A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries

The Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) is an extension to the classical Vehicle Routing Problem (VRP), where customers may both receive and send goods simultaneously. The Vehicle Routing Problem with Mixed Pickup and Delivery (VRPMPD) differs from the VRPSPD in that the customers may have either pickup or delivery demand. However, the solution approaches proposed for the VRPSPD can be directly applied to the VRPMPD. In this study, an adaptive local search solution approach is developed for both the VRPSPD and the VRPMPD, which hybridizes a Simulated Annealing inspired algorithm with Variable Neighborhood Descent. The algorithm uses an adaptive threshold function that makes the algorithm self-tuning. The proposed approach is tested on well-known VRPSPD and VRPMPD benchmark instances derived from the literature. The computational results indicate that the proposed algorithm is effective in solving the problems in reasonable computation time.     

Understanding value creation in closed loop supply chains – Past findings and future directions

The topic of value creation through the recovery of returned products in closed loop supply chains is scattered across various bodies of literature. We undertake a systematic literature review of 144 articles in relevant green, reverse and closed loop supply chain literature to synchronize existing knowledge on value creation. Value manifestations of four types of value, namely economic, environmental, information and customer value, are identified. Value adding concepts from the forward- and reverse supply chain may leverage the process of value creation. They are classified into six subclasses, namely partnerships and collaboration, product design characteristics, service concepts, IT solutions, supply chain processes and organizational characteristics. We present a conceptual framework on a strategic level. In this way companies can create competitive advantages by closing the loop. The results of the literature analysis suggest avenues for future research on the operational and strategic level.     

磺基琥珀酸双2-丁基辛酯钠盐的合成及表面活性测定

以马来酸酐和2-丁基辛醇为原料,经酯化得到相应的双酯,以乙醇作混相促进剂,使双酯与亚硫酸氢钠进行磺化反应,合成了磺基琥珀酸双2-丁基辛酯钠盐。采用正交试验对酯化反应条件进行了优化。合成产物的临界胶束浓度(cmc)值为3.58×10-6mol/L,表面张力(γcmc)为27.568mN/m。     

十二酰胺丙基二甲基羟乙基氯化铵与十二烷基硫酸钠水溶液的表面吸附和胶束形成

利用十二酰胺丙基二甲胺和氯乙醇反应 ,合成了十二酰胺丙基二甲基羟乙基氯化铵 (DDHA)阳离子表面活性剂 ,将其与十二烷基硫酸钠 (SDS)以不同摩尔比进行混合 ,测定了混合系统的表面张力 ,计算了单一系统和混合系统的饱和吸附量、分子最小截面积 ,表面层和胶束中 DDHA的摩尔分率及分子间相互作用参数 ,目视观察了混合系统的浑浊情况。结果表明 :在降低γcmc和 cmc方面 ,DDHA SDS混合系统有协同效应 ,表面层和胶束的组成与二组分配比有关 ,但是非对称的 ,等物质的量混合物中 ,DDHA在胶束和表面层中具有较大的摩尔分数。DDHA与 SDS在实验测定的各混合系统中都不出现混浊     

Slow eroding biodegradable multiblock poloxamer copolymers

Biodegradable multiblock poloxamers (BMPs) with gel duration of 8 h to several weeks were prepared by varying their molecular weights from 4000 to 40 000 g mol^?1. The molecular weight of the BMP was controlled by changing the poloxamer to coupling agent ratio. Assuming a micelle packing model of the BMP gel, as in the case of a poloxamer gel, the micelle properties and critical gel concentration of BMPs were investigated on the basis of the scaling concept. The findings suggest that the control of molecular weight by hydrolyzable groups can be a facile approach to optimize the gel properties for biomedical applications. Copyright © 2005 Society of Chemical Industry     

Influence of Reaction Parameters on the Hydrogenolysis of Hydroxymatairesinol Over Carbon Nanofibre Supported Palladium Catalysts

The density functional theory (DFT/B3LYP) calculations were applied to investigate the interaction of a Pt₆ particle with the ZSM-5 zeolite framework. The electronic structure of the metal particle is strongly affected by the interaction with basic framework oxygens and acid sites of the zeolite support. Adsorption on basic sites (E_ads = 6 kcal/mol) favors the formation of the electron enriched metal cluster. Interaction of the platinum cluster with the acid site characterized by stabilization energy of 47 kcal/mol results in oxidation of the metal particle and suppression of Brønsted acidity of the support. The hypothesis is put forward that the oxidized platinum particle can function as an active site for the alkane isomerisation on platinum supported high silica zeolites.     

Understanding and Modeling the Effect of Surfactants in Enhanced Particle Removal from Surfaces in Aqueous Media

The removal of particulate contamination is a critical issue for many manufacturing processes. It is particularly critical to the electronics industry in which small pieces of microscopic debris remaining after chemical mechanical planarization (cmp) using submicron polishing particles can cause device failure. One way to enhance particle removal following the cmp process is to utilize surfactants. Recent research has shown ways to model the effect of surfactants on enhanced particle removal. However, previous research has not demonstrated the effect of ionic strength on enhanced particle removal associated with surfactant use. Past research has also not shown the combined effects of ionic strength and surfactant concentration on enhanced particle removal using surfactants. This article summarizes the parameters affecting particle removal, and it provides data and analysis on the effect of ionic strength as well as the combined effects of ionic strength and surfactant concentration on particle removal following cmp processing.     

Running programs backwards: The logical inversion of imperative computation

Imperative programs can be inverted directly from their forward-directed program code with the use of logical inference. The relational semantics of imperative computations treats programs as logical relations over the observable state of the environment, which is taken to be the state of the variables in memory. Program relations denote both forward and backward computations, and the direction of the computation depends upon the instantiation pattern of arguments in the relation. This view of inversion has practical applications when the relational semantics is treated as a logic program. Depending on the logic programming inference scheme used, execution of this relational program can compute the inverse of the imperative program. A number of nontrivial imperative computations can be inverted with minimal logic programming tools.