β-hydroxyacyl-coa-dehydrogenase (HADH) activity of unfrozen and frozen—thawed frog (Rana esculenta) legs

The β-hydroxyacyl-CoA-dehydrogenase (HADH) activity of unfrozen and thawed frog legs was investigated. The enzyme was extracted by either immersing frog legs in phosphate buffer 0.1 M, pH 6.0 at 25°C for 15 min or pressing them between trichinoscopy glasses. The enzyme activity was assayed using acetoacetyl-CoA as substrate and measured spectrophotometrically at 340 nm. It was possible by both extraction methods to distinguish between thawed and unfrozen samples although when the juice was obtained by pressing the HADH activity of the dilution was ～ 1.5 times higher than that obtained by immersion. The HADH activity was significantly higher (P≤0·001) in frozen-thawed frogs than in unfrozen legs because during freezing there is a release of HADH. No significative differences were found in the HADH activity in samples frozen in the temperature range -10 to -196°C. HADH activity was not affected by the storage time in crushed ice up to 6 days.     

改进的反向蛙跳算法求解函数优化问题

针对混洗蛙跳算法在求解连续函数优化问题中出现的收敛速度慢、求解精度低的缺点,提出了一种基于反向学习策略的改进算法,在种群初始化和进化过程中分别加入反向操作,产生更靠近优质解的种群,从而提高了算法的全局寻优能力,促进了算法收敛。实验仿真表明,新算法在寻优效率、计算精度等方面均优于原算法。     

一种单种群混合蛙跳算法

针对SFLA算法运行速度较慢、在优化部分函数问题时精度不高和易陷入局部最优的缺点,提出了一种单种群混合蛙跳算法SPSFLA。该算法采用单个种群,无需对整个种群进行排序,每个个体通过向群体最优个体和群体中心位置学习进行更新。如果当前个体学习没有进步,则对群体最优个体进行变异,并用变异的结果替代当前个体,加快了算法的运行速度和收敛速度,提高了优化精度。仿真实验结果表明,该算法具有更好的优化性能。     

高强度复合材料整铸辙叉前期研究

辙叉是线路上工作条件最为严峻的轨道部件之一。用高强度复合材料整铸的辙叉替代普通辙叉的研究具有重要意义。以ＰＤ３钢轨钢作为基体材料，在其表面熔合上一层新型具有更好耐磨性能的材质。新材料１、新材料２分别在ＰＤ３基础上把Ｖ的含量提高到０．１５％～０．２５％和０．３５％～０．４５％。采用合适的工艺措施，使新材料１、２与ＰＤ３轨道钢很好地熔合在一起。它们的σｂ、ａｋ、δ、τｂ均不低于ＰＤ３，而Ｈｖ却有了提高。     

改进混合蛙跳算法在蔬菜总黄酮软测量中的应用

针对蔬菜总黄酮化学物提取过程复杂、非线性和生物参数难以在线测量等特点,提出了基于改进混合蛙跳算法优化最小二乘支持向量机的蔬菜总黄酮软测量模型。该模型对标准混合蛙跳算法进行改进,采用反向学习的种群初始化策略,确保个体分布的均匀性;并根据群体适应度方差大小,动态调整变异概率,使算法避免陷入局部最优;最后采用改进的混合蛙跳算法对最小二乘支持向量机的参数进行寻优,实现蔬菜总黄酮软测量。仿真结果表明,基于改进混合蛙跳算法的最小二乘支持向量机软测量模型具有测量精度高,稳定性好的优点,有利于蔬菜总黄酮化学物测量工程的实际应用。     

基于信息融合度传递的频域徙动入侵特征挖掘算法

在功率自激混合组合网络中,路由之间的相群特征相异性会产生谐振信号,因此需要有效挖掘入侵信号的频域徙动特征来实现对入侵信号的拦截。传统方法采用混合蛙跳算法挖掘入侵特征并且聚类中心矢量向模糊边缘贴近,因此搜索和挖掘精度不高。提出了一种基于混合蛙跳最优模因组信息融合度传递的频域徙动入侵特征挖掘算法。构建功率自激组合网络的系统模型和入侵信号数学模型,基于频域谐振慢变衰落幅度均衡原理,得到多源网络攻击源信号在相干点积功率累积尺度坐标,采用多普勒频移模糊搜索对入侵信号进行平滑处理,计算入侵信号的多普勒频移状态空间固有模态函数,得到入侵信号的频域特征包络幅度估计值。采用IIR滤波算法,对信号进行降噪滤波处理,提高信号的纯度,提出基于信息融合度传递的混合蛙跳入侵信号检测算法,优化特征挖掘结果,完成入侵信号的频域徙动特征挖掘算法改进。仿真实验结果表明,该算法能准确挖掘入侵信号的频域徙动特征,特征的波脊亮点明显,在低信噪比下提高了入侵信号的检测性能。     

基于云模型和余弦跳跃权重的改进蛙跳算法

标准蛙跳优化算法(SFLA)有寻优精度低和易陷入局部收敛区域的缺点, 为提高其性能, 提出一种基于云模型局部搜索和余弦跳跃权重更新位置的改进蛙跳算法(CSFLA). 首先通过Tent混沌映射和反向学习生成种群, 使种群的分布更均匀, 利用云模型的正态特性对子群中的优秀个体的所在区域进行探索. 同时, 对种群中其他个体引入基于余弦函数的跳跃步长权重, 使该权重在整个迭代过程中由高以不同的速率下降, 提高种群的全局搜索能力. 最后, 将CSFLA与多个优化算法在不同类型的测试函数上进行了比较. 结果表明, CSFLA具有更好的收敛速度和精度, 能有效找出全局最优解. 并且将改进算法应用至旅行商问题, 该算法可以找到总路程更短的路线.     

Test Case Prioritization in Unit and Integration Testing: A Shuffled-Frog-Leaping Approach

Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product. Due to resource constraints, when software is subjected to modifications, the drastic increase in the count of test cases forces the testers to opt for a test optimization strategy. One such strategy is test case prioritization (TCP). Existing works have propounded various methodologies that re-order the system-level test cases intending to boost either the fault detection capabilities or the coverage efficacy at the earliest. Nonetheless, singularity in objective functions and the lack of dissimilitude among the re-ordered test sequences have degraded the cogency of their approaches. Considering such gaps and scenarios when the meteoric and continuous updations in the software make the intensive unit and integration testing process more fragile, this study has introduced a memetics-inspired methodology for TCP. The proposed structure is first embedded with diverse parameters, and then traditional steps of the shuffled-frog-leaping approach (SFLA) are followed to prioritize the test cases at unit and integration levels. On 5 standard test functions, a comparative analysis is conducted between the established algorithms and the proposed approach, where the latter enhances the coverage rate and fault detection of re-ordered test sets. Investigation results related to the mean average percentage of fault detection (APFD) confirmed that the proposed approach exceeds the memetic, basic multi-walk, PSO, and optimized multi-walk by 21.7%, 13.99%, 12.24%, and 11.51%, respectively.     

边坡临界滑动面确定的蛙跳算法

将蛙跳算法引入到边坡极限平衡稳定性分析中,详细介绍了蛙跳算法的流程,并对典型土坡进行了计算分析,结果表明:蛙跳算法搜索到的最危险滑动面上较多的点位于软弱夹层内,所得到的安全系数比遗传算法结果更为合理。通过正交试验分析了蛙跳算法各个参数对计算结果的影响,并给出了推荐的参数取值。     

超声冲击对高锰钢辙叉组织与性能的影响

利用超声冲击技术对高锰钢辙叉试样表面进行强化处理。用维氏显微硬度仪测量分析横截面显微硬度分布,用金相显微镜和扫描电镜观察经超声冲击后的组织变化。试验结果表明:经超声冲击处理后,试样表面的显微硬度显著提高,且随冲击功率的提高逐渐增大,随距表面距离的增大而减小;试样表层经超声冲击产生高密度滑移线,随着距表面距离的增大,由多系滑移逐渐过渡到单系滑移,滑移带与基体没有明显界限;试样表面经超声冲击发生剧烈的塑性变形,冲击功率越大,塑性变形越剧烈,变形层越厚。