矿山工程建设项目造价管理信息系统设计

为提高矿山工程建设项目造价管理水平,设计了矿山工程建设项目造价管理系统。通过分析矿山工程项目的造价组成,并采用三层B/S架构设计系统硬件框架,运用Web服务器传输矿山工程项目各项数据,划分系统功能子系统,并对矿山工程建设项目造价额与价差预备费进行计算,完成系统软件设计。结果表明,该系统能够有效管理矿山工程建设项目造价,并对外部的恶意攻击进行及时报警,系统具有有效性与安全性。     

超分子作用阻尼材料的动态力学模型修正

为提高飞机起落架载荷实测精度，以支柱式起落架结构为研究对象，探讨处理其载荷标定数据的工程方法。首先，对实际受载情况和单向加载工况标定数据的分析，挖掘出三向载荷、缓冲支柱压缩行程与应变码值间的数学关系，将预测的数学关系代入到多向工况的标定数据中，验证了它们的准确性;其次，根据两种标定数据回归方法，提出了对应使用的支柱式起落架载荷-应变标定方程的数学模型;最后，将两种标定方程代回到标定数据中，计算起落架三向载荷，所有反算载荷的误差均在可控范围内，表明标定方程满足精度要求。将标定方程代入实测数据中，实测曲线符合变化规律。该处理方法的应用能有力提高支柱式起落架的起飞-着陆载荷实测和载荷谱编制的准确度。     

优化军工科研项目管理的具体策略

我国的军工科研所成立于上世纪，它以军工项目的科研、预研为主，为我国的国防军工提供研发产品。伴随着我国经济实力的增强和科技军事力量的增长，军工科研院所也转变了原有的工业专属性质，走上了军民两用、寓军于民的道路，并在时代的进步中成为了我国先进装备制造业的重要科研力量和科技创新支柱。凸现军事工业“高、精、尖”的特点，以项目管理的优化为具体策略进行军工科研开发工作。     

Supramolecular Glyco‐nanoparticles Toward Immunological Applications

Glyco‐mimicking nanoparticles (glyco‐NPs) with Förster resonance energy transfer (FRET) donor and acceptor groups formed via dynamic covalent bond of benzoboroxole and sugar from two complementary polymers are prepared. The glyco‐NPs are proved to be quite stable under physiological conditions but sensitive to pH. So the glyco‐NPs can be internalized by dendritic cells with integrity and nontoxicity and then dissociate within the acidic organelles. This particle dissociation is directly observed and visualized in vitro, for the first time via the FRET measurements and fluorescent microscopy. This feature makes controlled release of drug or protein by glyco‐NPs possible, i.e., when model antigen Ovalbumin is loaded in the glyco‐NPs, the released Ovalbumin in dendritic cells stimulates T cells more efficiently than the free Ovalbumin itself as a result of the enhanced antigen processing and presentation. Thus, the results enlighten a bright future of the glyco‐NPs in immunotherapy.     

"人机环管"在煤矿供电安全管理中的应用

制定供电过程中消除安全隐患的针对性措施,可以为矿井安全生产提供必要保障。为探究煤矿供电管理中安全隐患的具体分析方法,首先介绍“人机环管”管理体系的建立过程和核心内容,接着以“人机环管”的管理方法分析了供电管理中的普遍问题。在分析供电管理中的具体问题时,分别得出了“人”“机”“环”“管”4方面的具体措施。分析认为,“人机环管”方法可以有效查找出存在的安全隐患,进而保证煤矿供电系统的安全可靠。     

基于MF-R和AWS密钥管理机制的物联网健康监测大数据分析系统

带有传感器的可穿戴式医疗设备不断生成大量数据，由于数据的复杂性，难以通过处理和分析大数据来找到有价值的决策信息。为了解决这个问题，提出了一种新的物联网体系结构，用于存储和处理医疗应用的可扩展传感器数据（大数据）。所提出的架构主要由两个子架构组成：Meta Fog重定向（MF-R）架构和AWS密钥管理机制。MF-R架构使用Apache Pig和Apache HBase等大数据技术来收集和存储不同传感器设备生成的传感器数据，并利用卡尔曼滤波消除噪声。AWS密钥管理机制使用密钥管理方案，目的是保护云中的数据，防止未经授权的访问。当数据存储在云中时，所提出的系统能够使用随机梯度下降算法和逻辑回归来开发心脏病的预测模型。仿真实验表明，和其他几种算法相比，提出的算法具有更小的误差，且在吞吐量、准确度等方面具有一定的优越性。     

Automated network management and configuration using Probabilistic Trans-Algorithmic Search

Online configuration of large-scale systems such as networks requires parameter optimization within a limited amount of time, especially when configuration is needed as a response to recover from a failure in the system. To quickly configure such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It allocates an experiment budget to each available search algorithm and observes its performance on the system-at-hand. PTAS then probabilistically reallocates the experiment budget for the next round proportional to each algorithm’s performance relative to the rest of the algorithms. This “roulette wheel” approach probabilistically favors the more successful algorithm in the next round. Following each round, the PTAS framework “transfers” the best result(s) among the individual algorithms, making our framework a trans-algorithmic one. PTAS thus aims to systematize how to “search for the best search” and hybridize a set of search algorithms to attain a better search. We use three individual search algorithms, i.e., Recursive Random Search (RRS) (Ye and Kalyanaraman, 2004), Simulated Annealing (SA) (Laarhoven and Aarts, 1987), and Genetic Algorithm (GA) (Goldberg, 1989), and compare PTAS against the performance of RRS, GA, and SA. We show the performance of PTAS on well-known benchmark objective functions including scenarios where the objective function changes in the middle of the optimization process. To illustrate applicability of our framework to automated network management, we apply PTAS on the problem of optimizing link weights of an intra-domain routing protocol on three different topologies obtained from the Rocketfuel dataset. We also apply PTAS on the problem of optimizing aggregate throughput of a wireless ad hoc network by tuning datarates of traffic sources. Our experiments show that PTAS successfully picks the best performing algorithm, RRS or GA, and allocates the time wisely. Further, our results show that PTAS’ performance is not transient and steadily improves as more time is available for search.     

MG410采煤机滚筒辅助叶片板的增设与应用

针对MG170/410-WD滚筒式采煤机在大倾角、仰角、“三软”煤层使用中遗漏在机道中的浮煤多、装煤效率低等问题,通过添加螺旋板数量对采煤机滚筒进行改造。改造后,在滚筒转速不变的情况下,提高抛煤效率,缩短了工作面割煤和工作面空顶时间,提高了装煤效率,从源头上降低了顶板管理的安全风险。     

Levelized cost of energy definition – An economic paradox

Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect.     

A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems

Airline disruptions incurred huge cost for airlines and serious inconvenience for travelers. In this paper, we study the integrated aircraft and crew schedule recovery problem. A two stage heuristic algorithm for the integrated recovery problem is proposed. In the first stage, the integrated aircraft recovery and flight-rescheduling model with partial crew consideration is built. This model is based on the traditional multi-commodity network model for the aircraft schedule recovery problem. The objective of this model also includes minimization of the original crew connection disruption. In the second stage, the integrated crew schedule recovery and flight re-scheduling model with partial aircraft consideration is built. We proposed a new multi-commodity model for the crew schedule recovery. The main advantage of such model is that it is much more efficient to integrate the flight-scheduling and aircraft consideration. New constraints are incorporated to guarantee that the aircraft connections generated in the stage 1 are still feasible. Two stages are run iteratively until no improvement can be achieved. Experimental results show that our method can provide better recovery solutions compared with the benchmark algorithms.