In order to accurately sort the impurities and defective materials in the raw Chinese medicinal materials,an improved YOLOv6 algorithm for Chinese medicinal materials sorting is proposed to solve the difficult detection of the materials with inconspicuous defective feature.First,based on the characteristics of medicinal materials,the redundant large target detection head of the detection network is cut to reduce false detections;Then,the SPD convolution is introduced instead of strided convolution for image downsampling to enhance the ability to extract fine grained features.Finally,the coordinate attention mechanism is introduced in the network to improve the attention of important features.The experiments are conducted based on the astragalus dataset.The results show that the mAP of the improved YOLOv6 algorithm is 86.2%,which is 2.9%higher than the original algorithm and has the stronger detection ability for small defective medicinal materials.
With the advancement of urbanization,the traffic situation in cities has become increasingly congested,and how to dispatch and manage the traffic flow has become an urgent problem to be solved.By designing an efficient and intelligent traffic control system,the problem of traffic congestion can be greatly reduced.However,at present,the traffic lights on most road sections are still timed based on specific schedules.This control method works well when the traffic flow is low,but it cannot meet the demand due to large traffic flow or changes in traffic conditions.Therefore,this article designs an intelligent traffic control system that collects traffic flow information,calculates the corresponding relationship between intersection traffic flow and passing time using the BP neural network control algorithm,and improves the algorithm model through independent learning and training of the system,thereby achieving the goal of intelligent adjustment of traffic flow.This system designs a control system model based on BP neural network for intelligent transportation,which predicts the passage time of various types of transportation vehicles.Through this design,the traffic light control system can be more intelligent,with certain economic and social benefits.
In this paper,Citespace uses the diffusion model as the title and the documents dated from 2012 to 2022 to conduct data analysis.It objectively analyzes the number of documents,countries,institutions,keywords,references and other aspects of the diffusion model documents,and obtains that the number of documents issued by the diffusion model has been on the rise,indicating that the research on the diffusion model has been a hot topic for scholars in recent years.Through the analysis of the distribution of countries and institutions,as well as the number of papers issued,it is found that China and the United States have more research on the diffusion model,and the lines between countries are closely connected,which indicates that the academic exchanges between countries on the diffusion model are more extensive,and the cooperation between institutions is also closer.Among them,the Chinese Academy of Sciences has the largest number of papers issued,while some universities and institutions in the United States have published more.Through the analysis of keyword co-occurrence,clustering,highlighted words and references,it can be seen that the diffusion model in 2012-2022 is a hot topic in the field of medical research.In combination with other clustering tagwords,it can be seen that the diffusion model is also widely studied in the ecological field,and in infectious diseases,machine learning is also widely favored by scholars.
Aiming at the problems of vehicle detection by YOLOv5 model in complex traffic scenarios,such as slow detection speed,serious error detection,and difficulty in small object recognition,a new model YOLOv5-Ours with fast model convergence speed and high target frame accuracy is proposed.Firstly,the Bidirectional Feature Pyramid network(BiFPN)structure is used to improve the recognition accuracy by using the fine-grained features of multi-scale small objects,so as to mine the fine-grained features of different images.Secondly,the composite structure of the Spatial Pyramid Pool Fast(SPPF)structure and the ELU activation function is used to achieve fast and accurate target detection.The experimental results show that,compared with other algorithms,the algorithm has faster speed,higher precision and good robustness.
Session recommendations were designed to predict the next item they will interact with based on a sequence of historical user behavior.How to deeply analyze the complex dependencies within the conversation sequence and accurately extract the potential preferences of users is a huge challenge in the design of the current conversation recommendation model.In view of this,a graph neural network session recommendation model(AMSR-GNN)combined with attention mechanism was proposed.Firstly,all session data was constructed as a graph,and the local embedding representation of nodes on the graph was obtained through the graph neural network.Secondly,the attention mechanism containing the noise filter was used to display and filter out the unimportant node representations to obtain the denoising-enhanced global embedding representation,and finally,the local embedding representation and global embedding representation of the item are considered by the prediction layer to generate personalized recommendations for users.
This article introduces the framework,core components,and operation mechanism of the Openstack platform.In the campus network training environment,it installs basic operation and maintenance and sets up the Openstack platform.Through the entire process of creating cloud hosts and precautions through the platform,it facilitates readers to understand the Openstack framework and conduct in-depth research on key technologies based on it.
"DSP technology and its application"is an important and highly practical professional core course for the electronic information specialty.It is usually equipped with corresponding experimental teaching to assist theoretical teaching,to combine theory with practice and improve the teaching effect.This paper designs a comprehensive experimental teaching case that integrates signal generation,acquisition,and processing based on the DSP chip.The purpose is to enable students to systematically understand the basic working principle of the DSP chip,establish the overall concept of the DSP system,improve hands-on practice,develop independent analysis and problem-solving skills,and enhance independent innovation awareness,to meet the needs of emerging engineering talent training.
The traditional teaching mode of electrical courses is no longer suitable for modern applied technical personnel training objectives and educational concepts,and many educators are constantly seeking new classroom education modes.The article explores the method of using advanced simulation software to optimize classroom teaching to change the traditional single lecture mode,and introduces diversified teaching methods from teaching design,theoretical derivation,simulation verification,etc.This teaching mode of combining theoretical teaching with simulation verification stimulates students'learning enthusiasm and enables them to master relevant theoretical knowledge from shallow to deep,thus improving their professional comprehensive The teaching mode of theoretical teaching combined with simulation verification stimulates students'enthusiasm to learn and enables them to grasp the relevant theoretical knowledge from the beginning to the end,thus improving their professional comprehensive quality.
In order to realize the teaching and learning mode that can not only give play to the leading role of teachers but also fully reflect the dominant position of students,the information technology is used to create a new ubiquitous learning environment of the course 3D modeling Technology.The teaching reform of this course is mainly implemented from three aspects:the application of digital platform,the construction of micro course teaching resources,and teaching evaluation and feedback.Teaching practice shows that ubiquitous learning environment can improve teaching efficiency and achieve effective teaching.
In this paper,a series of image preprocessing operations such as background subtraction,image mask and high pass filtering are performed on the captured flow field image of the regulating valve,and then the cross correlation algorithm and multi grid iteration algorithm are used to study the flow field of the captured image.The results show that the overall flow field photographed is consistent with the theoretical trend.The upstream flow channel,the top of the valve core head and the valve seat wall are low speed flow areas,and the rest are high speed flow areas.With this algorithm,the observed flow field can be calculated in a short time,which avoids the disassembly of traditional sensors and greatly shortens the measurement time.
Aiming at the problem that the two lines of sight corresponding to the same marker in a stereoscopic X-ray fluoroscopic stereo image do not strictly intersect with each other,resulting in the inability to accurately reconstruct the markers,this paper proposes a two-stage marker three dimensional(3D)reconstruction method based on convex optimization from coarse to fine.First,3D coarse reconstruction of the markers from two X-ray images acquired at intervals is performed using the traditional direct linear transformation method;then,the 3D reconstruction optimization problem is transformed into a convex optimization problem by combining the linear projection model with bipolar constraints.Reconstruction experiments were performed on simulated stent-graft marker data and real X-ray stent-graft marker images.The results demonstrate that the proposed method obtained better results than the conventional reconstruction methods.
In order to improve the efficiency of blood cell detection,an improved blood cell target detection algorithm based on the RetinaNet model is proposed.First,the SE attention mechanism is embedded in the residual network and the feature pyramid network,so that the neural network focuses on the channel associated with the cell feature;secondly,the generalized intersection-over-union ratio(GIoU)is used instead of the original Intersection over Union(IoU)to obtain a more accurate prediction box.The experimental results show that compared with the original RetinaNet algorithm,the mAP has increased by 0.593 percentage points,and the AR has increased by 2.170 percentage points.
The construction industry involves multiple participants with complex cooperation relationships.There are many participants in the construction industry,and the cooperation relationship is mixed.How to design blockchain architecture for the construction industry in this situation with complex and project-oriented cooperative relationships is an urgent problem to be solved.Compared with traditional contracts,smart contracts based on blockchain technology have many advantages such as decentralization,immutable,verifiable and self-mandatory,which can effectively addresssolve the drawbacks of high execution cost,low operating efficiency and difficult dispute resolution in the process of construction project performance.This research study will study blockchain technology and smart contract technology,get through project progress,contracts,data and other data,and develop and provide intelligent project management cloud platform with multi-party participation and collaboration,so as to improve the efficiency of project execution.
In order to improve the level and quality of online and offline mixed teaching of ideological and political courses in colleges and universities in the era of integrated media,we must strictly follow the scientific and reasonable principle of online and offline mixed teaching of ideological and political courses in colleges and universities in the era of integrated media on the basis of a comprehensive analysis of relevant concepts and theories,adopt multiple effective teaching methods,and truly realize the combination and integration of online and offline ideological and political courses in colleges and universities.
Aiming at the problems of low emphasis,separation between theory and practice,insufficient hardware equipment,and less innovative teaching content in the traditional teaching mode of the edge computing course,combining the characteristics of online and offline hybrid teaching,putting forward the teaching method of"Learning online,Learning offline",expounding the overall teaching process design,high-quality resource construction scheme,and multi-dimensional assessment and evaluation mechanism of the mixed teaching mode,analyzing and explain the teaching achievements and characteristics.
In order to actively respond to the digital,intelligent enabling economic and social development of the demand for talents.Taking the teaching reform of the School of Information Engineering in Xuzhou Polytechnic of Industry as an example,this paper puts forward a"3D 12 elements"model of vocational competence around the improvement of students'vocational competence.Reconstructed the curriculum system of"platform sharing,direction separation,expansion of mutual selection,dual integration";The new mixed teaching model of"industry-oriented,education and training combined with solid foundation and strong skills,competent for the post"has been constructed.Adhere to the student-centered,use AI technology,build ubiquitous learning resources,and achieve timely feedback and accurate teaching;Data-driven innovation of the value-added evaluation system of"multi-subject,multi-method and multi-dimension"has improved the training quality of professional talents and students.
Wall cleaning is a kind of high-altitude operation,which can not only clean the city appearance,but also improve people's working environment.It is generally carried out manually,which has great potential safety hazards.Therefore,the research of wall cleaning robot is very necessary,and its comprehensive application in work production has become an inevitable trend.The structural design of a simple and efficient wall cleaning robot is discussed in this paper,Its main body includes cleaning device,adsorption device,walking mechanism and transmission mechanism.The robot can be used for smooth and flat wall surfaces such as glass and ceramics.By means of vacuum adsorption,it is driven by air cylinder and moves with the alternative adsorption of multiple suction cups.The combined cleaning scheme of disc brush,nozzle and scraper is adopted to clean the wall surface of high-rise buildings.It has the advantages of strong adsorption ability,good movement performance,good cleaning effect and light body load,etc.
In order to achieve the fundamental goal of cultivating talents in colleges and universities of"cultivating people by virtue and cultivating people by casting souls",the paper deeply excavates the thought of casting souls and educating people contained in the knowledge points in the course of computer network.Then,the paper realizes the organic integration of knowledge points in each chapter and ideological and political elements,and designs the specific implementation scheme and teaching comprehensive evaluation method of ideological and political education in the course of computer network.Practice shows that students'enthusiasm for learning has been significantly improved,and extracurricular expansion of professional knowledge has been significantly enhanced.Students are enthusiastic about participating in college students'innovation and entrepreneurship activities.At the same time,the students'sense of professional identity and social responsibility is growing,which lays a solid foundation for the cultivation of high-quality and versatile talents required by society.
Based on the characteristics of learning situation,this paper analyzes the problems existing in traditional offline teaching,meets the requirements of national first-class undergraduate course construction standards and graduation requirements,gives the online and offline hybrid teaching scheme of this course from the aspects of teaching content reconstruction,organizational form optimization,assessment methods,etc.,and finally illustrates the effect of mixed teaching through practice.
In view of the fact that the fall detection model cannot meet the requirement of lightweight,a lightweight and high-precision fall detection method for the elderly based on YOLOv5s improvement is proposed.Firstly,the lightweight network MobileNetV3 small is used to replace the backbone network of YOLOv5s,reducing the calculation amount and size of the model;Then replace the SE attention mechanism in MobileNetV3 small with CoordAttention;The convolution of the Neck part is changed to GSConv.The size of the improved model is reduced from 14.5MB to 2.3MB,and the mAP is 95.9%.The results show that the improved lightweight network can meet the requirements of high precision and lightweight of the elderly fall detection model.
