Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of CO...Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of COPD.Methods:A descriptive nature research method was adopted.An interview outline was formulated based on the theoretical domain framework.From October to December 2024,15 medical staff from the respiratory department of a tertiary hospital in Shaanxi Province were selected for semi-structured interviews.The interview data were analyzed using the Colaizzi 7-step analysis method.Result:The analysis of this study found that the obstructive factors for medical staff to implement respiratory rehabilitation include five theoretical domains.The problems are respectively the lack of knowledge about respiratory rehabilitation and insufficient training intensity,the insufficient self-recognition of implementing respiratory rehabilitation,the low awareness rate of patients and the low cooperation degree,the insufficient provision of instruments and facilities,the lack of rehabilitation training venues and respiratory rehabilitation clinics,and the lack of scientific and standardized respiratory rehabilitation management processes.Conclusion:There are many obstructive factors affecting the implementation of respiratory rehabilitation by medical staff.Clinical managers should take corresponding measures,continuously improve the rehabilitation management strategies for COPD,and promote the clinical application of the best evidence for respiratory rehabilitation.展开更多
The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge ...The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was展开更多
With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. Fir...With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.展开更多
目的了解理论域框架在慢性病患者行为改变中的应用现状,以期为国内慢性病管理干预策略的制订和完善提供思路。方法以澳大利亚JBI循证卫生保健中心范围综述指南为方法学框架,系统检索PubMed、Embase、CINAHL、Web of Science、Cochrane L...目的了解理论域框架在慢性病患者行为改变中的应用现状,以期为国内慢性病管理干预策略的制订和完善提供思路。方法以澳大利亚JBI循证卫生保健中心范围综述指南为方法学框架,系统检索PubMed、Embase、CINAHL、Web of Science、Cochrane Library、中国知网、万方、维普和中国生物医学数据库。检索时限为建库至2025年4月28日。结果共纳入72篇文献,其中质性研究54篇,量性研究9篇及混合研究9篇,学者对理论域框架的应用以设计访谈提纲、编码访谈资料、开发调查问卷为主,重点关注的疾病类型为慢性病,包括糖尿病、心脑血管疾病、癌症等,健康相关行为集中在饮食健康、运动锻炼、用药管理、遵医和预防保健行为等方面,与行为改变关联较强的理论域依次为环境与资源、社会影响、知识和结果信念。结论理论域框架可帮助研究者全面、深入地识别影响慢性病患者行为改变的决定性因素,促进干预措施的制订和完善,以适应不同患者的个性化需求,为慢性病防治提供创新方法论支持。展开更多
目的:以理论域框架为基础,系统综述乳腺癌病人辅助内分泌治疗(AET)依从性的行为心理学影响因素。方法:检索PubMed、Web of Science、EMbase、CINAHL、Cochrane Library、中国生物医学文献数据库(CBM)、中国知网(CNKI)、万方数据库(WanFa...目的:以理论域框架为基础,系统综述乳腺癌病人辅助内分泌治疗(AET)依从性的行为心理学影响因素。方法:检索PubMed、Web of Science、EMbase、CINAHL、Cochrane Library、中国生物医学文献数据库(CBM)、中国知网(CNKI)、万方数据库(WanFang Data)、维普数据库(VIP)9个数据库中涉及乳腺癌AET病人依从性行为心理学影响因素的中英文文献。由2名研究者独立筛选文献并提取资料。采用Nvivo 14软件进行数据分析,以理论域框架的14个理论域为一级节点对行为心理学影响因素相关文本进行编码,使用主题分析法凝练二级节点。结果:共纳入50篇文献,获得297个编码点,归纳获得30个二级节点,分布于12个理论域。环境和资源、情感、社会影响是编码点最多的3个理论域;身体状况是对病人依从性影响最多的因素。结论:乳腺癌病人AET依从性的行为心理学影响因素涉及理论域框架的多个理论域,且各因素间可能存在交互作用关系,可探索多种因素对依从性的作用路径以更精准、高效地进行行为干预。展开更多
域名系统(domain name system,DNS)是互联网的核心基础设施,其解析可靠性直接影响网络服务的可用性与用户体验。然而,随着DNS的功能扩展与体系结构复杂度的增加,DNS解析失败日益频发。现有针对DNS解析失败的研究较为碎片化,缺乏系统性...域名系统(domain name system,DNS)是互联网的核心基础设施,其解析可靠性直接影响网络服务的可用性与用户体验。然而,随着DNS的功能扩展与体系结构复杂度的增加,DNS解析失败日益频发。现有针对DNS解析失败的研究较为碎片化,缺乏系统性的归纳与方法论支撑。鉴于此,从协议实施缺陷、配置错误、域名滥用、网络与管理问题4个维度提出分类归因框架,系统地刻画了DNS解析失败的成因与特征。基于该框架,结合互联网工程任务组发布的请求评议标准与典型案例,提出了协议一致性测试、自动化配置校验、域名信誉评分、高可用部署架构等缓解思路,为DNS故障诊断和防护提供系统化的分析视角与实践参考。展开更多
人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Mod...人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Model of Domain Learning)和COST(Content-Others-Self-Task)教学设计框架,系统探讨人工智能深度融入教学的理论与实践路径。通过整合多模态数字资源与知识图谱、数字教师与虚拟学伴等人工智能工具,课程设计旨在促进学习者系统化知识的构建、个人专业兴趣的形成以及深度学习策略的掌握。研究指出,未来研究应进一步探索情感支持机制与复杂工程场景模拟,以推动人工智能与教育的深度融合与创新发展。展开更多
基金Shaanxi Provincial People’s Hospital Science and Technology Development Incubation Fund Program 2023(Project No.:2023HL-12)。
文摘Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of COPD.Methods:A descriptive nature research method was adopted.An interview outline was formulated based on the theoretical domain framework.From October to December 2024,15 medical staff from the respiratory department of a tertiary hospital in Shaanxi Province were selected for semi-structured interviews.The interview data were analyzed using the Colaizzi 7-step analysis method.Result:The analysis of this study found that the obstructive factors for medical staff to implement respiratory rehabilitation include five theoretical domains.The problems are respectively the lack of knowledge about respiratory rehabilitation and insufficient training intensity,the insufficient self-recognition of implementing respiratory rehabilitation,the low awareness rate of patients and the low cooperation degree,the insufficient provision of instruments and facilities,the lack of rehabilitation training venues and respiratory rehabilitation clinics,and the lack of scientific and standardized respiratory rehabilitation management processes.Conclusion:There are many obstructive factors affecting the implementation of respiratory rehabilitation by medical staff.Clinical managers should take corresponding measures,continuously improve the rehabilitation management strategies for COPD,and promote the clinical application of the best evidence for respiratory rehabilitation.
基金supported by the Key Technology R&D Program of China during the 12th Five-Year Plan period:Super-Class Scientific and Technical Thesaurus and Ontology Construction Faced the Foreign Scientific and Technical Literature (2011BAH10B01)
文摘The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was
基金Supported by the National Natural Science Foun-dation of China (60173058 ,70372024)
文摘With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.
文摘目的了解理论域框架在慢性病患者行为改变中的应用现状,以期为国内慢性病管理干预策略的制订和完善提供思路。方法以澳大利亚JBI循证卫生保健中心范围综述指南为方法学框架,系统检索PubMed、Embase、CINAHL、Web of Science、Cochrane Library、中国知网、万方、维普和中国生物医学数据库。检索时限为建库至2025年4月28日。结果共纳入72篇文献,其中质性研究54篇,量性研究9篇及混合研究9篇,学者对理论域框架的应用以设计访谈提纲、编码访谈资料、开发调查问卷为主,重点关注的疾病类型为慢性病,包括糖尿病、心脑血管疾病、癌症等,健康相关行为集中在饮食健康、运动锻炼、用药管理、遵医和预防保健行为等方面,与行为改变关联较强的理论域依次为环境与资源、社会影响、知识和结果信念。结论理论域框架可帮助研究者全面、深入地识别影响慢性病患者行为改变的决定性因素,促进干预措施的制订和完善,以适应不同患者的个性化需求,为慢性病防治提供创新方法论支持。
文摘域名系统(domain name system,DNS)是互联网的核心基础设施,其解析可靠性直接影响网络服务的可用性与用户体验。然而,随着DNS的功能扩展与体系结构复杂度的增加,DNS解析失败日益频发。现有针对DNS解析失败的研究较为碎片化,缺乏系统性的归纳与方法论支撑。鉴于此,从协议实施缺陷、配置错误、域名滥用、网络与管理问题4个维度提出分类归因框架,系统地刻画了DNS解析失败的成因与特征。基于该框架,结合互联网工程任务组发布的请求评议标准与典型案例,提出了协议一致性测试、自动化配置校验、域名信誉评分、高可用部署架构等缓解思路,为DNS故障诊断和防护提供系统化的分析视角与实践参考。
文摘人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Model of Domain Learning)和COST(Content-Others-Self-Task)教学设计框架,系统探讨人工智能深度融入教学的理论与实践路径。通过整合多模态数字资源与知识图谱、数字教师与虚拟学伴等人工智能工具,课程设计旨在促进学习者系统化知识的构建、个人专业兴趣的形成以及深度学习策略的掌握。研究指出,未来研究应进一步探索情感支持机制与复杂工程场景模拟,以推动人工智能与教育的深度融合与创新发展。
