Random Forests with ensemble of feature spaces

Random Forests receive much attention from researchers because of their excellent performance. As Breiman suggested, the performance of Random Forests depends on the strength of the weak learners in the forests and the diversity among them. However, in the literature, many researchers only considered pre-processing of the data or post-processing of the Random Forests models. In this paper, we propose a new method to increase the diversity of each tree in the forests and thereby improve the overall accuracy. During the training process of each individual tree in the forest, different rotation spaces are concatenated into a higher space at the root node. Then the best split is exhaustively searched within this higher space. The location where the best split lies decides which rotation method to be used for all subsequent nodes. The performance of the proposed method here is evaluated on 42 benchmark data sets from various research fields and compared with the standard Random Forests. The results show that the proposed method improves the performance of the Random Forests in most cases.     

Hybrid clustering solution selection strategy

Cluster ensemble approaches make use of a set of clustering solutions which are derived from different data sources to gain a more comprehensive and significant clustering result over conventional single clustering approaches. Unfortunately, not all the clustering solutions in the ensemble contribute to the final result. In this paper, we focus on the clustering solution selection strategy in the cluster ensemble, and propose to view clustering solutions as features such that suitable feature selection techniques can be used to perform clustering solution selection. Furthermore, a hybrid clustering solution selection strategy (HCSS) is designed based on a proposed weighting function, which combines several feature selection techniques for the refinement of clustering solutions in the ensemble. Finally, a new measure is designed to evaluate the effectiveness of clustering solution selection strategies. The experimental results on both UCI machine learning datasets and cancer gene expression profiles demonstrate that HCSS works well on most of the datasets, obtains more desirable final results, and outperforms most of the state-of-the-art clustering solution selection strategies.     

Large-scale SRAM-based IP lookup architectures using compact trie search structures

SRAM-based pipelined architectures for high-speed IP lookup using Field Programmable Gate Arrays (FPGAs) has recently attracted a great deal of attention from researchers. Due to the limited amount of on-chip memory and the number of I/O pins of FPGAs, compact data structures providing high memory efficiency are in great demand.     

润滑油调和数学模型的建立与应用

分析了南阳石蜡精细化工厂的基础油用阿伦尼乌斯公式计算的粘度数值与实测粘度数值的关系,对其系数进行校正,成功得出了精确度较高的润滑油调和数学模型,并经现场应用,证明可用于生产中.     

Silica Nanoboxes as New Nano-structured Materials: Their Secondary Synthesis from Alumina-Rich Zeolites

Novel silica nanoboxes were prepared by controlled dealumination of Na-X and Ca-A type zeolites using ammonium hexafluorosilicate (AHFS). The silica-richer the parent zeolite, the smaller the average pore size produced and the narrower the pore size distribution obtained. This was due to the specific reactivity of the extracting agent with the zeolite framework aluminum atoms. High temperature calcination of the dealuminated X-zeolite (ammonium form) resulted in mesoporous materials exhibiting an ink-bottle shape, a quite high surface area (330 m²/g, no micropores), an average pore diameter of 4.5 nm with a quite narrow pore size distribution (± 1.0 nm) and finally, a pore opening diameter of 3.9 nm. The latter was determined by using the nitrogen sorption isotherms (BET technique) and related pore volume data. The sorption behavior also suggested the interconnecting character of the newly created nanoboxes. The periodicity of these nanoboxes throughout the mesoporous material was clearly shown by X-ray powder diffraction at very small angles. These materials, herein called monomodal nanoboxes because of the absence of micropores in the structure, were also thermally stable. Incorporation of orthosilicate into the obtained silica nanoboxes, in accordance with the recently developed technique for pore size engineering in zeolites, led to materials with smaller pore openings but having almost the same textural properties. Solid superacidic materials were prepared by incorporating a liquid superacid (triflic acid or trifluoromethanesulfonic acid) into the silica nanoboxes using the wet impregnation technique. The maximum triflic acid loading which did not significantly affect the mesoporous framework of the materials was 24 wt%. As a reference, the maximum loading of less acidic sulfuric acid was slightly lower. All this showed the high chemical stability of the silica nanoboxes for supporting very acidic species. Temperature-programmed desorption using a combined DTA/TGA system allowed the identification of the bound phases and some liquid phase of the loaded triflic acid.     

Development of high-performance liquid chromatography criteria for determination of grades of commercial olive oils. Part I. The normal ranges for the triacylglycerols

Criteria for authentic olive oils were developed from isocratic high-performance liquid chromatography analyses of 99 olive oils from the major Mediterranean producers in the 1983–1986 crop years. Authentic olive oils include extra virgin, virgin and pure or refined oils, but exclude all reesterified and adulterated oils. The extra virgin through pure grades will have a combined area for the LOO (C_18:2C_18:1C_18:1), LOP (C_18:2C_18:1C_16:0), OOO (C_18:1C_18:1C_18:1), POO (C_16:0C_18:1C_18:1), POP (C_16:0C_18:1C_18:1), and SOO (C_18:0C_18:1C_18:1) peaks between 82.0 and 92.6% of the total area (L, linoleic; O, oleic; P, palmitic; S, stearic). Authentic oils will have ratios of LOO/LOP and OOO/POO that coincide with a line defined by OOO/POO=0.7844(LOO/LOP)+0.0968; correlation coefficient is 0.885. Authentic oils will not have a trilinolein (LLL) peak over 0.5% in area. Neither triolein (OOO) nor any other single peak suffices to characterize an olive oil sample as one of the authentic grades.     

基于计算智能的电站锅炉燃烧优化控制

燃烧优化是提升电站锅炉效率降低污染物排放的有效途径;计算智能是目前实现燃烧过程建模及优化的重要手段.本文综述了各种计算智能算法在电站锅炉燃烧优化控制中研究成果,分别对其技术特点和不足进行了分析,并提出了燃烧优化技术的发展方向和前景,对从事该方面的研究人员有一定参考价值.     

Catalytic wall reactor: Catalytic coatings of stainless steel by VOx/TiO2 and Co/SiO2 catalysts

Catalytic wall (structured) reactors and structured supports are suitable to study the catalytic properties of nanosized materials. The coating of metallic (aluminum and stainless steel) plates by thin layers of active phase is presented in two cases, VO_x/TiO₂ and Co/SiO₂, catalysts used in the oxidative dehydrogenation (ODH) of propane and in Fischer–Tropsch synthesis (FTS) of clean fuels, respectively. The preparation of coated plates and their characterisation by various methods of physicochemical analysis are described. Both chemical and physical methods were used for coating. VO_x/TiO₂ layers were obtained by grafting of Ti (on Al or stainless-steel plates) and V (on TiO₂) alkoxides and use of sol–gel media or suspension. A silica primer was deposited (on stainless-steel plate) by plasma-assisted chemical vapour deposition (PACVD) onto which Co oxide and silica were coprecipitated from sol–gel. The catalytic experiments in the respective reactions were carried out in special plate reactors and compared with those of catalytic powders. The study shows that the coating of a metallic substrate by a catalyst is not straightforward and requires specific studies dealing with both chemistry (chemical affinity between substrate and catalytic layers) and catalytic engineering (catalytic performance in taylor-made reactors).     

丙碳脱碳溶剂的改进研究

介绍一种由丙碳、叔胺和少量活化剂构成的复合溶剂的开发，并详细地测定了不同压力和操作工况下，这种复合溶剂对ＣＯ２的吸收和解吸性能，以及溶剂的缓蚀性能和抗氧化性能．实验证明这种复合溶剂与纯丙碳相比，具有吸收容量大、速率快、脱碳净化度高、对设备无腐蚀等特点，对改进现行的丙碳脱碳工艺具有应用价值．     

Aromatization of n-butane over new LD-HBS catalysts. Effect of the gallium oxide support

It is shown that even pure quartz, other silicas or aluminas can enhance the aromatization activity of a ZSM-5 zeolite. Incorporation of gallium oxide onto these supports increases further the production of aromatics. The use of supported gallium oxide co-catalyst obtained by co-evaporation of a colloidal silica and a Ga salt has led to extremely high aromatization performance for the hybrid catalyst.