A frequency-aware and energy-saving strategy based on DVFS for Spark

The Journal of Supercomputing - With the fast growth of big data applications, it has brought about a huge increase in the energy consumption for big data processing in Cloud data centers. In this...     

Interactive genetic algorithms with large population and semi-supervised learning

Interactive genetic algorithms are effective methods of solving optimization problems with implicit (qualitative) criteria by incorporating a user's intelligent evaluation into traditional evolution mechanisms. The heavy evaluation burden of the user, however, is crucial and limits their applications in complex optimization problems. We focus on reducing the evaluation burden by presenting a semi-supervised learning assisted interactive genetic algorithm with large population. In this algorithm, a population with many individuals is adopted to efficiently explore the search space. A surrogate model built with an improved semi-supervised learning method is employed to evaluate a part of individuals instead of the user to alleviate his/her burden in evaluation. Incorporated with the principles of the improved semi-supervised learning, the opportunities of applying and updating the surrogate model are determined by its confidence degree in estimation, and the informative individuals reevaluated by the user are selected according to the concept of learning from mistakes. We quantitatively analyze the performance of the proposed algorithm and apply it to the design of sunglasses lenses, a representative optimization problem with one qualitative criterion. The empirical results demonstrate the strength of our algorithm in searching for satisfactory solutions and easing the evaluation burden of the user.     

Improved stability conditions for systems with interval time-varying delay

The paper is concerned with the stability of linear systems with interval time-varying delay. Through constructing a new augmented Lyapunov-Krasovskii functional (LKF) which contains some quadruple-integral terms and estimating the time derivative of the LKF less conservatively, new stability criteria are derived without introducing any free matrices. Moreover, by proving the positive definiteness of the LKF with some integral inequalities, the constraints on some functional parameters are relaxed and the conservatism of the obtained results are further reduced. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

Study on diffusion welding SiCp/ZL101 with Cu interlayer

Through the vacuum diffusion welding SiCp/ZL101 aluminum with Cu interlayer,the effect of welding parame-ter and the thickness of Cu on the welded joint property was investigated,and the optimal welding parameters were putforward at the same time.The microstructure of joint was analyzed by means of optical-microscope,scanning electron mi-croscope in order to study the relationship between the macro-properties of joint and the microstructure.The results showthat diffusion welding with Cu interlayer could be used for welding aluminum matrix composites SiCp/ZL101 successfully.     

铁路军事运输柔性捆绑加固器设计

为进一步提高军事装备铁路运输捆绑加固效率和运输安全性,针对现有加固器材存在的问题,从加固器适应性、可靠性和便利性等3个方面,分析铁路军事运输柔性捆绑加固器的设计需求;提出柔性织带和棘轮收紧器结构设计方案及其功能;论证铁路军事运输柔性捆绑加固器的技战术指标.     

岗位体验式教学法在雷达装备实践教学中的应用

针对雷达装备实践教学中演示式教学法对于学员能力的拓展和装备的综合运用等方面存在的问题,将岗位体验式教学法运用于雷达装备实践教学中.首先分析岗位体验式教学法的基本内涵;然后提出前期准备、场景设置、教学实施、交流研讨和总结讲评等5个方面的具体实施方法,进行实例分析;最后给出岗位体验式教学法的实施效果.教学实践结果验证了该方法的有效性.     

PREDICTION OF THE PROBABILITY OF SPHEROIDIZATION IN NODULAR CAST IRON BY PARAMETRIC DIAGRAM OF CHEMICAL BOND

<正> 本文试图从化学键理论出发,探讨石墨球化的规律。鉴于用键参数图法总结与化学键有关的规律性往往见效,故本文从球化剂元素和反球化元素在键参数图中的分布规律入手进行研究。 球化剂元素(或反球化元素)对石墨球化的影响应与该元素和C_(石墨)间的相互作用有关,其键参数函数写成如下形式:     

热压变形对灰口铸铁石墨形态的影响

研究了灰口铸铁(HTl50)在900℃大压下量塑性变形后石墨的分布形态，结果表明：随着压下量的增加，石墨片逐渐趋于平行分布；变形过程中发生了碳的回溶，同时伴随着石墨片的断裂；石墨片体积分数及片间距随压下量的增加而逐渐减少。     

Preparation of Protein-Stabilized β-Carotene Nanodispersions by Emulsification–Evaporation Method

This work was initiated to prepare protein-stabilized β-carotene nanodispersions using emulsification–evaporation. A pre-mix of the aqueous phase composed of a protein and hexane containing β-carotene was subjected to high-pressure homogenization using a microfluidizer. Hexane in the resulting emulsion was evaporated under reduced pressures, causing crystallization and precipitation of β-carotene inside the droplets and formation of β-carotene nanoparticles. Sodium caseinate (SC) was the most effective emulsifier among selected proteins in preparing the nanodispersion, with a monomodal β-carotene particle-size distribution and a 17-nm mean particle size. The results were confirmed by transmission-electron microscopy analysis. SC-stabilized nanodispersion also had considerably high ζ-potential (−27 mV at pH 7), suggesting that the nanodispersion was stable against particle aggregation. Increasing the SC concentration decreased the mean particle size and improved the polydispersity of the nanodispersions. Nanodispersions prepared with higher β-carotene concentrations and higher organic-phase ratios resulted in larger β-carotene particles. Although increased microfluidization pressure did not decrease particle size, it did improve the polydispersity of the nanodispersions. Repeating the microfluidization process at 140 MPa caused the nanodispersions to become polydisperse, indicating the loss of emulsifying capacity of SC due to protein denaturation.