A decomposition heuristics for the container ship stowage problem

In this paper we face the problem of stowing a containership, referred to as the Master Bay Plan Problem (MBPP); this problem is difficult to solve due to its combinatorial nature and the constraints related to both the ship and the containers. We present a decomposition approach that allows us to assign a priori the bays of a containership to the set of containers to be loaded according to their final destination, such that different portions of the ship are independently considered for the stowage. Then, we find the optimal solution of each subset of bays by using a 0/1 Linear Programming model. Finally, we check the global ship stability of the overall stowage plan and look for its feasibility by using an exchange algorithm which is based on local search techniques. The validation of the proposed approach is performed with some real life test cases. This work has been developed within the research area: “The harbour as a logistic node” of the Italian Centre of Excellence on Integrated Logistics (CIELI) of the University of Genoa, Italy     

基于课程标准的教学——以常见阴、阳离子的检验为例

以常见的阴、阳离子的检验为例，研究了如何实施基于标准的教学。校本教材的开发为标准、教材、教学、评价的一致性提供保障；以学生应知的和能做的驱动课堂活动；根据达成标准应有怎样的质量表现，试卷编制先于教学设计。课堂上，“教”“学”双方都明确学习目标，教师提供多种策略来满足学生多样的学习需要，如提供工具，搭建脚手架，并以“微”研究性学习的方式展开教学，给学生提供了充分的进步空间。     

毗邻沙漠地区微分博弈模型与宏观环境治理策略研究

工业化发展导致了脆弱的土地进一步沙漠化,沙漠地区政府应综合考虑经济发展与土地沙漠化导致的生态质量降低。通过构建两个沙漠化地区微分博弈模型,研究了两个地区的沙漠治理问题。研究结果表明,提高工业生产排放技术或沙漠治理技术均能够提高均衡经济产出水平,在工业生产收益系数较高的情况下也能够提高沙漠治理投入水平,并且两种技术提高存在交互效应;只有对生产排放技术水平和沙漠治理技术水平较高的地区,延长地方政府领导任期有利于沙漠治理;实现沙漠完全治理情况下控制土地再沙化的治理投入低于控制沙漠稳定在一定规模的治理投入。     

HACCP体系的原理

论述了美国从１９９７年１２月１８日零时起执行的并被国际认同的ＨＡＣＣＰ体系的原理，对我国水产品加工企业出口产品与编制产品的ＨＡＣＣＰ计划有重要指导作用。     

Probabilistic approaches to compute uncertainty intervals and sensitivity factors of ultrasonic simulations of a weld inspection

For comprehension purpose, numerical computations are more and more used to simulate the propagation phenomena observed during experimental inspections. However, the good agreement between experimental and simulated data necessitates the use of accurate input data and thus a good characterization of the inspected material. Generally the input data are provided by experimental measurements and are consequently tainted with uncertainties. Thus, it becomes necessary to evaluate the impact of these uncertainties on the outputs of the numerical model. The aim of this study is to perform a probabilistic analysis of an ultrasonic inspection of an austenitic weld containing a manufactured defect based on advanced techniques such as polynomial chaos expansions and computation of sensitivity factors (Sobol, DGSM). The simulation of this configuration with the finite element code ATHENA2D was performed 6000 times with variations of the input parameters (the columnar grain orientation and the elastic constants of the material). The 6000 sets of input parameters were obtained from adapted statistical laws. The output parameters (the amplitude and the position of the defect echo) distributions were then analyzed and the 95% confidence intervals were determined.     

晶硅太阳电池原位光老化及热致输运机理

为研究晶体硅太阳电池在标准模拟光条件下的输出特性变化规律和电池内部载流子输运特性,采用原位光老化技术对被测电池进行光照处理,按标准测试实验流程测量电池的伏安特性及光谱响应等参量,发现原位光老化后太阳电池伏安特性各项参量衰减,导致电池效率降低;短波段光谱响应微量下降,是由于原位光老化过程中电池表面产生极微量的面缺陷导致经过硅表面的微量载流子被复合;而长波段响应明显降低,是由于晶硅内大量体缺陷被激活导致长波载流子在经过硅材料内部时被复合.随后将光老化后电池退火并测量比对电池各项特性参量,结果表明,退火对光老化后电池内部深层体缺陷具有较好的修复功能,但对浅层面缺陷没有修复功能,最终造成电池伏安特性参量和光谱响应只得到部分恢复.     

中国进口食品安全风险评估的统计学方法

近年来,随着对外贸易的快速发展和人民生活水平的不断提高,我国已经成为食品进口大国。运用科学的方法优化检验资源配置,强化对进口食品安全的风险管理,是一个关系到人民福社的重大问题。国际上通行的做法是对不同种类的食品和检测项目的潜在风险进行评估,并根据评估结果制定有针对性的监督抽检计划,使得更多的检验资源可以投入到对高风险产品和项目的监管中去。我国在这方面的管理实践才刚刚起步,急需建立一套符合我国食品进口自身特点和管理需求的风险评价模型和相应的估计方法。本文借鉴了其它国家的相关做法,并结合我国进口食品的管理需求和历史检测数据的特点,制定了一套完整的风险评价和估计方法。     

管式炉中半导体激光器巴条Au80Sn20焊料封装研究

为了提高半导体激光器的封装质量和效率,引入管式炉利用夹具进行批量封装。由于封装质量的好坏直接影响半导体激光器的输出特性和使用寿命,利用MOCVD生长808 nm芯片,重点分析了管式炉温度和封装时间对半导体激光器巴条双面金锡封装质量的影响。利用X射线检测、结电压、光电特性参数和smile效应测试手段,确定了管式炉封装半导体激光器巴条的最优封装条件,为以后的产业化提供了指导意义。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.