Over-Constraints and a Unified Mobility Method for General Spatial Mechanisms Part 2:Application of the Principle

The pre-research on mobility analysis presented a unified-mobility formula and a methodology based on reciprocal screw theory by HUANG, which focused on classical and modem parallel mechanisms. However its range of application needs to further extend to general multi-loop spatial mechanism. This kind of mechanism is not only more complex in structure but also with strong motion coupling among loops, making the mobility analysis even more complicated, and the relevant research has long been ignored. It is focused on how to apply the new principle for general spatial mechanism to those various multi-loop spatial mechanisms, and some new meaningful knowledge is further found. Several typical examples of the genera/multi-loop spatial mechanisms with motion couple even strong motion couple are considered. These spatial mechanisms include different closing way： over-constraint appearing in rigid closure, in movable closure, and in dynamic closure as well; these examples also include two different new methods to solve this kind of issue： the way to recognize over-constraints by analyzing relative movement between two connected links and by constructing a virtual loop to recognize over-constraints. In addition, over-constraint determination tabulation is brought to analyze the motion couple. The researches above are all based upon the screw theory. All these multi-loop spatial mechanisms with different kinds of structures can completely be solved by following the directions and examples, and the new mobility theory based on the screw theory is also proved to be valid. This study not only enriches and develops the theory and makes the theory more universal, but also has a special meaning for innovation in mechanical engineering.

Lightweight Cross-Modal Multispectral Pedestrian Detection Based on Spatial Reweighted Attention Mechanism

Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the weighted feature data across different modalities, thereby reducing the interference of multi-modal features. Subsequently, lightweight modules with depthwise separable convolution are incorporated to reduce the model’s parameter count and computational load through channel-wise and point-wise convolutions. The network model algorithm proposed in this paper was experimentally validated on the publicly available KAIST dataset and compared with other existing methods. The experimental results demonstrate that our approach achieves favorable performance in various complex environments, affirming the effectiveness of the multispectral pedestrian detection technology proposed in this paper.

Analysis and optimal synthesis of single loop spatial mechanisms

In this work, a systematic approach is presented to obtain the input-output equations of a single loop 4-bar spatial mechanisms. The dialytic method along with Denavit-Hartenberg parameters can be used to obtain these equations efficiently. A genetic algorithm （GA） has been used to solve the problem of spatial mechanisms synthesis. Two types of mechanisms, e.g., RSCR and RSPC （R： revolute; S： spherical; C： cylindrical; P： prismatic）, have illustrated the application of the GA to solve the problem of function generation and path generation. In some cases, the GA method becomes trapped in a local minimum. A combined GA-fuzzy logic （GA-FL） method is then used to improve the final result. The results show that GAs, combined with an adequate description of the mechanism, are well suited for spatial mechanism synthesis problems and have neither difficulties inherent to the choice of the initial feasible guess, nor a problem of convergence, as it is the case for deterministic methods.

Type Synthesis of Spatial Straight Line Mechanisms with only Revolute Joints

Spatial straight line mechanisms are a class of spatial mechanisms whose end-effectors generate the trajectory with the form of exact straight lines, which have potential applications in many industrial sectors. This study aims to synthesis the spatial straight line mechanisms with only revolute joints, meaning that no prismatic joints are included. According to the generalized function sets and the law of one dimensional rotation, the type of compositions of characteristic and the corresponding conditions are derived. Furthermore, some novel symmetrical and asymmetrical spatial straight line mechanisms are synthesized through assembling specific kinematic chains under the corresponding conditions. Finally, several synthesized spatial straight line mechanisms are illustrated to show the effectiveness of the synthesis methodology.

A Deepfake Detection Algorithm Based on Fourier Transform of Biological Signal

Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal threats.Although current deepfake generators strive for high realism in visual effects,they do not replicate biometric signals indicative of cardiac activity.Addressing this gap,many researchers have developed detection methods focusing on biometric characteristics.These methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography(rPPG)signal,resulting in high detection accuracy.However,in the spectral analysis,existing approaches often only consider the power spectral density and neglect the amplitude spectrum—both crucial for assessing cardiac activity.We introduce a novel method that extracts rPPG signals from multiple regions of interest through remote photoplethysmography and processes them using Fast Fourier Transform(FFT).The resultant time-frequency domain signal samples are organized into matrices to create Matrix Visualization Heatmaps(MVHM),which are then utilized to train an image classification network.Additionally,we explored various combinations of time-frequency domain representations of rPPG signals and the impact of attention mechanisms.Our experimental results show that our algorithm achieves a remarkable detection accuracy of 99.22%in identifying fake videos,significantly outperforming mainstream algorithms and demonstrating the effectiveness of Fourier Transform and attention mechanisms in detecting fake faces.

Perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.

Dynamic Modeling and Analysis of 4UPS-UPU Spatial Parallel Mechanism with Spherical Clearance Joint

Clearance between the moving joints is unavoidable in real working process. At present, many researches are mainly focused on dynamics of plane revolute joint in plane mechanism, but few on dynamics of spatial spherical joint clearance in spatial parallel mechanism. In this paper, a general method is proposed for establishing dynamic equations of spatial parallel mechanism with spatial spherical clearance by Lagrange multiplier method. The kinematic model and contact force model of the spherical joint clearance were established successively. Lagrange multiplier method was used to deduce the dynamics equation of 4 UPS-UPU mechanism with spherical clearance joint systematically. The influence of friction coefficient on dynamics response of 4 UPS-UPU mechanism with spherical clearance joint was analyzed. Non-linear characteristics of clearance joint and moving platform were analyzed by Poincare map, phase diagram, and bifurcation diagram. The results show that variation of friction coefficient and clearance value had little effect on stability of the mechanism, but the chaotic phenomenon was found at spherical clearance joint. The research has theoretical guiding significance for improving the dynamic performance and avoiding of chaos of parallel mechanisms including spherical joint clearance.

Simulation and Analysis of Spatial Weft Insertion Mechanism Considering Flexibility and Clearance

A 3D model of the spatial four-bar weft insertion mechanism was built with unigraphics NX(UG) according to the actual requirement,and dynamics simulation was carried out by importing the model into ADAMS.Without considering the clearance,the motion characteristic curve of the sword belt was generated through ADAMS combined with MATLAB.In this paper the hinge between the rod and the sector gear was selected as an example with different values of clearance,outputting the motion characteristic curve of the sword belt.Finite element analysis(FEA)was conducted,the flexible body was generated by importing the forked frame into ANSYS,and flexible dynamics simulation was carried out by importing the flexible body into ADAMS to replace the rigid rod.A comprehensive comparison of the output characteristics of the sword belt was conducted in the consideration of the clearance or flexible.Analysis of the force on the left hinge of the rod was carried out with the ADAMS post processing module.With the same clearance,considering the flexibility,amplitude of fluctuation of the force on the hinge increased obviously.

KINEMATIC ANALYSIS OF THE GENERAL SPATIAL 7R MECHANISM

The displacement, velocity and acceleration analysis of the general spatial 7R mechanism is discussed in this paper, fused on the method proposed in Ref. [2], an input-output algebra equation of the 16th degree in the tan-half-angle of the output angular displacement is derived. The derivation process and computation are considerably simple. A program written in Allanguage is used to derive the coefficients of displacement equations: therefore the amount of manual work is greatly decreased. The results are verified by a numerical example. The researches of this paper and Ref. [5]found a base for establishing an expert system of spatial mechanism analysis in the future.

Dynamic Modeling of Variable Stiffness and Damping for Spatial Linkage Weft Insertion Mechanism with Clearance

In order to further analyze the influence of clearance on the kinematic performance of spatial linkage weft insertion mechanism,it is necessary to study the dynamic characteristics of contact impact force model with the variable stiffness and damping coefficient.Firstly,the parameters in the output process of the system are solved by describing of the flexible joint clearance.Then,based on Lankarani-Nikravesh contact force model,the contact impact stiffness and damping coefficient is modified from fixed values to time-varying coefficients.The dynamic model of spatial linkage weft insertion mechanism with modified clearance is established by Lagrange method,and the dynamic characteristics of the system are calculated.The results show that the joint clearance can directly affect the output performance of the mechanism.With the increase of the clearance value,the curve fluctuations of acceleration,driving torque and collision force are obvious,and it will be further intensified with the increase of spindle speed,which greatly affects the stability of mechanism and fabric quality.Finally,the virtual prototype is established by the SolidWorks software and simulated by the ADAMS software.The simulation results are compared with the numerical results,which verifies the accuracy of the modeling method in this paper.

VELOCITY ANALYSIS OF A SPATIALM ECHANISM USING THE PRINCIPLEOF VIRTUAL FORCES

A new method of both analysis and graphics is presented for solving the problem of velocity analysis of a spatial four-bar mechanism. Central to the method is how to use the principle of virtual forces equilibrium system connected with the principle of virtual velocity to solve the velocity analysis of a mechanism. The method is accurate in principle and much simpler than the conventional method. It can be applied to both planar and spatial mechanisms. For brevity an example of a spatial mechanism only is presented.

Improved Blending Attention Mechanism in Visual Question Answering

Visual question answering(VQA)has attracted more and more attention in computer vision and natural language processing.Scholars are committed to studying how to better integrate image features and text features to achieve better results in VQA tasks.Analysis of all features may cause information redundancy and heavy computational burden.Attention mechanism is a wise way to solve this problem.However,using single attention mechanism may cause incomplete concern of features.This paper improves the attention mechanism method and proposes a hybrid attention mechanism that combines the spatial attention mechanism method and the channel attention mechanism method.In the case that the attention mechanism will cause the loss of the original features,a small portion of image features were added as compensation.For the attention mechanism of text features,a selfattention mechanism was introduced,and the internal structural features of sentences were strengthened to improve the overall model.The results show that attention mechanism and feature compensation add 6.1%accuracy to multimodal low-rank bilinear pooling network.

SSD Real-Time Illegal Parking Detection Based on Contextual Information Transmission

With the improvement of the national economic level,the number of vehicles is still increasing year by year.According to the statistics of National Bureau of Statics,the number is approximately up to 327 million in China by the end of 2018,which makes urban traffic pressure continues to rise so that the negative impact of urban traffic order is growing.Illegal parking-the common problem in the field of transportation security is urgent to be solved and traditional methods to address it are mainly based on ground loop and manual supervision,which may miss detection and cost much manpower.Due to the rapidly developing deep learning sweeping the world in recent years,object detection methods relying on background segmentation cannot meet the requirements of complex and various scenes on speed and precision.Thus,an improved Single Shot MultiBox Detector(SSD)based on deep learning is proposed in our study,we introduce attention mechanism by spatial transformer module which gives neural networks the ability to actively spatially transform feature maps and add contextual information transmission in specified layer.Finally,we found out the best connection layer in the detection model by repeated experiments especially for small objects and increased the precision by 1.5%than the baseline SSD without extra training cost.Meanwhile,we designed an illegal parking vehicle detection method by the improved SSD,reaching a high precision up to 97.3%and achieving a speed of 40FPS,superior to most of vehicle detection methods,will make contributions to relieving the negative impact of illegal parking.

All-organic covalent organic frameworks/perylene diimide urea polymer S-scheme photocatalyst for boosted H_(2) generation

Conjugated covalent organic frameworks(COFs)hold great promise in photocatalytic hydrogen evolution owing to their high crystallinity,large surface area,and distinct structure.However,COFs exhibit poor charge separation.Therefore,investigating highly effective COF-based photocatalysts is crucial.For the first time,conjugated COF/perylene diimide urea polymer(PUP)all-organic heterostructure with S-scheme interfacial charge-transfer channels was successfully developed and manufactured via in situ coupling of the two-dimensional triazine-based imine-linked COF(denoted as TATF-COF)with PUP.The optimal photocatalytic hydrogen-evolution rate of 94.5 mmol h^(-1) g^(-1) for TATF-COF/PUP is 3.5 times that of pure TATF-COF and is comparable to or even higher than that of the previously reported COF-based photocatalysts,resulting in an apparent quantum efficiency of up to 19.7%at 420 nm.The improved directional S-scheme charge transfer driven by the tuned built-in electric field and enhanced oxidation and reduction reaction rates of the photogenerated carriers contribute synergistically to the boosted photocatalytic H_(2) evolution.Experiments and theoretical studies reveal plausible H_(2) evolution and spatial S-scheme charge-separation mechanisms under visible-light irradiation.This study provides advanced methods for constructing all-organic S-scheme high-efficiency photocatalysts by the modulation of band structures.

Biped 4R2C Six-bar Mechanism with Inner and Outer Feet

Most current biped robots are equipped with two feet arranged in the right and left which inspired by the human body system. Different from the existing configurations, a novel biped robot with inner and outer feet based on a spatial six-bar 4R2C（R and C denote revolute and cylindric joints, respectively） mechanism is proposed. It can move along a line or a curve by three walking modes that are dwell adjustment mode, limit position adjustment mode and any position adjustment mode. Kinematic, gait planning and stability analyses are performed respectively, and a prototype is developed. Lastly, a potential application is considered and two manipulating modes（sphere and cylinder manipulating modes） are carried out. This interesting mechanism feathering its single dosed-chain structure and unique work performance is expected to motivate the configuration creation of biped robots.

Design and Gait Planning of a Worm-inspired Metameric Robot for Pipe Crawling

The earthworm has been attracted much attention in the research and development of biomimetic robots due to their unique locomotion mechanism,compact structure,and small motion space.This paper presents a new design and prototype of a worm-inspired metameric robot with a movement pattern similar to that of earthworms.The robot consists of multiple telescopic modules connected in series through joint modules.The telescopic module mimics the contraction and elongation motion modes of the earthworm segments.A kinematic and dynamic analysis is conducted on the telescopic module,and an input torque calculation method is provided to ensure sufficient friction between the robot and the pipe wall.The gait modes of the prototype robot for straight and turning locomotion are introduced,and these modes are extended to robots constructed by different numbers of telescopic modules.In addition,a method is proposed to increase the friction between the robot and the pipe wall in the aforementioned gait modes without changing the robot structure,thereby improving the robot’s motion ability in pipelines.The theoretical model of gait modes has also been validated through gait experiments.The findings of this paper would provide a useful basis for the design,modeling,and control of future worm inspired robots.

Anti-Occlusion Object Tracking Algorithm Based on Filter Prediction

Visual object tracking is an important issue that has received long-term attention in computer vision.The ability to effectively handle occlusion,especially severe occlusion,is an important aspect of evaluating the performance of object tracking algorithms in long-term tracking,and is of great significance to improving the robustness of object tracking algorithms.However,most object tracking algorithms lack a processing mechanism specifically for occlusion.In the case of occlusion,due to the lack of target information,it is necessary to predict the target position based on the motion trajectory.Kalman filtering and particle filtering can effectively predict the target motion state based on the historical motion information.A single object tracking method,called probabilistic discriminative model prediction(PrDiMP),is based on the spatial attention mechanism in complex scenes and occlusions.In order to improve the performance of PrDiMP,Kalman filtering,particle filtering and linear filtering are introduced.First,for the occlusion situation,Kalman filtering and particle filtering are respectively introduced to predict the object position,thereby replacing the detection result of the original tracking algorithm and stopping recursion of target model.Second,for detection-jump problem of similar objects in complex scenes,a linear filtering window is added.The evaluation results on the three datasets,including GOT-10k,UAV123 and LaSOT,and the visualization results on several videos,show that our algorithms have improved tracking performance under occlusion and the detection-jump is effectively suppressed.

A distributed EEMDN-SABiGRU model on Spark for passenger hotspot prediction

To address the imbalance problem between supply and demand for taxis and passengers,this paper proposes a distributed ensemble empirical mode decomposition with normalization of spatial attention mechanism based bi-directional gated recurrent unit(EEMDN-SABiGRU)model on Spark for accurate passenger hotspot prediction.It focuses on reducing blind cruising costs,improving carrying efficiency,and maximizing incomes.Specifically,the EEMDN method is put forward to process the passenger hotspot data in the grid to solve the problems of non-smooth sequences and the degradation of prediction accuracy caused by excessive numerical differences,while dealing with the eigenmodal EMD.Next,a spatial attention mechanism is constructed to capture the characteristics of passenger hotspots in each grid,taking passenger boarding and alighting hotspots as weights and emphasizing the spatial regularity of passengers in the grid.Furthermore,the bi-directional GRU algorithm is merged to deal with the problem that GRU can obtain only the forward information but ignores the backward information,to improve the accuracy of feature extraction.Finally,the accurate prediction of passenger hotspots is achieved based on the EEMDN-SABiGRU model using real-world taxi GPS trajectory data in the Spark parallel computing framework.The experimental results demonstrate that based on the four datasets in the 00-grid,compared with LSTM,EMDLSTM,EEMD-LSTM,GRU,EMD-GRU,EEMD-GRU,EMDN-GRU,CNN,and BP,the mean absolute percentage error,mean absolute error,root mean square error,and maximum error values of EEMDN-SABiGRU decrease by at least 43.18%,44.91%,55.04%,and 39.33%,respectively.