中小企业集群演进动力机制的实证研究

在总结企业集群生成动力,发展动力与锁定效应的基础上,构建了企业集群演进的动力机制模型,利用河北省清河羊绒企业集群的调研数据进行了实证分析,在对各个影响因素的作用机制进行具体分析的基础上,将数据带入"企业集群演进动力作用机制模型",得出来现阶段对集群演进产生影响的主要因素.     

Bone Tissue Response to the Bone-like Tissue Coating on Titanium

The objective of this study was to investigate the effects of mineralized bone nodules, formed in vitro by bone marrow stromal cells(BMSCs), on the new bone formation in bone defect and on implant surface. The mineralized bone nodules were generated by culture of Lewis rats BMSCs on titanium disks in osteogenic induction medium. The gap-healing animal model was used to create the bone defect facing the disk. The titanium disks in the presence of B group or in the absence of NB group bone nodules were randomly placed into one of the rat distal femurs. This self-control design was used to compare the bone formation in defects and on titanium surface, by Micro-CT, fluorescence staining, histological and histomorphometric analysis. The new bone formation parameters in bone defect area of B group were significantly higher than those of NB group at 2 weeks, including bone volume fraction, trabecular thickness and bone area ratio. The bone nodules pre-stained with Alizarin red disappeared mostly at 2 weeks, while the red fluorescence reappeared in the newly formed bone away from the disk surface. For the bone-implant contact, B group showed lower values than NB group at 2 weeks, but no significant difference was found at 4 weeks. Our results indicate that the mineralized bone nodules can be resorbed in vivo and promote the early osteogenesis in the bone defects, and bone nodules may be applicable for new bone generation in bone defect or modification of tissue engineering scaffold.     

超细Al（OH）3的粒度控制研究

采用铝酸钠种子分解法制备超细Al（OH）3.用X射线衍射仪（XRD）表征了样品的晶相组成,用扫描电子显微镜（SEM）观察了样品的形貌,用激光粒度分析仪测定样品的粒度分布.研究了NaOH浓度、NaOH/Al（OH）3摩尔比,分解温度,分解时间、晶种率和搅拌速率等因素对Al（OH）3的粒度的影响.结果表明：NaOH浓度越高,分解温度越低,NaOH/Al（OH）3摩尔比越小,得到的Al（OH）3颗粒的粒度越小.试验条件为：NaOH浓度180 g/L,NaOH/Al（OH）3摩尔比1.15,分解温度40℃,分解时间26 h,晶种率8％,搅拌速率200 rpm时,氢氧化铝颗粒的平均粒度为2.89 μm.     

面向草图检索的小样本增量有偏学习算法

为了解决草图检索相关反馈中小样本训练、数据不对称及实时性要求这3个难点问题,提出了一种小样本增量有偏学习算法.该算法将主动式学习、有偏分类和增量学习结合起来,对相关反馈过程中的小样本有偏学习问题进行建模.其中,主动式学习通过不确定性采样,选择最佳的用户标注样本,实现有限训练样本条件下分类器泛化能力的最大化;有偏分类通过构造超球面区别对待正例和反例,准确挖掘用户目标类别;每次反馈循环中新加入的样本则用于分类器的增量学习,在减少分类器训练时间的同时积累样本信息,进一步缓解小样本问题.实验结果表明,该算法可以有效地改善草图检索性能,也适用于图像检索和三维模型检索等应用领域.     

一种多总线通讯系统的实现

首先讨论了多总线通讯系统的主从式网络构建方法和通讯MBI的功能;其次给出了多总线通讯系统中总线利用率和总线负载的计算方法以及在系统中时基的应用方法。在此基础上,论述了基于ADSP21060,结合1553B总线和RS-422总线的多总线通讯系统的实现,具体包括硬件接口设计和通讯软件的实现。实验表明,多总线通讯系统适用于外部总线负载小于70%,内部总线负载小于40%的通讯系统,具有普遍意义。     

时变不确定非线性系统自适应滑模跟踪控制

针对一般的具有时变且界未知的非线性不确定性的单输入多输出非线性系统,提出一种自适应滑模跟踪控制器的框架.在该框架内,系统的时变且界未知的非线性不确定性可以通过函数逼近技术(FAT)表示成为一组正交基函数序列的组合,并通过滑模控制技术和直接Lyapunov方法获得基函数系数的更新律以及对不确定性逼近误差的在线自适应补偿,从而得到自适应的滑模控制律.所提出的基于函数逼近技术的自适应滑模跟踪控制策略在直流电机跟踪控制系统实验装置上进行了实际控制实验,并进行了性能的对比与分析.     

Research and Implementation of Parallel Artificial Fish Swarm Algorithm Based on Ternary Optical Computer

Mobile Networks and Applications - Artificial fish swarm algorithm (AFS) is used in the field of function optimization problems widely. The traditional AFS algorithm has some problems such as long...     

Applying deep learning in football ankle injury for value of high-power magnetic resonance bioimaging evaluation

The Journal of Supercomputing - This study was to evaluate the performance of magnetic resonance imaging (MRI) reconstruction algorithm based on convolutional neural network (CNN) in the diagnosis...     

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.     

基于MP算法的快速地震信号谱分析

MP(Matching Pursuits)算法以其灵活的自适应性,取得了广泛的应用,但依然存在计算量大的应用瓶颈问题.为了解决传统MP算法运算量大的问题,首先对MP算法的原理进行了介绍,然后针对其计算量大的问题提出了一种基于遗传算法的快速算法,有效地降低了MP算法的运算量,较好地解决了运算量大的问题.最后利用MP算法对地震信号进行了谱分析,消除了Wigner算法中的交叉项,从而有效地揭示了地震信号的时频信息.结果表明,改进后的MP算法可以作为地震信号谱分析的有效算法,为烃类检测和储层描述等提供有地效的手段.