A Model-Centric DevOps Architecture for DEVS-Based Digital Twin Simulation Services
本文提出了一种以模型为中心的DevOps架构,用于将基于DEVS的数字孪生模拟作为管理服务部署,解决了版本控制、自动化验证和持续交付问题。
本文提出了一种以模型为中心的DevOps架构,用于将基于DEVS的数字孪生模拟作为管理服务部署,解决了版本控制、自动化验证和持续交付问题。
研究提出固定后缀依赖比率(FSDR)方法,量化拉脱维亚借词中性别分配对固定派生后缀的依赖程度,揭示了借词系统中的显著不对称性。
研究解决了软互动伴侣中情感触摸分类的难题,通过设计和验证紧凑的机器学习模型,使用1D CNNs和SVM等方法,在多类任务上达到高准确率。
To address steep learning curves and low learner motivation in post-merger information systems (IS) integration training, this study proposes the first gamified learning framework specifically designed for this context. Drawing on cognitive load theory, the ARCS motivation model, and serious game design principles, we develop a dual-component architecture—“transformation process” and “learning experience”—through iterative design and empirical validation. Key design requirements are identified, and a practical roadmap for framework development and evaluation is established. Results demonstrate that the framework significantly reduces extraneous cognitive load, enhances intrinsic motivation, and improves decision-support capabilities among IS integration professionals. This work contributes a theoretically grounded yet operationally viable paradigm for IS integration training, bridging critical gaps between learning science, human-computer interaction, and organizational change management. (149 words)
本文提出了一种以模型为中心的DevOps架构,用于将基于DEVS的数字孪生模拟作为管理服务部署,解决了版本控制、自动化验证和持续交付问题。
研究提出固定后缀依赖比率(FSDR)方法,量化拉脱维亚借词中性别分配对固定派生后缀的依赖程度,揭示了借词系统中的显著不对称性。
研究解决了软互动伴侣中情感触摸分类的难题,通过设计和验证紧凑的机器学习模型,使用1D CNNs和SVM等方法,在多类任务上达到高准确率。
To address steep learning curves and low learner motivation in post-merger information systems (IS) integration training, this study proposes the first gamified learning framework specifically designed for this context. Drawing on cognitive load theory, the ARCS motivation model, and serious game design principles, we develop a dual-component architecture—“transformation process” and “learning experience”—through iterative design and empirical validation. Key design requirements are identified, and a practical roadmap for framework development and evaluation is established. Results demonstrate that the framework significantly reduces extraneous cognitive load, enhances intrinsic motivation, and improves decision-support capabilities among IS integration professionals. This work contributes a theoretically grounded yet operationally viable paradigm for IS integration training, bridging critical gaps between learning science, human-computer interaction, and organizational change management. (149 words)