Research and Discussion on Flipped Classroom Combined with Case-Based Learning in Pharmacoeconomics Teaching

Objective:To explore the application effect of flipped classroom combined with case-based learning teaching methods in pharmacoeconomics teaching.Methods:The students majoring in clinical pharmacy in 2019 were selected as the study subjects,and the cost-effectiveness analysis of different dosage forms of Yinzhihuang in the treatment of neonatal jaundice was selected as the teaching case.The flipped classroom combined with case-based learning teaching method was used to carry out theoretical teaching to the students.After the course,questionnaires were distributed through the Sojump platform to evaluate the teaching effect.Results:The results of the questionnaire showed that 85.71%of the students believed that the flipped classroom combined with case-based learning teaching method was helpful in mobilizing the learning enthusiasm and initiative,and improving the comprehensive application ability of the knowledge of pharmacoeconomics.92.86%of the students think that it is conducive to the understanding and memorization of learning content,as well as the cultivation of teamwork,communication,etc.Conclusion:Flipped classroom combined with case-based learning teaching method can improve students’knowledge mastery,thinking skills,and practical application skills,as well as optimize and improve teachers’teaching levels.

Integration of Theory and Practice in Medical Morphology Curriculum in Postgraduate Training:A Flipped Classroom and Case-based Learning Exercise

Objective:The integration of training in theory and practice across the medical education spectrum is being encouraged to increase student understanding and skills in the sciences.This study aimed to determine the deciding factors that drive students'perceived advantages in class to improve precision education and the teaching model.Methods:A mixed strategy of an existing flipped classroom(FC)and a case-based learning(CBL)model was conducted in a medical morphology curriculum for 575 postgraduate students.The subjective learning evaluation of the individuals(learning time,engagement,study interest and concentration,and professional integration)was collected and analyzed after FC-CBL model learning.Results:The results from the general evaluation showed promising results of the medical morphology in the FC-CBL model.Students felt more engaged by instructors in person and benefited in terms of time-saving,flexible arrangements,and professional improvement.Our study contributed to the FC-CBL model in Research Design in postgraduate training in 4 categories:1)advancing a guideline of precision teaching according to individual characteristics;2)revealing whether a learning background is needed for a Research Design course to guide setting up a preliminary course;3)understanding the perceived advantages and their interfaces;and 4)barriers and/or improvement to implement the FC-CBL model in the Research Design class,such as a richer description of e-learning and hands-on practice.Conclusion:Undertaking a FC-CBL combined model could be a useful addition to pedagogy for medical morphology learning in postgraduate training.

State of the art in applications of machine learning in steelmaking process modeling

With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.

Hydraulic Circuit Design and Dynamic Learning Using Case-based Reasoning

This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.

Research on Compatible Mode of Self-directed Learning and Cooperative Learning in Blended Teaching of Basic English Course

In the information age,blended teaching,no matter online or offline,has become the mainstream of college teaching reform.In this teaching model,self-directed learning and cooperative learning are the two main learning approaches.On the online teaching platform,students mainly learn knowledge-based content by self-directed learning,while practising their language skills by cooperative learning in flipped classroom activities.On one hand,it advocates student-centered strategy so as to improve students autonomous learning ability;on the other hand,teachers serve as a guide to organize the classroom activities;meanwhile,they give timely feedback to students in order to promote students’learning ability.In blended teaching model,this mutually compatible and reinforcing model of self-directed learning and cooperative learning is undoubtedly helpful to improve the teaching efficiency.

Research on Federated Learning Data Sharing Scheme Based on Differential Privacy

To realize data sharing,and to fully use the data value,breaking the data island between institutions to realize data collaboration has become a new sharing mode.This paper proposed a distributed data security sharing scheme based on C/S communication mode,and constructed a federated learning architecture that uses differential privacy technology to protect training parameters.Clients do not need to share local data,and they only need to upload the trained model parameters to achieve data sharing.In the process of training,a distributed parameter update mechanism is introduced.The server is mainly responsible for issuing training commands and parameters,and aggregating the local model parameters uploaded by the clients.The client mainly uses the stochastic gradient descent algorithm for gradient trimming,updates,and transmits the trained model parameters back to the server after differential processing.To test the performance of the scheme,in the application scenario where many medical institutions jointly train the disease detection system,the model is tested from multiple perspectives by taking medical data as an example.From the testing results,we can know that for this specific test dataset,when the parameters are properly configured,the lowest prediction accuracy rate is 90.261%and the highest accuracy rate is up to 94.352.It shows that the performance of the model is good.The results also show that this scheme realizes data sharing while protecting data privacy,completes accurate prediction of diseases,and has a good effect.

Deep‐learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency

During the last decades the whispering gallery mode based sensors have become a prominent solution for label-free sensing of various physical and chemical parameters.At the same time,the widespread utilization of the approach is hindered by the restricted applicability of the known configurations for ambient variations quantification outside the laboratory conditions and their low affordability,where necessity on the spectrally-resolved data collection is among the main limiting factors.In this paper we demonstrate the first realization of an affordable whispering gallery mode sensor powered by deep learning and multi-resonator imaging at a fixed frequency.It has been shown that the approach enables refractive index unit(RIU)prediction with an absolute error at 3×10^(-6) level for dynamic range of the RIU variations from 0 to 2×10^(-3) with temporal resolution of several milliseconds and instrument-driven detection limit of 3×10−5.High sensing accuracy together with instrumental affordability and production simplicity places the reported detector among the most cost-effective realizations of the whispering gallery mode approach.The proposed solution is expected to have a great impact on the shift of the whole sensing paradigm away from the model-based and to the flexible self-learning solutions.

Research on the Construction of English Autonomous Learning Monitoring Mode under the Background of Big Data

The era of big data is coming,the combination of big data and traditional teaching can provide more and more accurate services for students'self-learning,and it is a good way to teach students according to their aptitude.In this background,a learning society is coming,which aiming at learning,autonomous learning and lifelong learning.Learning society emphasize the ability of learning autonomy for students unprecedentedly.Learning is no longer limited to the campus.Learning ability will accompany learners'social life and become an active and healthy lifelong activity.Autonomous learning is a learning theory that goes with the requirements of The Times and has a broad development prospect.The study of Autonomous learning not only has a very important guiding significance for the educational and teaching practice in China,but also plays an important role in the life development of every student.The subject of learning is gradually transferred from the classroom,teachers and textbooks to the students themselves.Teachers should not only impart knowledge and answer questions,but also,most importantly,teach students how to exert their autonomy in autonomous learning.After investigating and researching the existing monitoring model of autonomous English learning in colleges and universities,our group found that in practice,there is a lack of corresponding monitoring mechanisms and means,and autonomous learning has gradually become formalized.Therefore,according to the actual situation of autonomous English learning in our country's universities,the monitoring model of autonomous English learning has been reconstructed,and an effective comprehensive evaluation system has been established to effectively improve students'English learning ability.

Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties.The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller(MFISMC).A position controller is designed based on adaptive sliding mode control(SMC)to safely drive the aerial robot and ensure fast state convergence under external disturbances.Additionally,the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots.Then,the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state.Finally,to demonstrate the performance and robustness of the proposed control strategy,numerical simulations are carried out,which are also compared with other conventional strategies,such as proportional-integralderivative(PID),backstepping(BS),and SMC.The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

Innovative Research on the Blending Learning Mode of Econometrics

Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and the blending learning mode of various courses has blossomed everywhere.In this context,this paper used the Econometrics course as the carrier,analyzed the many unreasonable problems in the traditional Econometrics course,and proposed an optimization plan and path for the blending learning mode to address these problems.

LEARNS认知图式教育对乳腺癌MRI增强检查患者心理状态的影响

目的:探讨乳腺癌磁共振成像(MRI)增强扫描患者应用LEARNS模式下认知图式教育的效果。方法:以便利抽样法采集2023年1月31日-7月31日在某院接受MRI增强扫描检查的乳腺癌患者为对照组,2023年8月1日-2024年2月29日在该院接受MRI增强扫描检查的乳腺癌患者为研究组。对照组接受常规护理,研究组给予LEARNS模式下认知图式教育,对比两组心理状态、病耻感水平、应对方式、不良事件。结果:研究组坚韧性、力量性及乐观性及总分均高于对照组(t=50.575,44.798,19.077,86.704;P<0.001);研究组社会排斥、经济不安全感、内在羞耻感、社会隔离及总分均低于对照组(t=17.492,10.741,13.396,18.143,33.372;P<0.001);研究组简易应对方式问卷(SCSQ)中积极应对得分高于对照组、消极应对得分低于对照组(t=32.750,34.481;P<0.05);研究组不良事件发生率低于对照组(χ^(2)=6.093,P<0.05)。结论:在乳腺癌MRI增强扫描患者中应用LEARNS模式下认知图式教育有助于改善心理状态,降低患者病耻感水平,促进患者采用积极应对方式,并降低不良事件的发生率。

Research on Innovative Learning Based on Mixed Teaching Model of Data Structures

Under the premise of building an innovative country and cultivating innovative talents,teaching innovative learning,cultivating students’innovative thinking and improving the teaching mode and curriculum form have already become one of the main directions of deepening the reform of higher education.Data Structure is essential part in the undergraduate program.It is crucial for student to carry out research and project.In the actual teaching activities,the problems of content updating,practice ability for research projects of data structures are to be improved.Therefore,the course reform is imperative.This paper analyzed the main problems of the current data structures course,explored the solution of the problems,and proposed a new mixed teaching mode and evaluation method.

Analysis of the Application Value of Virtual Reality Combined with Flipped Classroom Teaching Mode in Cardiopulmonary Resuscitation Teaching

Objective:To analyze the value of using virtual reality combined with the flipped classroom teaching model in teaching cardiopulmonary resuscitation(CPR).Methods:Two classes of our nursing program were randomly selected for the study from September 2022 to September 2023,Class A(52 students,conventional teaching method)and Class B(52 students,virtual reality combined with flipped classroom teaching mode).The assessment scores and independent learning ability scores of the students in the two classes were compared.Results:CPR theory and operation scores,passing rate,and independent learning ability scores of Class B were higher than those of Class A(P<0.05).Conclusion:the use of virtual reality combined with the flipped classroom teaching mode in CPR teaching is conducive to the improvement of students’assessment scores and independent learning ability.

Designing Higher Vocational College English Blended Learning Mode based on Wechat Platform

As a platform bridging classroom teaching and online teaching for higher vocational college(HVC)English,WeChat expands the dimension of HVC English teaching.This paper first introduces basic functions and characteristics of WeChat,then analyzes problems existing in current HVC English teaching and finally puts forward specific ways to design HVC English blended learning mode based on WeChat platform in four steps:warming-up,text analysis,exercises and post-course expansion.

Construction of Chinese Learning Mode for Overseas Students in Higher Vocational Colleges under the Background of the Belt and Road Initiative

With the deepening of exchanges between China and other countries,especially the proposal of the Belt and Road Initiative,more and more foreign students come to China to study,putting forward higher requirements for the education and management of colleges and universities in China.In the process of implementing the strategy of"one belt and one road",language interaction is the basic prerequisite for achieving exchanges and cooperation among different countries.In the face of this situation,by analyzing the existing problems in the training of overseas students in higher vocational colleges in China under the background of"One Belt and One Road"strategy,in this paper,the construction of the Chinese learning mode for overseas students in higher vocational colleges was put forward,hoping to provide help for the training of overseas students and solve the problem of foreign students'language learning.

糖尿病肾病开展Triangle分层分级管理+LEARNS模式的效果及心理状态的观察

目的探究在对糖尿病肾病患者护理时开展Triangle分层分级管理+LEARNS模式对患者血糖水平、肾功能水平以及心理状态等改善作用。方法在2022年2月至2023年1月云南省第三人民医院收治糖尿病肾病患者中随机抽选74例为对象,Excel表随机排序划分对照组(n=37,治疗期间接受常规护理)和观察组(n=37,接受Triangle分层分级管理+LEARNS模式护理)。针对患者血压水平、肾功能水平等改善情况进行评估。结果对比2组干预前后血糖水平,餐后2 h血糖、空腹血糖,干预后观察组低于对照组,差异有统计学意义(P<0.05)。对比患者生存质量,干预前无差异,干预后观察组QOLIE-31量表评分高于对照组,差异有统计学意义(P<0.05)。对比患者负面情绪评分,干预前BAI以及BDI评分无差异,干预后观察组评分低于对照组,差异有统计学意义(P<0.05)。对比患者肾功能水平,干预后观察组肾功能水平高于对照组,差异有统计学意义(P<0.05)。对比2组自我管理能力,干预后观察组高于对照组,差异有统计学意义(P<0.05)。结论在对糖尿病肾病患者护理时开展Triangle分层分级管理+LEARNS模式,可改善患者血糖、肾功能水平,缓解患者治疗期间负面情绪,有助于患者进行恢复。

An Exploration of a New Running Mode of Equipment Management for Institutions of Higher Learning

With the great changes in China's economic mechanism, the present running modes of equipment management at most institutions of higher learning are becoming less and less effective and efficient. Being fully aware of the common problems and their characteristics, this paper proposes a new running mode which aims at these problems' permanent resolution. It involves (1) Systems such as renting, competition and paid services are to be introduced to the campus, in order to effectively associate duty with interest. (2) The present managerial pattern is to be replaced by a new running network, in which all the links cooperate with as well as restrain each other. Such a mode focuses on the “two mechanisms and four patterns,”that is, to rely on the stimulative mechanism and restraint mechanism, and to enforce such patterns as centralized management and application centralized management and common application, opening to public use, and renting and borrowing. Through persistent exploration of the inner potential of the institutions, the ratio of investment and economic efficiency will accordingly be elevated.

2型糖尿病患者护理中Triangle分层分级管理联合LEARNS模式的应用效果

目的探究2型糖尿病(Type 2 Diabetes Mellitus,T2DM)患者护理中Triangle分层分级管理联合LEARNS模式的应用效果。方法选取武威市天祝藏族自治县人民医院于2021年2月—2023年2月收治的280例T2DM患者为研究对象,以随机信封法分为常规组(n=140,常规护理)、观察组(n=140,常规组基础上行Triangle分层分级管理联合LEARNS模式)。观察并对比护理前后组间、组内各指标之间的差异。结果干预前组间血糖水平、自我管理能力评分对比,差异无统计学意义(P均>0.05);组间干预6个月后血糖水平对比,观察组更低,差异有统计学意义(P<0.05);组间干预6个月后自我管理能力评分对比,观察组(85.41±3.12)分高于常规组(84.23±3.19)分,差异有统计学意义(t=3.129,P<0.05)。结论Triangle分层分级管理联合LEARNS模式护理T2DM,可改善血糖水平及提高患者自我管理能力。

Constructing a Monitoring Mode over English Autonomous Learning in the Networking Age

In the Networking age,the monitoring from teachers and classmates over one's English autonomous learning is weakened.The relevance among learning resources can't be measured,and the learning efficiency can't be ensured,either.In order to solve the problems,a monitoring mode over English autonomous learning process is constructed,which involves the application of the internal and external monitoring strategies.