The classic OpenPose convolutional neural network model has excellent performance in the field of human posture *** it also has some shortcomings,such as poor accuracy and low accuracy of human posture detection *** i...
The classic OpenPose convolutional neural network model has excellent performance in the field of human posture *** it also has some shortcomings,such as poor accuracy and low accuracy of human posture detection *** improved OpenPose network model is proposed to solve these *** of all,the feature extraction network VGG-19 of OpenPose model is replaced by the residual network(ResNet) with residual learning structure to improve the training accuracy of the ***,at the same stage,the dual-branch parallel structure is changed to the single-branch serial structure to predict the part confidence maps(PCMs) and the part affinity fields(PAFs) of human joint ***,the structure of the convolution kernel is optimized and the residual network is *** accuracy of the algorithm is improved and the computational speed of the model is guaranteed as much as *** verification on MPII data sets shows that the detection accuracy of the improved algorithm model in this paper can reach 79.5%,which is 3.9% higher than the original *** the same time,it has a higher accuracy of detection compared with other human posture detection *** can be applied to human posture detection with a high pursuit of the accuracy of detection of the model,such as the field of intelligent driving and rehabilitation training and so on.
With the rapid development of virtual power plants, how to eliminate the negative impact of uncertainty on both sides of source and load on virtual power plants has become an urgent problem to be solved. In this paper...
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ISBN:
(数字)9798350390315
ISBN:
(纸本)9798350390322
With the rapid development of virtual power plants, how to eliminate the negative impact of uncertainty on both sides of source and load on virtual power plants has become an urgent problem to be solved. In this paper, a virtual power plant energy storage configuration method based on two-stage robust optimization is proposed to deal with the uncertainty of photovoltaic output and load demand. By constructing an uncertain set, the scheduling scheme of the system in the ‘worst’ scenario is optimized. The effectiveness and superiority of the method under different uncertainty conditions are verified by simulation analysis, which provides a reference for the configuration of energy storage capacity in the construction of virtual power plant.
We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the referen...
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ISBN:
(数字)9798350395440
ISBN:
(纸本)9798350395457
We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the reference as part of optimization variables of the resulting problem, where a deliberate sequence of errors is induced to obtain an optimal PID control action. In addition, the desired behavior of the PID controller is achieved without the need for internal modification of the PID gains. To better highlight the ability of coping with poor PID tuning, several test cases consisting of progressively degraded PID gains are presented. Validation of the proposed strategy is displayed by comprehensive simulations using two different plants.
Aiming at the problem that some detection networks have high accuracy but poor real-time performance and are not easy to deploy on embedded devices when used to intelligent vehicles,the method in this paper is *** it ...
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Aiming at the problem that some detection networks have high accuracy but poor real-time performance and are not easy to deploy on embedded devices when used to intelligent vehicles,the method in this paper is *** it solves the problem of global target tracking respectively and trajectory management in multi-objective ***'s an improved method for object detection and tracking based on the data fusion of lidar and *** this method,first,Yolov3 algorithm,which is accelerated by KCF algorithm,is used to recognize the object in the image *** cluster the point ***,align sensor data in time and ***,the object information of the two sensors is supplemented by the Hungarian algorithm *** then,the multi-frame matching is carried out through the key point matching count,and the multi-frame information is used for the object ***,the continuous motion trajectory of each object in the surrounding environment can be *** verification shows that the position detection error of this method is less than 5%,and the total processing time of a single frame is 154 *** with other methods,this method can significantly improve the processing speed,which is convenient to enhance the real-time data processing as a step of the perception module.
The problem of synchronization of heterogeneous processes in organizational systems is considered against the background of the transition of systems from a tectocentric to a holistic paradigm of their development. Th...
The problem of synchronization of heterogeneous processes in organizational systems is considered against the background of the transition of systems from a tectocentric to a holistic paradigm of their development. The process basis for the presentation of organizational systems in the conditions of “blurring” of their boundaries, taking into account the transition to a holistic paradigm, becomes a new basis for the development of organizational, system-technical and technological solutions for the creation and development of the material basis of organizational systems. The role and place of the process system in substantiating the directions of implementation of the strategy for the development of organizational systems and determining the overall structure of the material and technical basis of organizational systems is shown. The systematization and classification of heterogeneous processes in the life cycle of organizational systems is presented, the subject and objects of synchronization, the necessary and sufficient conditions for its implementation in organizational systems are determined. It is shown that synchronization at the process level in organizational systems should be carried out at the level of such attributes of related processes as outputs and inputs of processes, control actions and the necessary resources for the implementation of processes.
Chinese Train control System level 3 (CTCS-3) train control onboard equipment plays a crucial role in ensuring train safety and improving operational efficiency. And the on-board interface equipment enables the intera...
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ISBN:
(数字)9798350365221
ISBN:
(纸本)9798350365238
Chinese Train control System level 3 (CTCS-3) train control onboard equipment plays a crucial role in ensuring train safety and improving operational efficiency. And the on-board interface equipment enables the interaction between the on-board Automatic Train Protection (ATP), ground equipment, drivers, and trains. While its fault accounts for a relatively high proportion of faults, therefore, this paper proposed a fault diagnosis method for on-board interface equipment based on temporal knowledge graph completion. Firstly, this method introduces temporal series to integrate travel logs and fault statistics, which extract fault phenomena and perform entity alignment, construct the temporal knowledge graph. Secondly, on this basis, we constructed a fault diagnosis network based on knowledge graph completion, which incorporates the Temporal-Translating Embedding (T - TransE) vectorization algorithm, Bidirectional Long Short-Term Memory (Bi-LSTM), and Self-Attention (SA) mechanism for temporal feature extraction. Finally, the T - TransE vectorization model was pretrained using the on-board interface equipment fault data from a railroad station in recent years for selecting the most effective temporal integration method. In order to validate the superiority of the proposed fault diagnosis method and the effectiveness of the data combination method, the diagnostic network without data combination and temporal relationship introduction, and other common fault diagnostic networks, were tested using the on -board fault data. Compared with the following fault diagnosis methods, the model proposed in this paper achieved the highest fault diagnostic accuracy of 96.8%.
Abstract: The essence of aging is a decline in total vitality with age, being basic personal characteristics of human potential. Viability (v) is defined as the probability of surviving through 1 year. Mortality (m) i...
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Grid-forming devices can provide frequency and voltage support and are considered crucial components of future power systems. However, their process of power impact distribution for frequency support remains unclear. ...
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Recent discoveries have underscored the cross-talk between intestinal microbes and their ***,intestinal microbiota impacts the development,physiological function and social behavior of *** influence usually revolves a...
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Recent discoveries have underscored the cross-talk between intestinal microbes and their ***,intestinal microbiota impacts the development,physiological function and social behavior of *** influence usually revolves around the microbiota-gut-brain axis(MGBA).In tbis review,we firstly outline the impacts of the host on colonization of intestinal microorganisms,and then highlight the influence of intestinal microbiota on hosts focusing on short-chain fatty acid(SCFA)and tryptophan metabolite-mediated *** also discuss the intervention of intestinal microbial metabolism by dietary sup-plements,which may provide new strategies for improving the welfare and production of ***,we summarize a state-of-the-art theory that gut microbiome affects brain functions via metabolites from dietary macronutrients.
For robots and navigation systems, determining if a targeted location has been visited before is a challenging task by visual method. This paper presents a multi-scale vision loop closure detection algorithm that focu...
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For robots and navigation systems, determining if a targeted location has been visited before is a challenging task by visual method. This paper presents a multi-scale vision loop closure detection algorithm that focuses on establishing balance between limited computational resources and localization accuracy. It takes complementary advantages of both local and global descriptors. The extracted multi-scale features are highly robust to changes in illumination, appearance, viewpoint and occlusion. The intra-normalization combined with center adaptation approach improves the algorithm generalization. In addition, we design a new spatial scoring method called Offset Consistency Scoring. This method penalizes the relatively large spatial offsets in the matched positions, thus effectively measuring the consistency of the overall movement of the elements. Experiment results show our proposed algorithm have much lower computational complexity with similar accuracy performance compared to the state-of-the-art spatial scoring methods.
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