建筑群体综合控爆技术

本项工程采用铵梯炸药、水胶炸药、毫秒延期电雷管等爆破器材，运用微差起爆，定向折叠，水压爆破等控制爆破技术，成功地拆除了总面积达３８００ｍ２的建筑群，达到了爆破噪声低，震动小，碎片坍塌范围小，尘土飞扬少等原设计目标。     

基于Profibus-DP的水泥自动配料系统设计

针对某水泥厂配料生产线使用的PLC控制系统存在连线多、距离远、故障点多等缺陷,提出了一种基于Profibus-DP的水泥自动配料系统的改造方案,详细介绍了系统的硬件与软件的设计。该系统以西门子S7-300 PLC为主控制器,具有配料系统运行状态监控、运行异常报警、运行参数修改、实时数据自动生成、历史数据报表查询或打印等功能。     

Minimizing a nonlinear function under a fuzzy max-t-norm relational equation constraint

This work studies a nonlinear optimization problem subject to fuzzy relational equations with max-t-norm composition. Since the feasible domain of fuzzy relational equations with more than one minimal solution is non-convex, traditional nonlinear programming methods usually cannot solve them efficiently. This work proposes a genetic algorithm to solve this problem. This algorithm first locates the feasible domain through the maximum solution and the minimal solutions of the fuzzy relational equations, to significantly reduce the search space. The algorithm then executes all genetic operations inside this feasible domain, and thus avoids the need to check the feasibility of each solution generated. Moreover, it uses a local search operation to fine-tune each mutated solution. Experimental results indicate that the proposed algorithm can accelerate the searching speed and find the optimal solution.     

SOA架构在辽河流域报表管理系统的研究与实践

报表服务是辽河流域水环境相关管理系统中核心业务需求之一.随着水环境治理范围扩大,报表服务需求多样化,现有分散式报表管理方式已不能满足用户实际需求.对此,从异构系统中报表实际业务需求出发,结合SOA架构模型松散耦合与可重用性等特点,提出了一种基于SOA架构的报表管理系统.解决了多系统之间重复开发与数据共享等问题.本文通过对报表业务核心功能及流程的提炼,建立了相应的服务模型,根据对不同服务的组合和调用,实现了支持多系统并发访问的报表管理系统.     

A Low-Cost Checkpointing Technique for Distributed Databases

For distributed databases, checkpointing is used to ensure an efficient way to perform global reconstruction. However, the need for global reconstruction is infrequent. Most current checkpointing approaches for distributed databases are too expensive during run time. Some of them allow the checkpointing process to run in parallel with normal transactions at the cost of more data and resource contention, which in turn causes longer response time for normal transactions. Thus, an efficient way to checkpoint distributed databases is needed to avoid degrading the system performance. This paper presents a low-cost solution, called Loosely Synchronized Local Fuzzy Checkpointing (LSLFC), to these problems. LSLFC supports global reconstruction, and our performance study shows that LSLFC has little overhead during run time.     

Active Store Window: Enabling Far Store-Load Forwarding with Scalability and Complexity-Efficiency

Conventional dynamically scheduled processors often use fully associative structures named load/store queue (LSQ) to implement the value communication between loads and the older in-flight stores and to detect the store-load order violation.But this in-flight forwarding only occupies about 15% of all store-load communications,which makes the CAM-based micro-architecture the major bottleneck to scale store-load communication further.This paper presents a new micro-architecture named ASW (short for active store window).It provides a new structure named speculative active store window to implement more aggressively speculative store-load forwarding than conventional LSQ.This structure could forward the data of committed stores to the executing loads without accessing to L1 data cache,which is referred to as far forwarding in this paper.At the back-end of the pipeline,it uses in-order load re-execution filtered by the tagged SSBF (short for store sequence bloom filter) to verify the correctness of the store-load forwarding.The speculative active store window and tagged store sequence bloom filter are all set-associate structures that are more efficient and scalable than fully associative structures.Experiments show that this simpler and faster design outperforms a conventional load/store queue based design and the NoSQ design on most benchmarks by 10.22% and 8.71% respectively.     

基于选择性集成的最大化软间隔算法

当前,boosting集成学习算法研究主要集中于最大化弱学习器凸组合的间隔或软间隔,该凸组合几乎使用了生成的所有弱学习器,然而这些弱学习器间存在大量的相关性和冗余,增加了训练和分类过程的时空复杂度.针对这一问题,在LPBoost基础上提出了一种选择性boosting集成学习算法,称为SelectedBoost.在每次迭代生成新的弱学习器以后,通过计算新生成的弱学习器与已有弱学习器的相关度和差异度,并结合当前集成的强学习器的准确率来判断是否选择该弱学习器.另外,当前的一系列boosting算法(如AdaBoost,LPBoost,ERLPBoost等),本质上是基于已生成的1个或者多个弱学习器来更新样本权重,但与弱学习器相比,强学习器更能代表当前的决策面.因此,SelectedBoost通过在带约束的间隔最大化问题中引入更加严格的强学习器边界约束条件,使得该算法不仅参考弱学习器边界,同时还参考已生成的强学习器来更新样本权重,进而提高算法的收敛速度.最后,与其他有代表性的集成学习算法进行实验比较,结果表明,该方法在收敛率、分类准确性以及泛化能力等方面均具有比较明显的优势.     

基于事物特性表的敏捷设计系统

由于传统的产品设计流程存在较多弊端,如何缩短产品设计周期显得尤为重要。借助描述标准化和规范化的产品信息的事物特性表,基于大批量定制产品的开发设计技术上,以Solidworks为具体应用对象,研究了基于事物特性表进行产品变型设计的原理及关键技术,通过二次开发技术,实现了产品变型设计的方法和过程。最后,通过应用实例,验证了方法的可行性,并且给出了基于事物特性表的敏捷设计系统流程。     

GaAlAs红外发光二极管功率老化对其1/f噪声特性的影响

在可靠性筛选中检测具有潜在损伤的器件一直是个难题.对GaA lAs红外发光二极管(IRLED)功率老化前后低频噪声的测量发现,1/f噪声幅值与偏置电流的γ次方成正比(小电流区γ=1,在大电流区γ≈2),且老化后1/f噪声幅值比老化前增大2个数量级.基于载流子数涨落和迁移率涨落机制建立了一个GaA lAs IR LED的1/f噪声模型,分析结果表明GaA lAs IR LED的1/f噪声在小电流时反映体陷阱特征,大电流时反映激活区陷阱特征,1/f噪声的增加归因于功率老化诱生的界面陷阱和表面陷阱,1/f噪声可以用来检测GaA lAs IR LED s的潜在缺陷.     

L-苹果酸对苹果酸天冬氨酸穿梭转运蛋白及酶基因表达的作用研究

采用半定量RT-PCR方法,对小鼠给予L-苹果酸后肝线粒体苹果酸天冬氨酸穿梭相关的两种线粒体酶:线粒体天冬氨酸氨基转移酶(mitochondrialaspartateaminotransferase,mAST)及线粒体苹果酸脱氢酶(mitochondrialmalatedehydrogenase,mMDH)及线粒体内膜上的天冬氨酸谷氨酸转运蛋白(AGC)与α-酮戊二酸苹果酸转运蛋白(OMC)的基因表达进行检测,探讨了L-苹果酸对肝线粒体苹果酸天冬氨酸穿梭的关键酶及转运蛋白mRNA表达规律。半定量RT-PCR结果表明:剂量组小鼠肝线粒体转运蛋白AGCmRNA的表达显著高于空白对照组,而mAST、mMDH及转运蛋白OMCmRNA的表达无显著性差异。由此可知,L-苹果酸能促进TCA循环及苹果酸天冬氨酸穿梭,其分子生物学机理与L-苹果酸提高AGC的基因表达水平有关。