绿色水处理剂氢氧化镁应用的研究进展

氢氧化镁(氧化镁)被称为绿色安全的废水处理剂,本文评述了氢氧化镁在环境保护方面的研究与应用进展,包括工业废水中铅、铬、镍等重金属离子的去除和酸性废水的中和处理,并列举了氢氧化镁对一些实际废水的良好处理效果,包括其对一些特殊废水如含硼废水和放射性废水的处理效果,最后展望了其在生产和应用方面的发展前景。     

Growth Mechanisms for SiC–AlN Solid Solution Crystals Prepared by Combustion Synthesis

AlN–SiC solid solution particles with a variety of morphologies including faceted polyhedrons with or without ledges; hexagonal platelets; hexagonal columns with a hexagonal plate or a pyramidal cap; and interpenetrating cones, have been found in the combustion products of a mixture of Al, Si, and carbon black under a nitrogen pressure of 10 MPa. Combustion temperature (the growth temperature of crystals) is the most important factor controlling the morphology of crystals formed in the combustion product. When temperatures are close to the melting point of the solid solutions, a small driving force for nucleation and long distances of surface migration make nucleation on the basal plane difficult, and thus the solid solution particles tend to grow as platelets. Supersaturation is the second key factor influencing crystal growth. At relatively low temperatures, a low supersaturation at the large pores renders nucleation difficult and the solid solution particles tend to grow as platelets. At relatively low temperatures and high supersaturation, a relatively high driving force for nucleation and short mean distances of surface migration promote the growth of AlN–SiC solid solutions as polyhedrons. The formation of the ledges on the polyhedral particles is attributed to the differences in the evaporation rates and the deposition rates between Al and Si. At relatively low temperatures and an intermediate supersaturation, the solid solution particles grow as prismatic columns. The formation of the prismatic columns with a hexagonal plate, or a pyramidal cap, is attributed to a sudden change of temperature during combustion. A possible growth mechanism for the AlN–SiC solid solution cones is proposed.     

Efective Error-Tolerant Keyword Search for Secure Cloud Computing简

The existing solutions to keyword search in the cloud can be divided into two categories： searching on exact keywords and searching on error-tolerant keywords. An error-tolerant keyword search scheme permits to make searches on encrypted data with only an approximation of some keyword. The scheme is suitable to the case where users＇ searching input might not exactly match those pre-set keywords. In this paper, we first present a general framework for searching on error-tolerant keywords. Then we propose a concrete scheme, based on a fuzzy extractor, which is proved secure against an adaptive adversary under well-defined security definition. The scheme is suitable for all similarity metrics including Hamming distance, edit distance, and set difference. It does not require the user to construct or store anything in advance, other than the key used to calculate the trapdoor of keywords and the key to encrypt data documents. Thus, our scheme tremendously eases the users＇ burden. What is more, our scheme is able to transform the servers＇ searching for error-tolerant keywords on ciphertexts to the searching for exact keywords on plaintexts. The server can use any existing approaches of exact keywords search to search plaintexts on an index table.     

氧化焰烧成铜红釉

本研究以SiC作还原剂，采用氧化焰烧成，试制成功了在1250～1260℃下烧成的铜红釉，克服了传统的还原焙烧成方法的不足，简化了生产工艺，提高了铜红釉的成品率。     

Influence of epoxy resin on the morphological and rheological properties of PBT/ABS blends compatibilized by ASMA

Polybutylene terephthalate (PBT)/acrylonitrile–butadiene–styrene (ABS) copolymer blends compatibilized by a mixture of styrene–acrylonitrile–maleic anhydride (ASMA) copolymers and epoxy resin (EP) were prepared through melt reactive extrusion. The morphological, rheological, and mechanical properties of these blends were studied. The epoxy functional groups of EP can react with anhydride groups of ASMA and the PBT terminal groups (? OH and ? COOH) simultaneously, leading to the formation of ASMA–EP–PBT graft copolymers. Because of the effective compatibilization of these copolymers at the interface, finer dispersed phase morphologies were obtained. Compared with PBT/ABS/ASMA blends, the addition of EP induced a more stable molten phase structure, with increases of storage moduli, loss moduli, and dynamic viscosities. Results indicated that 1.5 wt% of the EP in the blends was most suited for the compatibilization. Impact properties of these blends were also investigated. POLYM. ENG. SCI., 47:1943–1950, 2007. © 2007 Society of Plastics Engineers     

一次低烧SrTiO3基晶界层电容器的研究

研究了以Ｌｉ２ＣＯ３为助烧结剂、Ｓｒ（Ｌｉ１／４Ｎｂ３／４）Ｏ３为施主掺杂剂、Ｂｉ２Ｏ３和ＳｉＯ２为晶界绝缘剂的ＳｒＴｉＯ３基晶界层电容器的一次低温烧成技术。初步探索了Ｔｉ／Ｓｒ比值、施主掺杂剂、绝缘剂对显微结构及介电性能的影响。在１１５０℃烧成温度下，获得了εａｐｐ〉３．５×１０＾４；ｐ〉１．０×１０＾１１Ω·ｃｍ；ｔｇδ〈１．０％；ΔＣ／Ｃ〈±５．０％（－２５￣＋８５℃）的ＳｒＴｉＯ３基晶界层     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

Target detection based on a dynamic subspace

For hyperspectral target detection, it is usually the case that only part of the targets pixels can be used as target signatures, so can we use them to construct the most proper background subspace for detecting all the probable targets? In this paper, a dynamic subspace detection (DSD) method which establishes a multiple detection framework is proposed. In each detection procedure, blocks of pixels are calculated by the random selection and the succeeding detection performance distribution analysis. Manifold analysis is further used to eliminate the probable anomalous pixels and purify the subspace datasets, and the remaining pixels construct the subspace for each detection procedure. The final detection results are then enhanced by the fusion of target occurrence frequencies in all the detection procedures. Experiments with both synthetic and real hyperspectral images (HSI) evaluate the validation of our proposed DSD method by using several different state-of-the-art methods as the basic detectors. With several other single detectors and multiple detection methods as comparable methods, improved receiver operating characteristic curves and better separability between targets and backgrounds by the DSD methods are illustrated. The DSD methods also perform well with the covariance-based detectors, showing their efficiency in selecting covariance information for detection.     

A schema aware ETL workflow generator

Extract, Transform and Load (ETL) processes organized as workflows play an important role in data warehousing. As ETL workflows are usually complex, various ETL facilities have been developed to address their control-flow process modeling and execution control. To evaluate the quality of ETL facilities, Synthetic ETL workflow test cases, consisting of control-flow and data-flow aspects are needed to check ETL facility functionalities at construction time and to validate the correctness and performance of ETL facilities at run time. Although there are some synthetic workflow and data set test case generation approaches existed in literatures, little work is done to consider both aspects at the same time specifically for ETL workflow generators. To address this issue, this paper proposes a schema aware ETL workflow generator with which users can characterize their ETL workflows by various parameters and get ETL workflow test cases with control-flow of ETL activities, complied schemas and associated recordsets. Our generator consists of three steps. First, with type and ratio of individual activities and their connection characteristic parameter specification, the generator will produce ETL activities and form ETL skeleton which determine how generated activities are cooperated with each other. Second, with schema transformation characteristic parameter specification, e.g. ranges of numbers of attributes, the generator will resolve attribute dependencies and refine input/output schemas with complied attributes and their data types. In the last step, recordsets are generated following cardinality specifications. ETL workflows in specific patterns are produced in the experiment in order to show the ability of our generator. Also experiments to generate thousands of ETL workflow test cases in seconds have been done to verify the usability of the generator.     

A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions

This paper seeks to enhance network survivability under a disaster and reduce the expected post-disaster response time for transportation networks through pre-disaster investment decisions. The planning focuses on determining the links of the network to strengthen through investment under two types of uncertainties: the disaster characteristics, and the surviving network under each disaster. A bi-level stochastic optimization model is proposed for this problem, in which link investment decisions are made at the upper level to enhance the network survivability subject to a budget constraint such that the expected post-disaster response time is minimized at the lower level. A two-stage heuristic algorithm is proposed to obtain effective solutions efficiently. The numerical experiments indicate that the proposed heuristic algorithm converges to a fixed point representing a feasible solution, within an acceptable tolerance level, of the bi-level stochastic optimization model which is an effective solution under disasters of moderate severity. Parametric and sensitivity analyses reinforce the need for a holistic approach that integrates multiple relevant considerations to determine the link investment decisions.