有交易费的折算资产优化性质和可达性

针对有交易费的多股票资产模型 ,引入了资产折算函数 ,并利用辅助鞅和凸分析方法 。

常系数投资消费模型的一些优化性质

本文在有交易费的常系数投资消费模型下,讨论了折算函数和价值函数的一些基本性质,即给出了价值函数的凹性、连续性、正则性和变分不等式的粘性上解以及粘性解存在性等结果.

基于改进CAPSO的原油管道调合多性质优化方法

在仔细研究原油管道调合工艺基础上,提出一种基于改进有约束自适应粒子群优化(CAPSO)算法的原油管道调合多性质优化方法;首先,基于原油调合规则库、优化预处理及设备实际工作能力约束,建立了多原油多性质优化模型;然后,根据原油调合目标,通过CAPSO算法对优化模型进行快速、准确的优化计算,获得多种组分原油的最优配比;投运效果表明,系统能够自动、高效计算出原油调合的最优配比,避免人工计算所造成的一致性差,计算效率低并且不易获得最佳配比的问题,有效提高了加工设备的生产效率。

相变物质储能建筑材料性质研究的进展

本文概括了作者对相变物质储能建筑材料性质方面的研究，其中包含了应用相变物质二元混合物的近期结果，提供了储能建材热物性测量数据和模拟计算用的经验模型，讨论了把研究工作转向相变物质混合物的重要性。在测试与数值模拟计算基础上，确认了优化储能建材相变温度对节能的有效性，提出了进一步研究的建议。

芽胞杆菌苎麻脱胶酶—甘露聚糖酶的纯化及酶学性质

研究了苎麻高效脱胶菌株Bacillus subtilisNo.16A甘露聚糖酶的产生条件,纯化过程以及酶学性质。其优化的培养基为魔芋胶30 g/L,蛋白胨9 g/L,酵母膏2 g/L,KH2PO45 g/L,MgSO4.7H2O 0.25 g/L。优化的培养条件为起始pH 8.0,装样量50 mL,接种量10 mL,发酵72 h。进一步通过硫酸铵沉淀、阴离子交换层析、凝胶过滤3步从Bacillus subtilisNo.16A发酵液中纯化了甘露聚糖酶。结果表明,该酶分子量约为38.5ku,最适作用pH为7.0,最适作用温度为60℃,在55℃以下、中性pH（6.0～8.0）范围内稳定,Ca^2＋、Mn^2＋和Al^3＋、Mg^2＋对该酶有激活作用,Cu^2＋、Zn^2＋有抑制作用。

酶分子设计常用策略和进展

酶分子的生物学功能很大程度上是由其三维空间结构和所处溶剂环境共同决定的。因此,优化酶分子的结构性质以及探索其性质最优的溶剂环境是改善酶分子功能以及进行理性设计的一个可行途径。从实际应用的角度来看,分子设计方法可以为酶工程提供一种有效的解决方案。目前,酶分子设计有两个重要的研究方向,包括提高酶分子的催化活力和优化其稳定性。同时,对酶分子设计方法的研究也有助于对蛋白质生物学机理的探索。在近些年的学术界酶分子设计案例中,生物信息学方法得到广泛的应用。本文系统地总结基于生物信息学的酶分子设计方法的背景、策略和一些经典案例。

A Novel Real-time Optimization Methodology for Chemical Plants

In this paper, a novel approach termed process goose queue (PGQ) is suggested to deal with real-time optimization (RTO) of chemical plants. Taking advantage of the ad-hoc structure of PGQ which imitates biologic nature of flying wild geese, a chemical plant optimization problem can be re-formulated as a combination of a multi-layer PGQ and a PGQ-Objective according to the relationship among process variables involved in the objective and constraints. Subsequently, chemical plant RTO solutions are converted into coordination issues among PGQs which could be dealt with in a novel way. Accordingly, theoretical definitions, adjustment rule and implementing procedures associated with the approach are explicitly introduced together with corresponding enabling algorithms. Finally, an exemplary chemical plant is employed to demonstrate the feasibility and validity of the contribution.

A Novel Vertical Handoff Algorithm with Dynamic Weights in Wireless Heterogeneous Networks

In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS factors. In this paper, we develop a novel vertical handoff algorithm in an integrated 3G cellular and Wireless LAN networks. The proposed algorithm can adjust the weight of each QoS attribute dynamically as the networks change, trace the network condition and choose the optimal access point at transient regions. Simulation results show that this algorithm is able to provide accurate handoff decision, resulting in small unnecessary handoff numbers, good performance of throughput and handoff delay in heterogeneous environments.

Optimization Design of Vibration Characteristics of Ship Composite Brace with Rigid Vibration Isolation Mass

In considering the theory of structural dynamic optimization design, a design method of the structural style of ship composite brace with rigid vibration isolation mass was studied. Two kinds of structural dynamic optimization formulations minimizing the vibration acceleration of the non-pressure hull on the restraining condition of the gross weight of the ship cabin were established: 1) dynamic optimization of the sectional dimensions of the rigid vibration isolation mass in the composite brace; 2) dynamic optimization of the arranging position of the rigid vibration isolation mass. Through the optimization results, sectional dimensions and the arranging position of the rigid vibration isolation mass with better performance in reducing vibration were gained, and some reference was provided for practical engineering designs as well as enrichment of the design method of a novel ship vibration-isolation brace.

Application of grey relational analysis in sheet metal forming for multi-response quality characteristics

The theory of grey systems is a new technique for performing prediction, relational analysis and decision making in many areas. In this paper, the use of grey relational analysis for optimizing the square hole flanging process parameters with considerations of the multiple response (the average flanging height, regular flanging and maximum strain) is introduced. Various flanging parameters, such as the blank inner radius rb, blank inner width B0, are considered. An orthogonal array is used for the experimental design. Multiple response values are obtained using finite element analysis (FEA). Optimal process parameters are determined by the grey relational grade obtained from the grey relational analysis for multi-performance characteristics (flanging height, regular flanging and maximum strain). Analysis of variance (ANOVA) for the grey relational grade is implemented. The results showed good agreement with the experiment result. Grey relational analysis can be applied in multiple response optimi-zation designs.

Optimization of the Purification Methods for Recovery of Recombinant Growth Hormone from Paralichthys olivaceus

This study aimed to optimize the purification of recombinant growth hormone from Paralichthys olivaceus. Recombinant flounder growth hormone （r-fGH） was expressed by Escherichia coli in form of inclusion body or as soluble protein under different inducing conditions. The inclusion body was renatured using two recovery methods, i.e., dilution and dialysis. Thereafter, the refolded protein was purified by Glutathione Sepharase 4B affinity chromatography and r-fGH was obtained by cleavage of thrombin. For soluble products, r-fGH was directly purified from the lysates by Glutathione Sepharase 4B affinity chromatography. ELISA-receptor assay demonstrated that despite its low receptor binding activity, the r-fGH purified from refolded inclusion body had a higher yield （2.605 mg L^-1） than that from soluble protein （1.964 mg L^-l）. Of the tested recovery methods, addition of renaturing buffer （pH 8.5） into denatured inclusion body yielded the best recovery rate （17.9%）. This work provided an optimized purification method for high recovery of r-fGH, thus contributing to the application of r-fGH to aquaculture.

Optimization of Yield and Chemical Properties of Agar Extracted from Melanothamnus Somalensis from Oman Sea

The red seaweed Melanothamnus somalensis was investigated as potential economic source of agar. The effect of different conditions of alkali pre-treatment on chemical properties of agar was evaluated. Agar was extracted by various concentrations of NaOH （4%, 6% and 8%） and heated at different temperatures （70 ℃, 75 ℃ and 80 ℃） for different durations （2 h, 2.75 h and 3.5 h）. The yields-molecular weight （Mw） and sulfate contents of extracted agar were analysed and characterized by FTIR spectroscopy. The yield was significantly increased at these treatments from 23.29% to 30.86%. Mw studied by HPLC ranged from （.12.45 ± 0.21） × 10^5 to （8.60 ± 2.40） × 10^5 Da. FTIR bands show sulfate groups in C4 and C6 ofgalactose and no sulfate group were found on both C2 of galactose and C2 of 3,6-anhydrogalactose. All treatments showed a high sulfate content that ranged from 5.4% to 10.1%. These properties were found to be significantly affected by the alkali pre-treatment concentration （p 〈 0.05）. In conclusion, agar extracted in this study was considered acceptable for industrial application and the optimal conditions for extraction were found to be at 6% NaOH at 70 ℃ for 2 hours.

Hybrid Strategy of Particle Swarm Optimization and Simulated Annealing for Optimizing Orthomorphisms

Orthomorphism on F2^n is a kind of elementary pemmtation with good cryptographic properties. This paper proposes a hybrid strategy of Particle Swarm Optimization （PSO） and Sirrmlated Annealing （SA） for finding orthomorphisrm with good cryptographic properties. By experiment based on this strategy, we get some orthorrorphisrm on F2^n = 5, 6, 7, 9, 10） with good cryptographic properties in the open document for the first time, and the optirml orthorrrphism on F found in this paper also does better than the one proposed by Feng Dengguo et al. in stream cipher Loiss in difference uniformity, algebraic degree, algebraic irrarnity and corresponding pernmtation polynomial degree. The PSOSA hybrid strategy for optimizing orthomerphism in this paper makes design of orthorrorphisrm with good cryptographic properties automated, efficient and convenient, which proposes a new approach to design orthornorphisrm.

矿区地表裂隙土体MICP纤维加筋修复研究

我国西北地区作为煤炭产业富集区域,区域内的煤炭的过量开采导致了大量地表裂缝的产生。因此,地表裂缝的修复对煤炭开采过后的环境修复具有重大的现实意义。采用在紫外分光光度计和多参数分析仪等方法,研究了巨大芽孢杆菌在设定试验温度下其浓度和脲酶活性的生长趋势,选取微生物富集区间进行试样的制备。以无水氯化钙为碳源和无机盐来源,利用研究区黄土、煤矸石和标准砂的不同混合方式以及纯土、纯砂等作为土体裂隙充填物质,利用尿素作为氮源,开展一系列的MICP纤维加筋修复土体裂隙的试验,包括剪切强度对比试验,无侧限抗压强度对比试验,变水头渗透对比实验。研究结果表明:本次试验菌种在多次传代培养后,经过一周的恒温培养在第七天时其浓度和脲酶活性均达到峰值,选取部分菌液用于土体裂隙的修复。采用黄土和标准砂以1:1混合作为充填物质时,裂隙土体的物理力学和水理修复效果最好,且有利于后续植物联合修复。煤矸石和标准砂1:1混合作为充填物对裂隙土体的修复效果稍次之。单种充填物的修复效果最差。

Analysis of color distortion and optimum fusion for remote sensing images using the statistical property of wavelet decomposition

IHS （Intensity, Hue and Saturation） transform is one of the most commonly used tusion algonthm. But the matching error causes spectral distortion and degradation in processing of image fusion with IHS method. A study on IHS fusion indicates that the color distortion can＇t be avoided. Meanwhile, the statistical property of wavelet coefficient with wavelet decomposition reflects those significant features, such as edges, lines and regions. So, a united optimal fusion method, which uses the statistical property and IHS transform on pixel and feature levels, is proposed. That is, the high frequency of intensity component Ⅰ is fused on feature level with multi-resolution wavelet in IHS space. And the low frequency of intensity component Ⅰ is fused on pixel level with optimal weight coefficients. Spectral information and spatial resolution are two performance indexes of optimal weight coefficients. Experiment results with QuickBird data of Shanghai show that it is a practical and effective method.

Development of an Emulator for the Plasma Process Control

This work aims at developing an automatic system for the control of the APS （air plasma spraying） plasma process in which some instability phenomena are present. APS is a versatile technique to produce coatings of powder material at high deposition rates. Using this technique, powder particles are injected into a plasma jet, where they are melted and accelerated towards a substrate. The coating microstructures and properties depend strongly on the characteristics of the plasma jet, which can be controlled by the adjustment of the process parameters. However, the imeractions among the spray variables, render optimization and control of this process are quite complex. Understanding relationships between coating properties and process parameters is mandatory to optimize the process technique and the product quality. We are interested in this work to build an on-line control model for the APS process based on the elements of artificial intelligence and to build an emulator that replicates the dynamic behavior of the process as closely as possible.

Path planning of unmanned aerial vehicle based on improved gravitational search algorithm

Path planning of Uninhabited Aerial Vehicle(UAV) is a complicated global optimum problem.In the paper,an improved Gravitational Search Algorithm(GSA) was proposed to solve the path planning problem.Gravitational Search Algorithm(GSA) is a newly presented under the inspiration of the Newtonian gravity,and it is easy to fall local best.On the basis of introducing the idea of memory and social information of Particle Swarm Optimization(PSO),a novel moving strategy in the searching space was designed,which can improve the quality of the optimal solution.Subsequently,a weighted value was assigned to inertia mass of every agent in each iteration process to accelerate the convergence speed of the search.Particle position was updated according to the selection rules of survival of the fittest.In this way,the population is always moving in the direction of the optimal solution.The feasibility and effectiveness of our improved GSA approach was verified by comparative experimental results with PSO,basic GSA and two other GSA models.

Synergistic fibroblast optimization: a novel nature-inspired computing algorithm

The evolutionary algorithm, a subset of computational intelligence techniques, is a generic population-based stochastic optimization algorithm which uses a mechanism motivated by biological concepts. Bio-inspired computing can implement successful optimization methods and adaptation approaches, which are inspired by the natural evolution and collective behavior observed in species, respectively. Although all the meta-heuristic algorithms have different inspirational sources, their objective is to find the optimum(minimum or maximum), which is problem-specific. We propose and evaluate a novel synergistic fibroblast optimization(SFO) algorithm, which exhibits the behavior of a fibroblast cellular organism in the dermal wound-healing process. Various characteristics of benchmark suites are applied to validate the robustness, reliability, generalization, and comprehensibility of SFO in diverse and complex situations. The encouraging results suggest that the collaborative and self-adaptive behaviors of fibroblasts have intellectually found the optimum solution with several different features that can improve the effectiveness of optimization strategies for solving non-linear complicated problems.

TOPOLOGICAL STRUCTURE OF EFFICIENT SET OF OPTIMIZATION PROBLEM OF SET－VALUED MAPPING

This paper is concerned with the topological structure of efficient sets for optimizationproblem of set-valued mapping. It is proved that these sets are closed or. connected under someconditions on cone-continuity, cone-convexity and cone-quasiconvexity.

A COMBINATORIAL PROPERTY OF PALLET-CONSTRAINED TWO MACHINE FLOW SHOP PROBLEM IN MINIMIZING MAKESPAN

We consider the problem of scheduling n jobs in a pallet-constrained flow shop so as to minimize the makespan.In such a flow shop environment,each job needs a pallet the entire time,from the start of its first operation until the completion of the last operation,and the number of pallets in the shop at any given time is limited by a positive integer,K≤n.Generally speaking,the optimal schedules may be passing schedules.In this paper,we present a combinatorial property which shows that for two machines,K(K≥3）pallets,there exists a no-passing schedule which is an optimal schedule for n≤2K-1 and 2K-1 is tight.