新课改下新的语文教学模式探析

面对新课程的新导向，语文教师要重视教学方式的转变和创新，要变灌输式的教学为宿发式的教学，变重结果的教学为重过程的教学，变单一的信息传递的教学为综合信息交流的教学，变模式化的教学为个性发展的教学。只有实现教学方式的转变，才能改变沉闷的课堂教学，才能适应新课程标准的要求。

Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.

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.

Evolution of surgical skills training

Surgical training is changing： one hundred years of tradition is being challenged by legal and ethical concerns for patient safety, work hours restrictions, the cost of operating room time, and complications. Surgical simulation and skills training offers an opportunity to teach and practice advanced skills outside of the operating room environment before attempting them on living patients. Simulation training can be as straight forward as using real instruments and video equipment to manipulate simulated ＂tissue＂ in a box trainer. More advanced, virtual reality simulators are now available and ready for widespread use. Early systems have demonstrated their effectiveness and discriminative ability. Newer systems enable the development of comprehensive curricula and full procedural simulations. The Accreditation Council of Graduate Medical Education＇s （ACGME） has mandated the development of novel methods of training and evaluation. Surgical organizations are calling for methods to ensure the maintenance of skills, advance surgical training, and to credential surgeons as technically competent. Simulators in their current form have been demonstrated to improve the operating room performance of surgical residents. Development of standardized training curricula remains an urgent and important agenda, particularly for minimal invasive surgery. An innovative and progressive approach, borrowing experiences from the field of aviation, can provide the foundation for the next century of surgical training, ensuring the quality of the product. As the technology develops, the way we practice will continue to evolve, to the benefit of physicians and patients.

Dimensionality Reduction with Input Training Neural Network and Its Application in Chemical Process Modelling

Many applications of principal component analysis (PCA) can be found in dimensionality reduction. But linear PCA method is not well suitable for nonlinear chemical processes. A new PCA method based on im-proved input training neural network (IT-NN) is proposed for the nonlinear system modelling in this paper. Mo-mentum factor and adaptive learning rate are introduced into learning algorithm to improve the training speed of IT-NN. Contrasting to the auto-associative neural network (ANN), IT-NN has less hidden layers and higher training speed. The effectiveness is illustrated through a comparison of IT-NN with linear PCA and ANN with experiments. Moreover, the IT-NN is combined with RBF neural network (RBF-NN) to model the yields of ethylene and propyl-ene in the naphtha pyrolysis system. From the illustrative example and practical application, IT-NN combined with RBF-NN is an effective method of nonlinear chemical process modelling.

Computer-based simulative training system--a new approach to teaching pre-hospital trauma care

Objective:A computer-based STS(simulative training system) in providing pre-hospital trauma care at a disaster site was applied to teaching nursing students in the Second Military Medical University,China.This article reports on the teaching effectiveness of this system.Methods:Among 92 participants,46 were in the study group and 46 were in the 'control' group. Each student completed a multiple-choice quiz after completing 18 hours(six three-hour sessions) of the study module,and a score was recorded.The simulative training module was completed only by the study group;the 'control' group was assigned in-class discussions for the same amount of time covering the same content as the study group.The final course scores,which included both comprehensive and group task-based tests were compared between these two groups.The study used a descriptive and comparative approach for quantitative data analysis.Tests of independency between the multiple choice scores and the simulation scores were also performed.Finally,anonymous surveys were conducted.Results:The study group performed better than the 'control' group with a significantly higher average score for the group scenario task-based test score,and consequently the study group's final course score was significantly higher than the 'control' group.As per chi-square tests,no significant associations were found between the multiple choice scores and the simulated training scores.The final surveys showed students overwhelmingly agreed that STS training improved their knowledge and skills,their ability to recognize a potential critical event, and their initial response for trauma care at pre-hospital settings.The survey responses of the study group were noteworthy as they indicated that students recognized the importance of simulative training,appreciated the realism of the simulation,and were able to fight/adjust to the stressful feelings in order to focus on the task.Conclusion:Computer-based STS may be an effective teaching model to help students improve their capability in providing pre-hospital trauma care,and in their effectiveness in disaster response.

Evaluation of Training Program for New Nurses to Enhance Caring Behavior

This research was aimed to evaluate the training program enhancing caring behaviors of new nurses by Kirkpatrick＇s four level for evaluation model： reaction, learning, behavior, and result of the program. The participants were new nurses, preceptors of new nurses, administrators, patients and members of the patients＇ family cared by new nurses. The research instruments were： （1） five questionnaires toward program suitability, knowledge, attitude, caring expression, and result to organization. The mean, standard deviation and dependent sample t-test were used for data analysis; （2） guidelines for focus group discussion and semi-structural questionnaire analyzed by content analysis. The study revealed that： （1） the mean of suitability was at the very high level （X = 4.49, SD. = .30）; （2） the knowledge and attitude after training were significantly higher than before training at .000 level, [t =-21.65, p = .000 and t = -19.30, p = .000）; {3} caring behavior after training was significantly higher than before training at the .000 level; and {4} the result of the program was at the high level { X = 4.25, SD. = .17}, related to the result of semi-structured interview and focus group discussion. These evaluation research finding suggested that administrators can use for improving the preparation of any project and apply to evaluate other training programs, developing human resource system.

Interprofessional education in nursing: The impact of collaboration between physical and mental health care professionals

Objectives:lnterprofessional collaboration in the training of nursing and psychology students helps provide students of both disciplines with the ability and competences they need to best attend to their patients.This study implemented and analyzed a method for developing the competences of each discipline in a scenario of joint clinical simulation that incorporates mental and physical health simultaneously,and measured the caring ability of the participating students.Methods:Participants took a self-applied survey measuring their own caring ability.After,a clinical simulation was performed where nursing students performed clinical interviews on psychology students,who acted as standardized patients.Caring abilities were measured in the nursing students,and the psychology students implemented an intervention service measuring caring ability and brief-debrief simulation by coaching to nursing students.Results:The results indicated that the self-applied questionnaire of caring ability resulted in scores significantly higher than what was measured by observers.Conclusions:The results contribute to the development of protocols,training and collaborative work practices in interprofessional education,which allow the scaling of these competences.

Intelligent model of rehabilitation training program for stroke

In view of the uncertainty and complexity,the intelligent model of rehabilitation training program for stroke was proposed,combining with the case-based reasoning(CBR) and interval type-2 fuzzy reasoning(IT2FR).The model consists of two parts:the setting model based on CBR and the feedback compensation model based on IT2FR.The former presets the value of rehabilitation training program,and the latter carries on the feedback compensation of the preset value.Experimental results show that the average percentage error of two rehabilitation training programs is 0.074%.The two programs are made by the intelligent model and rehabilitation physician.That is,the two different programs are nearly identical.It means that the intelligent model can make a rehabilitation training program effectively and improve the rehabilitation efficiency.

Training gastroenterology fellows to perform gastric polypectomy using a novel ex vivo model

AIM:To evaluate the effect of hands-on training of gastroenterology fellows in gastric polypectomy using an ex vivo simulator.METHODS:Eight gastroenterology fellows at Mackay Memorial Hospital,Taipei were evaluated in gastricpolypectomy techniques using a pig stomach with artificial polyps created by a rubber band ligation device.The performance of four second year(year-2)fellows who had undergone one year of clinical training was compared with that of four f irst year(year-1)fellows both before and after a 4-h workshop using the ex vivo simulator.The workshop allowed for hands-on train-ing in the removal of multiple artif icial polyps and the placement of hemoclips at the excision site.Evaluation included observation of technical skills,procedure time,and the fellows' conf idence scale.RESULTS:One week after the workshop,the year-1 fellows were re-evaluated and had significantly im-proved mean performance scores(from 17.9 ± 1.8 to 22.5 ± 0.7),conf idence scale(from 4.5 ± 1.0 to 7.8 ± 0.5)and procedure time(from 615.0 ± 57.4 s to 357.5 ± 85.0 s)compared with their baseline performance.After 4 h of training using the ex vivo simulator,the skills of the year-1 fellows were statistically similar to those of the year-2 fellows.CONCLUSION:Use of this ex vivo simulator significantly improved the endoscopic gastric polypectomy skills of gastroenterology fellows who had not had previous clinical training in gastric polypectomy.

Research on the Flexible Yoga Training Mode based on Yin and Yang Theory of Dialectical Thinking Pattern

In this research paper, we conduct research on the flexible yoga training mode based on Yin and Yang theory of dialectical thinking pattern. Yoga become modem young people are increasingly keen on sports exercise program, at the same time, as more ferocious originated in India yoga culture, even beyond the native of the popularity of the tai chi culture in China, in view of this kind of social cultural phenomenon, the author think it is necessary to carry out the two of fitness culture contrast research, to more deep understanding from angle of culturology of tai chi chuan and the Indian yoga in development in our country, as well as the similarities and differences of inheritance, development and research of its better to provide theoretical reference. We discuss the combination of the cutures and propose the flexible yoga training mode which is innovative.

Adaptive WNN aerodynamic modeling based on subset KPCA feature extraction

In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.

Sub-pixel mapping method based on BP neural network

A new sub-pixel mapping method based on BP neural network is proposed in order to determine the spatial distribution of class components in each mixed pixel.The network was used to train a model that describes the relationship between spatial distribution of target components in mixed pixel and its neighboring information.Then the sub-pixel scaled target could be predicted by the trained model.In order to improve the performance of BP network,BP learning algorithm with momentum was employed.The experiments were conducted both on synthetic images and on hyperspectral imagery(HSI).The results prove that this method is capable of estimating land covers fairly accurately and has a great superiority over some other sub-pixel mapping methods in terms of computational complexity.

EEG classification based on probabilistic neural network with supervised learning in brain computer interface

Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented in this paper. It applies the recognition rate of training samples to the learning progress of network parameters. The learning vector quantization is employed to group training samples and the Genetic algorithm （GA） is used for training the network＇ s smoothing parameters and hidden central vector for detemlining hidden neurons. Utilizing the standard dataset I （a） of BCI Competition 2003 and comparing with other classification methods, the experiment results show that the best performance of pattern recognition Js got in this way, and the classification accuracy can reach to 93.8%, which improves over 5% compared with the best result （88.7 % ） of the competition. This technology provides an effective way to EEG classification in practical system of BCI.

Novel Active Learning Method for Speech Recognition

In speech recognition, acoustic modeling always requires tremendous transcribed samples, and the transcription becomes intensively time-consuming and costly. In order to aid this labor-intensive process, Active Learning （AL） is adopted for speech recognition, where only the most informative training samples are selected for manual annotation. In this paper, we propose a novel active learning method for Chinese acoustic modeling, the methods for initial training set selection based on Kullback-Leibler Divergence （KLD） and sample evaluation based on multi-level confusion networks are proposed and adopted in our active learning system, respectively. Our experiments show that our proposed method can achieve satisfying performances.

When Sensory Substitution Devices Strike Back： An Interactive Training Paradigm

A sensory substitution device （SSD） is a technology that translates information for one sensory modality, like vision, into information for use by another, like touch. Though SSDs have been in existence for over four decades, effective training techniques for their use are rarely discussed. In this paper, we compare three training strategies on a particular SSD known as the vOICe. These comparisons were conducted using a minimal but active search and localization task of luminescent discs. These studies show that an interactive training paradigm, which combines the efforts of two trainees at the same time in a tag-like game, is more effective than passive training at a computer console or active training involving search and localization of luminescent discs. This finding supports philosophical views of perception that take interaction with the environment seriously. In particular, we argue that these findings are in support of certain features of the extended mind view as proposed by Andy Clark （2008）. In particular, the study suggests that when environmental conditions are responsive to one＇s behavioral activity, the activity itself is enhanced, as is predicted by the extended mind view.

The Significance of Students＇ Personal Narratives in Teacher Training

Recognizing the importance of personal narratives in general and in the field of teacher training in particular this paper first presents a review of research in the field, offers several definitions and theories of analysis, and then provides readers with the personal narratives and the analyses of three fourth-year students in the Department of English at a College for Teacher Training. The goal is to find out, learn, and make use of the voices, attitudes, experiences, visions, successes, failures, hopes, and frustrations of students engaged in teacher education. The conclusion asserts the necessity of adopting a model of training which is based on students＇ personal narratives--one which encourages and strengthens partnership between students cooperating teachers, and academics

A Model to Analyze Small and Medium Enterprises＇ Training Needs Related to the Internationalization

Formal training can play a particularly important role in supporting the internationalization of small and medium enterprises （SMEs）. However, the demand for education services by the latter still appears limited. This is due to known structural and cultural limits that are found widely in this type of business and to the fact that the provision of training---especially that which is funded^oes not seem to address adequately SMEs＇ needs; in many cases, such training is not stimulating, because it is perceived as too general. In fact, SMEs do not constitute a single homogeneous group and therefore assistance needs vary among the different types of firms. So, especially in relation to internationalization, it is clear that there are important differences to consider due to the variety of approaches and ways of developing this process. In order to optimize the resources to invest in the promotion of training, there is a need to find a proper balance between providing ＂viable solutions for all businesses＂ and offering ＂targeted responses and tailored services＂. In such a context, the main objective of this paper is to identify and systematize the variables that most influence the SMEs＇ training needs related to internationalization by taking into account the differences among them. To this end, an empirical analysis was developed involving a significant number of Italian SMEs by using a combination of qualitative research methods. The results show the critical issues faced by the investigated firms during their internationalization process and highlight some important variables that affect their training needs： export involvement, characteristics of the product/market, characteristics of the company, exporting strategy, and human resources. Based on these variables, the writers identified clusters of firms characterized by similar needs and problems to be faced.

The research and develop on the training mode of the innovative professional photography personnel

Under the background of the Digital Age, This article proposes suggestions on the training mode of the innovative professional photography personnel. We should rest on the good foundations of the demand pattern of ＇Double art talent＇ and take advantage of the advanced special services of Art Design. We should persist in the principle of Artistic Innovation first. We should establish an optimal training scheme of ＇photography creative talents＇ . A highly innovative photography subject system will train talents for ＇Design of photography＇ . We should change our opinions on traditional teaching, and to suggest improvements or comment on the practicability of the innovation and reform of Professional photography.

Online Forum Post Opinion Classification Based on Tree Conditional Random Fields Model

There is a major defect when using the traditional topic-opinion model for post opinion classifications in an online forum discussion.The accuracy of the classification based on the topic-opinion model highly depends on the observable topic-opinion features aiming at the subject,while a large number of posts do not have such features in a forum.Therefore,for the most part,the accuracy is less than 78%.To solve this problem,we propose a new method to identify post opinions based on the Tree Conditional Random Fields(T-CRFs)model.First,we select the topic-opinion features of the posts and associated opinion features between posts to construct the T-CRFs model,and then we use the T-CRFs model to label the opinions of the tree-structured posts under the same topic iteratively to reach a maximum joint probability.To reduce the training cost,we design a simplified tree diagram module and some feature templates.Experimental results suggest the proposed method costs less training time and improves the accuracy by 11%.