论拓跋鲜卑民族的融合

化上的转变是完成民族融合的重要一步,这种转变促使了拓跋鲜卑民族成员社会心理与社会行为的变化。对汉化进一步“内化”的结果,使鲜卑人原初的民族意识逐渐消失、新的民族意识日益形成,当入主中原的拓跋鲜卑民族形成了与汉族相同的民族意识之后,就意味着二之间的融合已经完成,因此,民族意识的转化是考察民族融合的关键。     

林语堂MomentinPeking的翻译主体间性探究

在翻译活动中,只有相互作用的主体（译者、原作者和读者）平等交流和对话,才会取得成功的翻译。从视域融合视角出发,对林语堂先生所著Moment1nPeklng的三个译本进行对比分析．探讨主体词性在翻译过程中的体现和影响,对指导翻译活动有一定的意义。     

Adaptive multi-feature fusion via cross-entropy normalization for effective image retrieval

Multi-feature fusion has achieved gratifying performance in image retrieval. However, some existing fusion mechanisms would unfortunately make the result worse than expected due to the domain and visual diversity of images. As a result, a burning problem for applying feature fusion mechanism is how to figure out and improve the complementarity of multi-level heterogeneous features. To this end, this paper proposes an adaptive multi-feature fusion method via cross-entropy normalization for effective image retrieval. First, various low-level features (e.g., SIFT) and high-level semantic features based on deep learning are extracted. Under each level of feature representation, the initial similarity scores of the query image w.r.t. the target dataset are calculated. Second, we use an independent reference dataset to approximate the tail of the attained initial similarity score ranking curve by cross-entropy normalization. Then the area under the ranking curve is calculated as the indicator of the merit of corresponding feature (i.e., a smaller area indicates a more suitable feature.). Finally, fusion weights of each feature are assigned adaptively by the statistically elaborated areas. Extensive experiments on three public benchmark datasets have demonstrated that the proposed method can achieve superior performance compared with the existing methods, improving the metrics mAP by relatively 1.04% (for Holidays), 1.22% (for Oxf5k) and the N-S by relatively 0.04 (for UKbench), respectively.     

Artificial intelligence implication on energy sustainability in Internet of Things: A survey

The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.     

《计算机组成原理》教学中多课程知识融合探析

在《计算机组成原理》教学中实施多课程知识融合非常必要,文章举例分析了《计算机组成原理》与《程序设计》、《汇编语言》、《操作系统》等课程进行知识融合的方法,旨在通过教学改革,增进各课程间知识的联系,巩固、完善学生的专业知识体系。     

大学生法制教育与工程任务课程化融合探索

当前大学教育,特别是应用型人才培养过程中,不仅要求具备够用的专业能力和创新能力,而且对人才法律知识掌握程度和运用能力的要求也越来越高。而在大学中的法律知识学习途径除了＂两课＂中关于法律意识和法律制度的内容外,只有通过自学的方式取得。如果将法律知识的学习和应用与工程任务课程化融合,就能取得良好的效果,不但提高了法制意识,而且实际应用程度会更高,对培养复合型工程人才具有很强的实用价值。     

关于宇宙核模型与爱因斯坦宇宙学常数和反质量物质及黑洞关系的探讨

利用宇宙核式结构模型解释爱因斯坦宇宙学常数问题,并讨论宇宙核与负质量物质和黑洞的关系,进一步说明了宇宙的核式结构模型的正确性.     

“双园融合”办学模式下校企合作成本效益实证分析

"双园融合"是深化校企合作的一种办学模式。它是以专业建设为前提,校企共建生产性实训基地,共享资源,互惠互利、共同发展。通过调研,本文从学院角度对比分析"校中厂"与"厂中校"合作方式的成本效益,提出进一步深化合作、不断优化和完善"双园融合"办学模式的建议。     

虚实融合学习环境:概念、特征与应用

随着现代信息技术的发展和教育教学理念的转变,基于网络和多媒体的"虚拟"学习环境已经被人们熟悉并部分取代基于课堂的"现实"学习环境。虚拟和现实的学习环境各有利弊,前者有利于学习者使用丰富的数字化资源开展跨地域的协作学习、拓宽知识视野,后者有利于学习者的临场体验和实际操作能力培养。在分析相关文献和现有学习环境特征研究的基础上,分析了"虚实融合学习环境"的内涵与特征,对虚拟、现实以及虚实融合的学习环境进行比较,并就若干典型的虚实融合学习环境及其教学应用情况进行了分析,其中包括:校园环境信息观测与研究性学习、GLOBE全球性学习与观察、虚实融合的机器人教育、数字化探究实验室。     

三维图像重建中差异信息融合算法研究

针对三维图像重建中的差异信息融合算法识别率较低,稳定性差,无法有效处理不确定因素等弊端,提出一种新的三维图像重建差异信息融合算法,分析了二维图像和三维图像的一阶与二阶统计,对自相关函数进行归一化处理,将二维图像的自相关函数变成三维自相关函数,利用傅里叶变换求出三维图像的功率谱,通过调整合理的辐角塑造该三维图像的傅里叶转换。对三维图像重建过程中的特征向量进行划分,保证三维图像重建过程中全部信息的完整性。依据特征向量与信息之间的经验知识对学习样本进行建立,给出某一时间段内三维图像重建中某个神经网络对应的差异信息融合公式,对多个神经网络的差异信息融合结果进行融合,实现三维图像重建中差异信息的融合。仿真实验结果表明,所提算法具有很高的有效性。