8 results about "Professional development" patented technology

The invention provides a teacher professional development personalized recommendation method and system based on multi-modal data, and the method comprises the steps: obtaining the multi-modal data of a teacher, carrying out the time-space alignment and dimension unification of the multi-modal data, and generating a multi-modal fusion feature; quantizing the teaching ability of the teacher based on the multi-modal fusion features to obtain ability scores of the teacher in different ability dimensions; according to the ability scores of the different ability dimensions and the demand intensity of the teacher, calculating ability gap values of the different ability dimensions; and matching the capability gap value and the demand intensity with training resources to generate recommendation information. According to the recommendation method and system provided by the invention, the defects of single data source, static evaluation, recommendation homogenization and lack of continuous optimization in the prior art are overcome, and the accuracy, personalization and sustainability of professional development support of teachers are improved.

The invention discloses an online evaluation system and method based on occupational skills, relates to the technical field of occupational skill evaluation, and aims to solve the problems of one-sidedness, low efficiency and single dimension of traditional evaluation and realize multi-dimensional, accurate and efficient evaluation. The system comprises a user information management module, an evaluation index setting module, a data acquisition module, a data analysis and evaluation module, a result display and feedback module and a certificate generation and management module. The index setting module constructs a multi-dimensional index system for different occupations and sets quantitative standards and weights; the data acquisition module is used for acquiring data in multiple modes of online examination, video analysis and the like; the analysis module generates scores and comprehensive results through machine learning; the display module displays the result and provides suggestions; the certificate module generates a verifiable certificate after the user reaches the standard. The process of the method comprises the steps of registration and entry, index determination, data acquisition, analysis and evaluation, result feedback and certificate generation, and a basis can be provided for professional development and talent selection.

This invention discloses a method for improving the success rate of POY yarn spinning. The method is characterized by the following steps: POY yarn cake is prepared through slurry preparation, esterification, polycondensation, metering, melt extrusion via spinneret, cooling, oiling, and winding. During POY spinning, the oil content of the initial 0-1000m length of the POY bottom yarn and the last 1000m length of the POY surface yarn in each POY yarn cake is increased by 8-15%, while the oil content of the middle portion of the POY yarn remains unchanged. This method solves the problem of high yarn breakage rates caused by reduced yarn cohesion and adhesion of the bottom yarn after the oil evaporates.

The invention discloses a project management system development method based on low code configuration, relates to the technical field of computer software, and remarkably improves the prediction adaptability and practicability of a project management system in a new project type through a low code configuration and meta-learning fused architecture. A low-code interface allows non-technical users to intuitively configure project parameters, such as a construction period or a risk index, so that a system customization threshold is reduced, and enterprises can quickly respond to innovative project requirements without depending on professional development teams; the meta-learning module uses general knowledge of a pre-training model to complete model adjustment only with a small amount of new data, and overcomes the defect of weak generalization ability of a traditional model in a data sparse scene; the few-sample adaptive mechanism is optimized through internal and external loops, so that the model is ensured to be fast converged while keeping stability, and the training time and resource consumption are reduced; the verification process in the deployment stage enhances the reliability of the system, and the dynamic consistency verification can detect the output deviation of the model in time.

This application provides a method for configuring a self-service mode of a system, comprising: obtaining configuration parameters for the self-service mode from the cloud; and configuring the system's self-service mode according to the configuration parameters. The configuration parameters in the cloud may be set by the manufacturer of the self-service device, for example. When the self-service device needs to enter self-service mode, it can send a request message to the cloud to request the configuration parameters for the self-service mode; subsequently, it configures the system's self-service mode according to these configuration parameters. Since the configuration parameters are set by the manufacturer of the self-service device, and manufacturers typically have more professional development capabilities than customers, the above method reduces the time required to deploy the self-service device and the risk of secondary development failures, thereby reducing developer costs.

The invention discloses a nurse training examination system based on OKR. According to the system, a nurse can effectively master clinical theoretical knowledge and skills through the system, the nursing service quality is improved, medical errors are reduced, the work satisfaction degree and occupational development of the nurse are improved, modernization of nursing education is greatly promoted through implementation of the system, and the development of the nurse is promoted. The invention discloses an OKR-based nurse training examination system, and aims to ensure that continuous education and professional development of nurses can meet the goals of medical institutions, and improve the nursing quality and patient nursing results at the same time. By integrating the OKR into the training and assessment process, the progress can be better tracked, nurses are helped to improve professional skills, finally, the medical service quality is improved, and benefits are brought to patients. According to the system, a customized and high-efficiency nurse training system is created, and contributions are made to the development of the nursing industry.

The present invention provides a system and method for delivering interactive, chat-based training simulations tailored to mental health professionals. The system leverages large language model (LLM) technology, integrated with evidence-based psychological theories and behavioral principles, to create realistic simulations of interactions with virtual patients or colleagues. Key components include a prompting engine for generating scenario-specific prompts, an LLM for producing contextually accurate and clinically consistent responses, a transcript management module for recording and maintaining conversation logs, and an analytical feedback engine for evaluating user performance and providing actionable insights. The system enables mental health practitioners to practice therapeutic techniques, enhance clinical understanding, and refine professional skills in a controlled, immersive, and cost-effective environment. Applications extend to organizational training, candidate assessments, and broader professional development scenarios, offering an innovative, scalable solution to enhance the quality and accessibility of mental health education and training.

The invention belongs to a multi-modal analysis and evaluation method for a classroom teaching skill video, and belongs to the crossing field of education technology and artificial intelligence, and the method comprises the following steps: uploading a video and filling metadata; automatically preprocessing the video; teaching targets and characteristic innovation are analyzed; analyzing the teaching content and the teaching method; analyzing teacher behaviors; analyzing student performance; analyzing the classroom atmosphere; analyzing teaching evaluation; analyzing characteristic innovation; comprehensive evaluation is given; and generating an analysis report. According to the method, a multi-view quantitative evaluation system is constructed by fusing a multi-AI technology, full-process automation is realized, content score and improvement suggestion reports are output, evaluation objectivity and efficiency are improved, and accurate improvement of teaching quality and professional development of teachers are supported.