Comparative Study on the Digital Media Professional Personnel Training Models of China and Foreign Countries

In the current era of knowledge-based economy, digital media has become more and more important to the development of national economy, and also has gradually been the core power of the new pillar industries in a country. The training of digital media professionals has developed into one of important ways and methods for conforming to the trend of economic development and improving the national economic power. In this paper, the current situations of China＇ s current digital media professional personnel training model and other cotmtries＇ digital media professional personnel training model are comparatively analyzed for studying the characteristics of Chinese and foreign digital media professional personnel training models, absorbing the advanced, excellent digital media professional experience in personnel training model, and providing a reference for the training of the digital media professional personnel in China.

Comparative Analysis of Machine Learning Models for PDF Malware Detection:Evaluating Different Training and Testing Criteria

The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks.Portable Document Format(PDF)files have emerged as a major attack vector for malware due to their adaptability and wide usage.Detecting malware in PDF files is challenging due to its ability to include various harmful elements such as embedded scripts,exploits,and malicious URLs.This paper presents a comparative analysis of machine learning(ML)techniques,including Naive Bayes(NB),K-Nearest Neighbor(KNN),Average One Dependency Estimator(A1DE),RandomForest(RF),and SupportVectorMachine(SVM)forPDFmalware detection.The study utilizes a dataset obtained from the Canadian Institute for Cyber-security and employs different testing criteria,namely percentage splitting and 10-fold cross-validation.The performance of the techniques is evaluated using F1-score,precision,recall,and accuracy measures.The results indicate that KNNoutperforms other models,achieving an accuracy of 99.8599%using 10-fold cross-validation.The findings highlight the effectiveness of ML models in accurately detecting PDF malware and provide insights for developing robust systems to protect against malicious activities.

Comprehensive Evaluation of Talent Training Model for Modern Rehabilitation Therapy Technology:A Case Study of School Y

The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in School Y as the research subject,300 questionnaires were collected and the effective response rate was 92%.The strengths and weaknesses of the modern training model were analyzed through a mixed qualitative and quantitative research method.It was found that 68%of the students thought that the modern model had obvious advantages in practical teaching,but 42%of the students thought that it still needed to be improved in personalized teaching.This study provides an empirical basis and specific suggestions for optimizing the cultivation of rehabilitation therapy technology talents.

A Study on the Work Process-Based Practical Training Model for Basic Nursing Skills in Vocational Colleges

Objective:To explore and analyze the work process-based practical training teaching model for basic nursing skills in vocational colleges and its implementation effects.Methods:A total of 82 nursing students from our school were selected for the study,which was conducted from April 2023 to April 2024.Using a random number table method,the students were divided into an observation group and a control group,each with 41 students.The control group received conventional practical training teaching,while the observation group followed the work process-based practical training model for basic nursing skills.The assessment scores and teaching satisfaction of the two groups were compared.Results:The comparison of assessment scores showed that the observation group performed significantly better than the control group(P<0.05).The comparison of teaching satisfaction also indicated that the observation group had significantly higher satisfaction than the control group(P<0.05).Conclusion:The work process-based practical training teaching model for basic nursing skills in vocational colleges can improve students’assessment scores and enhance teaching satisfaction,demonstrating its value for wider application.

Training and Implementation of Subjective Questions Scoring System Based on the Baidu Qianfan Model Platform

Leveraging the Baidu Qianfan model platform,this paper designs and implements a highly efficient and accurate scoring system for subjective questions,focusing primarily on questions in the field of computer network technology.The system enhances the foundational model by utilizing Qianfan’s training tools and integrating advanced techniques,such as supervised fine-tuning.In the data preparation phase,a comprehensive collection of subjective data related to computer network technology is gathered,cleaned,and labeled.During model training and evaluation,optimal hyperparameters and tuning strategies are applied,resulting in a model capable of scoring with high accuracy.Evaluation results demonstrate that the proposed model performs well across multiple dimensions-content,expression,and development scores-yielding results comparable to those of manual scoring.

The Training Model and Development Route of Market-oriented Professional Farmers

To cultivate new professional farmers is a key way for rural labor development, resolving existing problems such as how to farming. It is notable that government and market take advantages in training of new professional farmers. Therefore, it is necessary to guarantee government and market playing the roles. The research explored market-oriented farmer training model and the characteristics and investigated training routes for new professional farmers.

基于ADDIE Training Model的高职英语课程教学实践与探索

加快发展现代高等职业教育,既有利于缓解当前就业压力,也是解决高技能人才短缺的战略之举。现代职场对有英语应用能力要求的岗位越来越多,一些专业技能强的学生由于无法满足用人单位在英语应用能力上的要求而与理想岗位失之交臂的情况时有发生。为改变这样的现状、提高学生的英语实际应用能力,开展基于ADDIE Training Model的高职英语课程教学实践与应用研究,并将试验效果与02O教学活动和传统的"讲授型"教学活动效果进行对比分析。

Interactive Training Model of TRIZ for Mechanical Engineers in China

Abstract： Innovation is a process of taking an original idea and converting it into a business value, in which the engineers face some inventive problems which can be solved hardly by experience. TRIZ, as a new theory for companies in China, provides both conceptual and procedural knowledge for finding and solving inventive problems. Because the government plays a leading role in the diffusion of TRIZ, too many companies from different industries are waiting to be trained, but the quantity of the trainers mastering TRIZ is incompatible with that requirement. In this context, to improve the training effect, an interactive training model of TRIZ for the mechanical engineers in China is developed and the implementation in the form of training classes is carried out. The training process is divided into 6 phases as follows： selecting engineers, training stage-l, finding problems, training stage-2, finding solutions and summing up. The government, TRIZ institutions and companies to join the programs interact during the process. The government initiates and monitors a project in form of a training class of TRIZ and selects companies to join the programs. Each selected companies choose a few engineers to join the class and supervises the training result. The TRIZ institutions design the training courses and carry out training curriculum. With the beginning of the class, an effective communication channel is established by means of interview, discussion face to face, E-mail, QQ and so on. After two years training practices, the results show that innovative abilities of the engineers to join and pass the final examinations increased distinctly, and most of companies joined the training class have taken congnizance of the power of TRIZ for product innovation. This research proposes an interactive training model of TRIZ for mechanical engineers in China to expedite the knowledge diffusion of TRIZ.

Research on Opportunity-Driven Redesign Process to Cooperate With Training Innovative Engineers in China

Many design engineers in cross-domain industries have attended training classes of TRIZ to improve their innovative abilities in China. Most of them are successful, but others are not. So the latest target of the trainers is to improve the training process used now in industry in China and to make the engineers to understand the basic principles of TRIZ better. Based on the mass-engineer-oriented training model(MEOTM) and mechanical engineers’ design cases, a relationship between managing activities about the opportunities for innovation and the training process is set up. It is shown that the inventive problems come first from opportunity searching for engineers. A training and gate system for evaluation is developed to involve the managing activities of the companies in the training process. Then comparison between the general analogous process and the application of TRIZ is made, which shows the advantages and depth principles of TRIZ for the engineers to apply them confidently. Lastly a new process is formed in which opportunity searching, engineers training, inventive problems identifying and solving,and three redesign paths are connected seamlessly. The research proposes an opportunity-driven redesign path that cooperates the training and opportunity searching, which will be applied in future training classes to make more and more engineers to follow.

Remote nursing training model combined with proceduralization in the intensive care unit dealing with patients with COVID-19

The shortage of personal protective equipment and lack of proper nursing training have been endangering health care workers dealing with coronavirus disease 2019(COVID-19).In our treatment center,the implementation of a holistic care model of time-sharing management for severe and critical COVID-19 patients has further aggravated the shortage of intensive care unit(ICU)professional nurses.Therefore,we developed a short-term specialized and targeted nursing training program to help ICU nurses to cope with stress and become more efficient,thus reducing the number of nurses required in the ICU.In order to avoid possible human-to-human spread,small teaching classes and remote training were applied.The procedural training mode included four steps:preparation,plan,implementation,and evaluation.An evaluation was conducted throughout the process of nursing training.In this study,we documented and shared experiences in transitioning from traditional face-to-face programs to remote combined with proceduralization nursing training mode from our daily work experiences during the COVID-19 pandemic,which has shown to be helpful for nurses working in the ICU.

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

Inquiry Training Model and Its Application in Teaching

Inquiry training model gives children directions to explore the new areas effectively which can help students develop the intellectual discipline and skills necessary to raise questions and search out answers stemming from their curiosity. Applying this model in teaching, process skills of the students can be improved, like observing, collecting, organizing data, identifying and controlling variables, formulating and testing hypotheses, and inferring. Besides, students will develop logical thinking and they will form the attitude that all knowledge is tentative.

Exploration of the Training Mode of School-enterprise Collaborative AI Innovative Talents Based on PaddlePaddle

This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innovation Center by enjoying the best of both UESTC and Baidu(China),and cooperating with 16 universities in Sichuan Province.With the support of this center,both the school and the enterprise successfully built a school-enterprise collaborative AI innovative talent training model,which mainly serves the universities,industries,and districts.Furthermore,this training model is able to facilitate the update of the industrial intelligence and the regional economic development in southwest China,and also provide a reference for deep integration of school-enterprise collaboration and the cultivation of innovative talents in electronic information fields.

Method to generate training samples for neural network used in target recognition

Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps：use computer and simulation software to build target object＇s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors＇ sequence.The vectors＇ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.

The Realistic Dilemma and Promoting Path of Secondary Vocational Education Talent Training Model under the Background of Education Supply-side Reform

In today's world,the competition for high-end smart technology is becoming increasingly fierce,and the huge connotation hidden behind the fierce competition is the competition of high-quality skilled talents.The status of secondary vocational education in our country's education system has a solid foundational role.The close connection it exhibits with social and economic development is beyond the reach of other types of education.However,the current secondary vocational education talent training model shows a situation that is not in line with market demand,and problems such as"shortage of skilled personnel"and"unemployment structural imbalance"have appeared in related fields.The supply of talents in secondary vocational education lacks a balanced mechanism,lacks in quality of supply,and does not have a high effect.It is urgent to train high-quality skilled talents with matching socio-economic structure transformation and upgrading for the society through education supply-side reform measures.In view of this,according to the changes in market demand,we will vigorously promote the reform of the school-based curriculum of secondary vocational schools,strive to create a new integrated development model that combines textbooks and practice,promote in-depth exchanges and cooperation between schools and characteristic enterprises in the industry,and train people in practice.Cultivating people,creating a good atmosphere for cultivating technical talents,and combining with the new goal of practicing education to build an evaluation system suitable for the growth of secondary vocational talents,making the human resource structure more and more suitable for the transformation and upgrading of the current social industrial structure.

New Equipment Training Based on Virtual-Real Fusion Training Model

In view of the phased development in college education,military training,and new equipment combat training,this paper proposes the virtual-real fusion training model of“five-in-one and step-by-step.”The five training modes,namely virtual panel training,immersive virtual training,physical(semi-physical)simulation training,training with equipped training equipment,and installation drill,are organically combined in the practical training of new equipment,which improves students' innovation consciousness and serviceability.

The Reform of the Talent Training Model for English Majors Based on OBE

Based on the reflection on the traditional teaching model of English majors,this paper points out that language teaching has long been divorced from the cultivation of cultural literacy and social needs;therefore,students’learning initiative has seriously deteriorated.On this basis,this study focuses on the“student-centered”notion and tries to integrate the four functions of language,which include“instrumental,”“cognitive,”“emotional,”and“literacy,”to establish a“four-three-two”teaching model,so as to explore an effective scheme for the teaching reform of English majors.

Exploration of Graduate Student Cultivation Mode of Landscape Architecture under the Background of“Artificial Intelligence+X”

Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.

A Support Data-Based Core-Set Selection Method for Signal Recognition

In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classifiers on large signal datasets with redundant samples requires significant memory and high costs.This paper proposes a support databased core-set selection method(SD)for signal recognition,aiming to screen a representative subset that approximates the large signal dataset.Specifically,this subset can be identified by employing the labeled information during the early stages of model training,as some training samples are labeled as supporting data frequently.This support data is crucial for model training and can be found using a border sample selector.Simulation results demonstrate that the SD method minimizes the impact on model recognition performance while reducing the dataset size,and outperforms five other state-of-the-art core-set selection methods when the fraction of training sample kept is less than or equal to 0.3 on the RML2016.04C dataset or 0.5 on the RML22 dataset.The SD method is particularly helpful for signal recognition tasks with limited memory and computing resources.

Optimizing Network Security via Ensemble Learning: A Nexus with Intrusion Detection

Network intrusion detection systems need to be updated due to the rise in cyber threats. In order to improve detection accuracy, this research presents a strong strategy that makes use of a stacked ensemble method, which combines the advantages of several machine learning models. The ensemble is made up of various base models, such as Decision Trees, K-Nearest Neighbors (KNN), Multi-Layer Perceptrons (MLP), and Naive Bayes, each of which offers a distinct perspective on the properties of the data. The research adheres to a methodical workflow that begins with thorough data preprocessing to guarantee the accuracy and applicability of the data. In order to extract useful attributes from network traffic data—which are essential for efficient model training—feature engineering is used. The ensemble approach combines these models by training a Logistic Regression model meta-learner on base model predictions. In addition to increasing prediction accuracy, this tiered approach helps get around the drawbacks that come with using individual models. High accuracy, precision, and recall are shown in the model’s evaluation of a network intrusion dataset, indicating the model’s efficacy in identifying malicious activity. Cross-validation is used to make sure the models are reliable and well-generalized to new, untested data. In addition to advancing cybersecurity, the research establishes a foundation for the implementation of flexible and scalable intrusion detection systems. This hybrid, stacked ensemble model has a lot of potential for improving cyberattack prevention, lowering the likelihood of cyberattacks, and offering a scalable solution that can be adjusted to meet new threats and technological advancements.