This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for struct...This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.展开更多
目的:评估常见水果的营养充足率与营养素密度,为消费者在选择水果时提供科学依据。方法:选取12种常见水果,即奇异果(黄心和绿心)、橙子、草莓、芒果、柠檬、柑橘、香蕉、葡萄、西瓜、梨和苹果,分析检测其代表性的16种营养素的含量,包括...目的:评估常见水果的营养充足率与营养素密度,为消费者在选择水果时提供科学依据。方法:选取12种常见水果,即奇异果(黄心和绿心)、橙子、草莓、芒果、柠檬、柑橘、香蕉、葡萄、西瓜、梨和苹果,分析检测其代表性的16种营养素的含量,包括蛋白质、总膳食纤维、维生素A、维生素B_(1)、维生素B_(2)、烟酸、泛酸、维生素B6、叶酸、维生素B_(12)、维生素C、维生素D_(3)、维生素E、钙、铁及镁等,据此计算营养充足率评分(nutrient adequacy score,NAS)及营养素密度评分(nutrient density score,NDS),以衡量水果的营养价值。结果:NAS较高的有奇异果(黄心)、草莓、奇异果(绿心)和柠檬,分别为14.62、12.67、11.80、10.09;草莓、柠檬、奇异果(黄心)和奇异果(绿心)的NDS也较高,分别为39.61、27.28、23.98、20.70。维生素C和膳食纤维在奇异果中含量丰富,而柠檬和橙子是膳食纤维的良好来源。铁的含量高出现在草莓中,钙和镁的含量高出现在柠檬中。结论:奇异果(黄心)、草莓、奇异果(绿心)、柠檬和橙子均属于营养充足率和营养素密度较高的水果。展开更多
高比例电力电子化和高比例可再生能源特征加剧了新型电力系统频率失稳和供需失配风险。为了防控这两类风险,需要在系统运行调度中引入频率与充裕性约束,但这两类约束使模型计算复杂度激增,难以在运行尺度内高精度求解。因此提出了计及...高比例电力电子化和高比例可再生能源特征加剧了新型电力系统频率失稳和供需失配风险。为了防控这两类风险,需要在系统运行调度中引入频率与充裕性约束,但这两类约束使模型计算复杂度激增,难以在运行尺度内高精度求解。因此提出了计及频率安全约束和充裕性约束的机组组合模型(frequency and adequacy constrained unit commitment,FACUC)。首先,建立了系统频率响应模型和考虑运行约束的运行充裕性评估模型,并将两种约束纳入FACUC中。其次,提出了一种分解优化方法来求解所提出的优化模型,将原问题分解为一个混合整数线性规划(mixed integer linear programming,MILP)的主问题、基于仿真计算的频率安全性评估子问题和基于最优化的充裕性评估子问题。通过主子问题之间的依次迭代,最终对FACUC模型进行求解。基于改进的IEEE 39节点系统进行算例分析,结果表明所提出的FACUC模型在保证经济性的同时,能够有效提高系统的频率安全和充裕性。展开更多
文摘This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.
文摘目的:评估常见水果的营养充足率与营养素密度,为消费者在选择水果时提供科学依据。方法:选取12种常见水果,即奇异果(黄心和绿心)、橙子、草莓、芒果、柠檬、柑橘、香蕉、葡萄、西瓜、梨和苹果,分析检测其代表性的16种营养素的含量,包括蛋白质、总膳食纤维、维生素A、维生素B_(1)、维生素B_(2)、烟酸、泛酸、维生素B6、叶酸、维生素B_(12)、维生素C、维生素D_(3)、维生素E、钙、铁及镁等,据此计算营养充足率评分(nutrient adequacy score,NAS)及营养素密度评分(nutrient density score,NDS),以衡量水果的营养价值。结果:NAS较高的有奇异果(黄心)、草莓、奇异果(绿心)和柠檬,分别为14.62、12.67、11.80、10.09;草莓、柠檬、奇异果(黄心)和奇异果(绿心)的NDS也较高,分别为39.61、27.28、23.98、20.70。维生素C和膳食纤维在奇异果中含量丰富,而柠檬和橙子是膳食纤维的良好来源。铁的含量高出现在草莓中,钙和镁的含量高出现在柠檬中。结论:奇异果(黄心)、草莓、奇异果(绿心)、柠檬和橙子均属于营养充足率和营养素密度较高的水果。
文摘高比例电力电子化和高比例可再生能源特征加剧了新型电力系统频率失稳和供需失配风险。为了防控这两类风险,需要在系统运行调度中引入频率与充裕性约束,但这两类约束使模型计算复杂度激增,难以在运行尺度内高精度求解。因此提出了计及频率安全约束和充裕性约束的机组组合模型(frequency and adequacy constrained unit commitment,FACUC)。首先,建立了系统频率响应模型和考虑运行约束的运行充裕性评估模型,并将两种约束纳入FACUC中。其次,提出了一种分解优化方法来求解所提出的优化模型,将原问题分解为一个混合整数线性规划(mixed integer linear programming,MILP)的主问题、基于仿真计算的频率安全性评估子问题和基于最优化的充裕性评估子问题。通过主子问题之间的依次迭代,最终对FACUC模型进行求解。基于改进的IEEE 39节点系统进行算例分析,结果表明所提出的FACUC模型在保证经济性的同时,能够有效提高系统的频率安全和充裕性。
