In this paper, we conduct research on primary core factors of influencing college students＇ entrepreneurial success rate under the perspectives of the law and team management perspectives. College students＇ entrepre...In this paper, we conduct research on primary core factors of influencing college students＇ entrepreneurial success rate under the perspectives of the law and team management perspectives. College students＇ entrepreneurship education is cultivating he students innovative spirit and creative ability as the basic value tendency, in order to cultivate creative talents as the main goal of education, it is an extension of the quality-oriented education, is the comprehensive development of students＇ qualities of wisdom education is the all-round development of students＇ personality education ＇is pay more attention to the body of the human spirit, the humanist education. Carrying out entrepreneurship education, the reform and development of higher education to improve the quality of talent training levels promote national independent innovation and entrepreneurship has important significance. Our research proposes the novel perspective on the issues that is meaningful.展开更多
This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the...This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.展开更多
数据流是一类具有高生成率、动态分布特性的数据,其异常检测旨在从这一类数据中发现偏离预期行为的数据流,从而为医疗、工业生产、金融等诸多领域的决策提供支持。现有数据流异常检测方法普遍面临参数敏感性高、时空开销大、阈值选取难...数据流是一类具有高生成率、动态分布特性的数据,其异常检测旨在从这一类数据中发现偏离预期行为的数据流,从而为医疗、工业生产、金融等诸多领域的决策提供支持。现有数据流异常检测方法普遍面临参数敏感性高、时空开销大、阈值选取难等问题。为了解决上述问题,提出一种基于变密度的自适应数据流的异常检测方法。首先定义了可变局部离群因子(Va-riable Local Outlier Factor,VLOF),VLOF通过对比数据点在并行的不同k值的邻域窗口下,其局部可达密度和局部异常因子的变化情况,度量数据点的密度分布,降低单一k近邻密度度量导致的结果不准确。其次,计算VLOF与k值的相对增长率和绝对均值率,以反映数据流的动态变化趋势,并将适应这种动态变化趋势的数据点定义为核心点,通过核心点加快对后续正常点的判断。最后,将相对增长率和绝对均值率作为数据点理论分布的度量指标,计算理论分布和新数据点实际分布的差异,从而自适应地将偏离理论分布的点识别为异常。为了验证提出算法的有效性,在多个UCI数据集和真实数据集下与8个算法进行对比实验,实验结果表明:与基线模型相比,所提方法在精确率、召回率、F1性能指标上表现良好,且时间和空间效率也有相应提升。展开更多
Estimation of power transformer no-load loss is a critical issue in the design of distribution transformers. Any deviation in estimation of the core losses during the design stage can lead to a financial penalty for t...Estimation of power transformer no-load loss is a critical issue in the design of distribution transformers. Any deviation in estimation of the core losses during the design stage can lead to a financial penalty for the transformer manufacturer. In this paper an effective and novel method is proposed to determine all components of the iron core losses applying a combination of the empirical and numerical techniques. In this method at the first stage all computable components of the core losses are calculated, using Finite Element Method (FEM) modeling and analysis of the transformer iron core. This method takes into account magnetic sheets anisotropy, joint losses and stacking holes. Next, a Quadratic Programming (QP) optimization technique is employed to estimate the incomputable components of the core losses. This method provides a chance for improvement of the core loss estimation over the time when more measured data become available. The optimization process handles the singular deviations caused by different manufacturing machineries and labor during the transformer manufacturing and overhaul process. Therefore, application of this method enables different companies to obtain different results for the same designs and materials employed, using their historical data. Effectiveness of this method is verified by inspection of 54 full size distribution transformer measurement data.展开更多
文摘In this paper, we conduct research on primary core factors of influencing college students＇ entrepreneurial success rate under the perspectives of the law and team management perspectives. College students＇ entrepreneurship education is cultivating he students innovative spirit and creative ability as the basic value tendency, in order to cultivate creative talents as the main goal of education, it is an extension of the quality-oriented education, is the comprehensive development of students＇ qualities of wisdom education is the all-round development of students＇ personality education ＇is pay more attention to the body of the human spirit, the humanist education. Carrying out entrepreneurship education, the reform and development of higher education to improve the quality of talent training levels promote national independent innovation and entrepreneurship has important significance. Our research proposes the novel perspective on the issues that is meaningful.
文摘This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.
文摘数据流是一类具有高生成率、动态分布特性的数据,其异常检测旨在从这一类数据中发现偏离预期行为的数据流,从而为医疗、工业生产、金融等诸多领域的决策提供支持。现有数据流异常检测方法普遍面临参数敏感性高、时空开销大、阈值选取难等问题。为了解决上述问题,提出一种基于变密度的自适应数据流的异常检测方法。首先定义了可变局部离群因子(Va-riable Local Outlier Factor,VLOF),VLOF通过对比数据点在并行的不同k值的邻域窗口下,其局部可达密度和局部异常因子的变化情况,度量数据点的密度分布,降低单一k近邻密度度量导致的结果不准确。其次,计算VLOF与k值的相对增长率和绝对均值率,以反映数据流的动态变化趋势,并将适应这种动态变化趋势的数据点定义为核心点,通过核心点加快对后续正常点的判断。最后,将相对增长率和绝对均值率作为数据点理论分布的度量指标,计算理论分布和新数据点实际分布的差异,从而自适应地将偏离理论分布的点识别为异常。为了验证提出算法的有效性,在多个UCI数据集和真实数据集下与8个算法进行对比实验,实验结果表明:与基线模型相比,所提方法在精确率、召回率、F1性能指标上表现良好,且时间和空间效率也有相应提升。
文摘Estimation of power transformer no-load loss is a critical issue in the design of distribution transformers. Any deviation in estimation of the core losses during the design stage can lead to a financial penalty for the transformer manufacturer. In this paper an effective and novel method is proposed to determine all components of the iron core losses applying a combination of the empirical and numerical techniques. In this method at the first stage all computable components of the core losses are calculated, using Finite Element Method (FEM) modeling and analysis of the transformer iron core. This method takes into account magnetic sheets anisotropy, joint losses and stacking holes. Next, a Quadratic Programming (QP) optimization technique is employed to estimate the incomputable components of the core losses. This method provides a chance for improvement of the core loss estimation over the time when more measured data become available. The optimization process handles the singular deviations caused by different manufacturing machineries and labor during the transformer manufacturing and overhaul process. Therefore, application of this method enables different companies to obtain different results for the same designs and materials employed, using their historical data. Effectiveness of this method is verified by inspection of 54 full size distribution transformer measurement data.
