paper,the development of simulation model of extended Kalman filter(EKF)in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track.Due to concurrent in nature,the Xilinx®System-on-Chip Zynq Field Programmable Gate Array(FPGA)device is chosen to check the onboard estimation ofwheel-rail interaction parameters by using the National Instruments(NI)myRIO®development board.The NImyRIO®development board is flexible to deal with nonlinearities,uncertain changes,and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle operation.The simulated dataset of the railway nonlinear wheelsetmodel is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the vehicle.The proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on FPGA.The obtained simulation results are aligned with the simulation results obtained through MATLAB.To the best of our knowledge,this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional verification.The functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

Real-time control for fuel-optimal Moon landing based on an interactive deep reinforcement learning algorithm

In this study,a real-time optimal control approach is proposed using an interactive deep reinforcement learning algorithm for the Moon fuel-optimal landing problem.Considering the remote communication restrictions and environmental uncertainties,advanced landing control techniques are demanded to meet the high requirements of real-time performance and autonomy in the Moon landing missions.Deep reinforcement learning(DRL)algorithms have been recently developed for real-time optimal control but suffer the obstacles of slow convergence and difficult reward function design.To address these problems,a DRL algorithm is developed using an actor-indirect method architecture to achieve the optimal control of the Moon landing mission.In this DRL algorithm,an indirect method is employed to generate the optimal control actions for the deep neural network(DNN)learning,while the trained DNNs provide good initial guesses for the indirect method to promote the efficiency of training data generation.Through sufficient learning of the state-action relationship,the trained DNNs can approximate the optimal actions and steer the spacecraft to the target in real time.Additionally,a nonlinear feedback controller is developed to improve the terminal landing accuracy.Numerical simulations are given to verify the effectiveness of the proposed DRL algorithm and demonstrate the performance of the developed optimal landing controller.

A virtual 3D interactive painting method for Chinese calligraphy and painting based on real-time force feedback technology

A novel 3D interactive painting method for Chinese calligraphy and painting based on force feedback technology is proposed. The relationship between the force exerted on the brush and the resulting brush deformation is analyzed and a spring-mass model is used to build a model of the 3D Chinese brush. The 2D brush footprint between the brush and the plane of the paper or object is calculated according to the deformation of the 3D brush when force is exerted on the 3D brush. Then the 3D brush footprint is obtained by projecting the 2D brush footprint onto the surface of the 3D object in real time, and a complete 3D brushstroke is obtained by superimposing 3D brush footprints along the painting direction. The proposed method has been suc- cessfully applied in a virtual 3D interactive drawing system based on force feedback technology. In this system, users can paint 3D brushstrokes in real time with a Phantom Desktop haptic device, which can effectively serve as a virtual reality interface to the simulated painting environment for users.

Real-time interactive motion control of virtual human in virtual maintenance based on limited information

In order to provide a simple and efficient approach to perform the real-time interactive motion control of virtual human in virtual maintenance environment(VME),the motion control method of virtual human based on limited input information is proposed.With the space position tracking system with only one sensor the action sequences and motion models of virtual human,the human motions and hand actions in VME are driven by the sensor data in stages and in real time through the transmission condition control in the process of maintenance operation.And the input data and information is processed based on the method of Kalman filtering and wavelet transforming to improve the control effects.An experimental VME is also established to validate the control efficiency,and the experiment results show that the space motion control of virtual human in VME can be performed based on limited information with proposed control strategy.

An algorithm supporting fast scheduling and viewing of remote sensing images in embedded devices

In order to resolve the conflict between the limited resources of embedded devices and the growing amount of massive image data to be shown, a solution for fast images rendering in embedded devices is proposed and implemented. First, an improved algorithm of a multi-resolution file-pyramid construction which is used for the organization of massive image data is presented. Then, a strategy, adopting technologies such as view-dependent levels of detail, target-tiles quick search and tiles seamless connection, is presented for fast scheduling and viewing of images. The results show that compared with the solution of multi-scale image representations based on wavelet, the proposed solution can improve the rendering speed, and the rendering speed does not depend on the image size, though it increases some data storage space. And the proposed solution is suitable for embedded devices and friendly experience.

The IOCAS intermediate coupled model(IOCAS ICM) and its real-time predictions of the 2015–2016 El Nio event

The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model （ICM） is used at the Institute of Oceanology, Chinese Academy of Sciences （IOCAS）, named the IOCAS ICM, to predict the sea surface temper- ature （SST） evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer （Te） is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model＇s ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed.

Cross electro-nape-acupuncture ameliorates cerebral hemorrhageinduced brain damage by inhibiting necroptosis

BACKGROUND Receptor interacting protein kinase 1(RIPK1)-mediated cell death,including apoptosis and necroptosis,belongs to programmed cell death.It has been reported that RIPK1-mediated necroptosis exists in lesions of cerebral hemorrhage(CH).Electroacupuncture,a treatment derived from traditional Chinese medicine,could improve neurological impairment in patients with brain injury.AIM To investigate the protective role of cross electro-nape acupuncture(CENA)in CH,and clarify the potential mechanism.METHODS CH rat models were established,and CENA was applied to the experimental rats.Neurological functions and encephaledema were then measured.Necrotic cells in the brain of rats with CH were evaluated by propidium iodide staining.Necroptosis was assessed by immunofluorescence.Activation of the necroptosisrelated pathway was detected by western blot.Extraction of brain tissue,cerebrospinal fluid and serum samples was conducted to measure the expression and secretion of inflammatory cytokines by quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay.RESULTS The necroptotic marker p-MLKL was detectable in the brains of rats with CH.Next,we found that CENA could ameliorate neurological functions in rat models of CH.Moreover,the upregulation of RIPK1-mediated necroptosis-related molecules in the brains of rats with CH were inhibited by CENA.Further investigation revealed that CENA partially blocked the interaction between RIPK1 and RIPK3.Finally,in vivo assays showed that CENA decreased the expression of the inflammatory cytokines tumor necrosis factor-α,interleukin-6 and interleukin-8 in CH rat models.CONCLUSION These findings revealed that CENA exerts a protective role in CH models by inhibiting RIPK1-mediated necroptosis.

Research on Enhancing the Functions of Animation in Web 3D

VRML offers powerful tool for generating 3D scene and realizing real time interactive animation on Web. This paper briefly introduces the related techniques of implementing interactive animation in Web 3D, focusing on how to use JavaScript to create Script node for extending VRML functions. This is very useful for virtual product design, product performance simulation, virtual assembly and remote education.

Efficient Approach for Monitoring and Controlling Water Parameters Utilizing Integrated Treatment Based on WSNs

Research works of Wireless Sensor Networks (WSNs) applications and its constraints solutions occupy wide area around the world and attract many researchers. In this paper, an important one of environmental WSN applications is presented that is the water monitoring applications. An efficient approach for monitoring and controlling water parameters in real-time is implemented utilizing merging between WSN and designed simple workstation. For implementation simplicity, two water parameters (pH and temperature) are monitored and controlled in the proposed approach. Most of past work of water monitoring presented different proposed monitoring scenarios for different water parameters only. This research work utilizes the concept of interactive WSN nodes. The interactive nodes interact with the monitored water parameters to control its value. In the base station, the collected data is analyzed and the real-time value of the monitored parameters appears on the designed Graphic User Interface (GUI). The GUI is designed using the Matlab program. Through the GUI, the operator can switch the control between automatic and manual. ZigBee module is used for implementing the wireless communications between the nodes and the workstation. Due to the cost and simplicity, two sensors only are used in the proposed approach. Different real-time experiments are performed to test and measure the effectiveness and performance of the presented approach. These experiments reveal that the presented approach is effective for water treatment and efficient more than the past proposed water monitoring scenarios.

Visualization aided system of hydropower engineering management

For the purpose of realizing the information visualization of hydropower engineering management, we construeted three kinds of graphics models sorted by hierarchy for system modelling, employed the construction simulation system to simulate the real-time construction behaviours, introduced the graphics rendering system to organize and update the virtual scene, and designed the interaction system to respond to the user-initiated and simulation-initiated events. So, the real-time, interactive visualization aided system of hydropower engineering management is developed. Eventually, the effectiveness and capabilities of the system are showed through the application examples in China.

Key Technology in Developing Web-Based Engineering Drawing CAI Software

Key techniques to improve the quality of developing Web-based engineering drawing CAI software are discussed and some experience in applying commercial tools for generating vector drawing, concise representation of 3D solids, real-time interactive animation, data management etc. is illustrated. A Web-based Engineering Drawing CAI software 'Solid Projection' has been implemented by using these techniques.

View-point Control for Walk-through in Internet Environment

Techniques of Viewpoint-binding, interactive Viewpoint-animation interaction and their realization with VRML2 are illustrated

Interactive operation of physically-based slender flexible parts in an augmented reality environment

In order to deal with the problems of laying and assembly planning of slender flexible parts in electromechanical products,a novel approach to operate the physically-based slender flexible parts in an augmented reality environment is presented in this paper.A discrete dynamic method is used to efficiently build the physical model of slender flexible parts,which is very well suited for interactive operation in the augmented reality environment.In this model,bending penalty force can be calculated by the bending energy function to improve dynamic bending behavior,and a penalty method is used to simplify the calculation of geometric torsion.With a reasonable construction of augmented reality environment,a real-time interactive algorithm based on the operating panel is proposed to enable users to interact with the virtual slender flexible parts in the mixed reality-based scene.A case study in the augmented reality environment shows that the proposed approach is efficient and feasible.