基于移动平台的翻转课堂教学研究

翻转课堂作为一种新的教学模式,迅速成为教育领域学者、教师研究的一个焦点。同时,移动平台以其便捷高效等特点在教育领域展现出巨大的活力。本文对基于移动平台的学习与翻转课堂教学融合可行性进行了分析,并且探讨了基于移动平台的翻转课堂教学构建途径,以期为基于移动平台的翻转课堂教学实践提供一些理论参考。2017年福建省教育厅,“双一流”背景下数字媒体特色专业建设探索,项目编号:FBJG20170302;;2018年教育部首批“新工科”研究与实践项目,新工科人才的创新创业能力培养探索——以厦门大学国家示范性软件学院为

基于混合式教学模式《IT项目管理》课程实践研究

《IT项目管理》作为信息学科相关专业一门重要的专业课程,在整个教学体系中的地位举足轻重。大学教学模式在MOOC风潮的推动下,需要做出一定的创新和调整。在全球MOOC风潮背景下,一些国外大学已经积极行动,基于此国内高校也需要秉持不断创新的意识,并将其落实到行动中。通过对混合学习的MOOC、SPOC进行创新性的研究,文章基于《IT项目管理》课程,探索混合式教学模式,并对其进行课程实践,我们发现更适合国内大学高等工程教学模式的为SPOC。2018年教育部新工科研究与实践项目“新工科人才的创新创业能力培养探索”2017年福建省教育厅本科高校教育教学改革研究项目“‘双一流’背景下数字媒体特色专业建设探索（FBJG20170302）”2017年厦门大学创新创业课程建设项目“大学生创新与创业实训（KC201702007）

在《IT项目管理》课程中实施“课程思政”的路径探索

为充分发挥"课程思政"在《IT项目管理》课程中的价值作用,实现知识传授与价值引领同频共振,笔者从在《IT项目管理》课程中实施"课程思政"的必要性和现实意义入手,对其进行了全面而深入地分析,并在此基础上探究了在《IT项目管理》课程中实施"课程思政"的路径。2018年教育部新工科研究与实践项目“新工科人才的创新创业能力培养探索”2017年福建省教育厅本科高校教育教学改革研究项目“‘双一流’背景下数字媒体特色专业建设探索（项目编号：FBJG20170302）”2017年厦门大学创新创业课程建设项目“大学生创新与创业实训（项目编号：KC201702007）

大数据对我国高校教育发展的影响探究基于移动平台的翻转课堂教学研究

大数据对高校教育的发展的影响体现在多面,本文主要分析大数据对高校教育的积极影响和消极影响,探究高校教育运用大数据技术得到有效发展的策略。2017年福建省教育厅,“双一流”背景下数字媒体特色专业建设探索,项目编号:FBJG20170302;;2018年教育部首批“新工科”研究与实践项目,新工科人才的创新创业能力培养探索——以厦门大学国家示范性软件学院为

Immune genetic algorithm based on meta-population

自然meta-种群中局部种群之间存在相对隔离和种群个体冒险迁徙的机制,提出了一种基于meta-种群理论的免疫遗传算法。该算法模拟了自然meta-种群中局部种群克隆、生殖、变异和自然灭绝等自然过程。其主要步骤包括初始种群,种群及其个体适应度计算,选择,克隆变异、交叉生殖、含记忆B细胞个体克隆和局部种群灭绝及其最优个体的冒险迁徙等。该算法的特点是模拟了meta-种群的自然机制,具有并行性,能够产生高适应能力的个体并不断地更新,直到最优个体的出现。对两种问题进行了模拟实验,并与普通遗传算法IMA进行了比较,结果表明所提出的算法能以较少的迭代次数完成最优解的寻找。There are the isolation correspondingly and the migration of risk between the populations in the meta-population.So this paper proposed a new optimization algorithm based on the meta-population theory.The algorithm simulated the natural process of the meta-population mechanism,such as initial the populations,the fitness of the population and the individual,selecting,cloning and mutating,crossover procreating,cloning of the mnemonic B cells,the depopulation of the sub-population,and the migration of risk of the best individual.The advantages were that the algorithm simulated the meta-population's natural mechanism,produced and updated the good optimum until the best one appeared,and had the parallelism.The method was utilized to optimize the two problems,the simulation results show that the algorithm can find the better optimum than the common IGA at the same iterative times.国家自然科学基金资助项目(60672018);; 厦门大学院士基金资助项

Implementation of Character Animation via BVH in OGRE

OgrE是一个被广泛使用的开源三维图形渲染引擎。为了提高角色动画的制作效率,应该减少一些中间转换的环节,本文提出采用解析标准bVH文件的方法:通过结构体函数直接将解析后的数据加载到内存中,利用OgrE引擎对其进行实时渲染。实验结果证明,在OgrE引擎中,解析后的bVH文件的运动数据能够成功驱动模型,并且实现高逼真的3d渲染效果。OGRE is a popular open-source 3D graphic rendering engine.To improve the efficiency of implementing character animation,standard BVH files should be exploited to reduce the workload of intermediate transformation.The structure functions of the BVH files is used to parse the animation data and the parsed data,which is loaded directly to the memory,and then real-time rendering is implemented in OGRE engine.The experiment results demonstrate that parsed BVH files can successfully drive the model,obtaining vivid and brilliant 3D rendering effect.福建省自然科学基金计划资助项目(F0910149;S0850028);福建省软科学研究计划资助项目(2010R0091);厦门市科技计划项目(3502Z20103001);泉州市技术研究与开发重点项目(2009G29

Feature extraction and automatic recognition of plant leaf using artificial neural network

Plant recognition is an important and challenging task. Leaf recognition plays an important role in plant recognition and its key issue lies in whether selected features are stable and have good ability to discriminate different kinds of leaves. From the view of plant leaf morphology (such as shape, dent, margin, vein and so on), domain-related visual features of plant leaf are analyzed and extracted first. On such a basis, an approach for recognizing plant leaf using artificial neural network is brought forward. The prototype system has been implemented. Experiment results prove the effectiveness and superiority of this method

Study on knowledge base verification based on Petri nets

The comparison of rule pairs is usually involved in traditional approaches to verify knowledge base. The efficiency of these approaches is low when used in the verification of large-scale knowledge base because of the comparison. An alternative method of detecting logical errors in knowledge base is presented in this paper. This is achieved by analyzing the reachability and the transition sequence of Petri nets which is the established model of rule base

The Research of Missing Value Estimation of Gene Sequence Based on Improved KNN

Gene based data mining has been received wider and wider attention as gene carries genetic information of living creature. While mining gene information, one of the tasks is to estimate the missing values reasonably and effectively, so as to reflect the original information of gene sequence. By analyzing the theory of KNN (K nearest neighbor algorithm), an improved KNN for gene sequence was proposed, which resolves the problem of missing values while mining gene data. Results show the feasibility of the algorithm with experiments using data from genbank

右美托咪定受体依赖性增强巨噬细胞吞噬功能

【目的】研究右美托咪定对巨噬细胞吞噬功能的影响并探讨其可能的机制。【方法】RAW264.7细胞分成对照组（control）、右美托咪定组（DEX）、BRL44408+右美托咪定组（BRL44408+DEX）。Western blotting检测α2A肾上腺素受体、p-Akt、Akt的表达，Phagocytosis Assay Kit（IgG PE）检测巨噬细胞的吞噬能力。【结果】RAW264.7细胞上有α2A肾上腺素受体的表达；右美托咪定能够增强巨噬细胞的吞噬能力（P<0.001），BRL44408逆转巨噬细胞吞噬能力的增强（P<0.001）；右美托咪定使RAW264.7细胞的Akt通路激活，BRL44408的使用抑制Akt通路的激活（P<0.01）。【结论】右美托咪定可能通过α2A肾上腺素受体激活Akt通路，进而增强巨噬细胞的吞噬功能