A transaction-based method for allocation of transmission grid cost and losses

The problem of grid cost and losses allocation may be divided into independent subproblems: allocation of branch flow and losses to transactions, definition of these transactions and cost allocation to transactions. From this final allocation, the charges to participants in transactions may be made straightforwardly. A differential, slack-invariant method for the allocation of flow and losses to transactions that makes use of the AC load flow equation is presented here. The definition of transactions must be addressed using a non-discriminatory rule in pool systems. There are many possible options for this definition, and the choice made has great influence on the results. Cost allocation, on the other hand, may be made in different ways, as well. The paper presents an allocation process that addresses all these issues. Results for the IEEE-RTS96 test system are obtained and discussed.     

An efficient face segmentation algorithm based on binary partition tree

This paper presents an efficient face segmentation algorithm based on binary partition tree. Skin-like regions are first obtained by integrating the results of pixel classification and watershed segmentation. Facial features are extracted by the techniques of valley detection and entropic thresholding, and are used to refine the skin-like regions. In order to segment the facial regions from the skin-like regions, a novel region merging algorithm is proposed by considering the impact of the common border ratio between adjacent regions, and the binary partition tree is used to represent the whole region merging process. Then the facial likeness of each node in the binary partition tree is evaluated using a set of fuzzy membership functions devised for a number of facial primitives of geometrical, elliptical and facial features. Finally, an efficient algorithm of node selecting in the binary partition tree is proposed for the final face segmentation, which can exactly segment the faces without any underlying assumption. The performance of the proposed face segmentation algorithm is demonstrated by experimental results carried out on a variety of images in different scenarios.     

Optimum thermoeconomic and thermodynamic performance characteristics of an irreversible three-heat-source heat pump

The coefficient of performance and specific heating load of an irreversible three-heat-source heat pump are given by using a general cycle model affected by the finite-rate heat transfer, heat leak and internal irreversibility of the cyclic working fluid. The heat pumping load divided by the total cost per unit time is taken as a new objective function and used to investigate the performance of the heat pump. The thermoeconomic and thermodynamic performance characteristics of the heat pump are discussed in detail. Some important performance parameters such as the thermoeconomic objective function and coefficient of performance are optimized. The optimally operating regions of the heat pump and the bounds of several performance parameters are determined. Finally, it is pointed out that the Carnot heat pump may be taken as a special case of a three-heat-source heat pump and consequently its optimal performance can be directly derived from the results obtained here.     

Lactic acid production from dining‐hall food waste by Lactobacillus plantarum using response surface methodology

BACKGROUND: Food waste generally has a high starch content and is rich in nutritional compounds, including lipids and proteins. It therefore represents a potential renewable resource. In this study, dining‐hall food waste was used as a substrate for lactic acid production, and response surface methodology was employed to optimise the fermentation conditions. RESULTS: Lactic acid biosynthesis was significantly affected by the interaction of protease and temperature. Protease, temperature and CaCO₃ had significant linear effects on lactic acid production, while α‐amylase and yeast extract had insignificant effects. The optimal conditions were found to be an α‐amylase activity of 13.86 U g^?1 dried food waste, a protease activity of 2.12 U g^?1 dried food waste, a temperature of 29.31 °C and a CaCO₃ concentration of 62.67 g L^?1, which resulted in a maximum lactic acid concentration of 98.51 g L^?1 (88.75% yield). An increase in inoculum size would be appropriate for accelerating the depletion of initial soluble carbohydrate to enhance the efficiency of α‐amylase in dining‐hall food waste fermentation. CONCLUSION: A suitable regression model for lactic acid production was developed based on the experimental results. Dining‐hall food waste was found to be a good substrate for lactic acid fermentation with high product yield and without nutrient supplementation. Copyright © 2008 Society of Chemical Industry     

A unified formulation of Kautz network and generalized hypercube

Hypercube and Kautz network each possess certain desirable properties. However, some of the attractive features of one network are not found in the other. A novel class of network topologies proposed in this paper has the generalized hypercube and the Kautz network as its two extremes. The proposed network inherits the topological properties of both the Kautz network and the generalized hypercube to a varying degree. This allows us to trade-off cost and performance effectively and construct networks which are most suitable for a particular purpose. In the present paper, we investigate the connectivity, wide-diameter, fault-tolerance, Hamiltonicity.     

Minimum weight design of inhomogeneous rotating discs

There are numerous applications for gas turbine discs in the aerospace industry such as in turbojet engines. These discs normally work under high temperatures while subjected to high angular velocities. Minimizing the weight of such items in aerospace applications results in benefits such as low dead weights and lower costs. High speed of rotation causes large centrifugal forces in a disc and simultaneous application of high temperatures reduces disc material strength. Thus, the latter effects tend to increase deformations of the disc under the applied loads. In order to obtain a reliable disc analysis and arrive at the corresponding correct stress distribution, solutions should consider changes in material properties due to the temperature field throughout the disc. To achieve this goal, an inhomogeneous disc model with variable thickness is considered. Using the variable material properties method, stresses are obtained for the disc under rotation and a steady temperature field. In this paper this is done by modelling the rotating disc as a series of rings of different but constant properties. The optimum disc profile is arrived at by sequentially proportioning the thicknesses of each ring to satisfy the stress requirements. This method vis-à-vis a mathematical programming procedure for optimization shows several advantages. Firstly, it is simple iterative proportioning in each design cycle not requiring involved mathematical operations. Secondly, due to its simplicity it alleviates the necessity of certain simplifications that are common in so-called rigorous mathematical procedures. The results obtained, compared to those published in the literature show agreement and superiority. A further advantage of the proposed method is the independence of the end results from the initially assumed point in the iterative design routine, unlike most methods published so far.     

热光双稳态的临界入射功率与临界温升

本文考虑到F—P腔夹层介质和后反射镜均具有一定的吸收时,推导出产生热致色散光学双稳态的临界入射光功率P_c和临界温升△T_c的数学解析表达式。理论计算的 △T_c值与实验值非常符合。为了得到最佳光学双稳态回线和避免腔内的纵向温度梯度,夹层介质和后反射镜应具有一定的匹配吸收。     

植物抗性基因识别中的随机森林分类方法

为了解决传统基于同源序列比对的抗性基因识别方法中假阳性高、无法发现新的抗性基因的问题,提出了一种利用随机森林分类器和K-Means聚类降采样方法的抗性基因识别算法。针对目前研究工作中挖掘盲目性大的问题,进行两点改进:引入了随机森林分类器和188维组合特征来进行抗性基因识别,这种基于样本统计学习的方法能够有效地捕捉抗性基因内在特性;对于训练过程中存在的严重类别不平衡现象,使用基于聚类的降采样方法得到了更具代表性的训练集,进一步降低了识别误差。实验结果表明,该算法可以有效地进行抗性基因的识别工作,能够对现有实验验证数据进行准确的分类,并在反例集上也获得了较高的精度。     

恶意软件鉴别技术及其应用

随着互联网技术的发展和安全形势的变化,恶意软件的数量呈指数级增长,恶意软件的变种更是层出不穷,传统的鉴别方法已经不能及时有效的处理这种海量数据,这使得以客户端为战场的传统查杀与防御模式不能适应新的安全需求,各大安全厂商开始构建各自的"云安全"计划。在这种大背景下,研究恶意软件检测关键技术是非常必要的。针对恶意软件数量大、变化快、维度高与干扰多的问题,我们研究云计算环境下的软件行为鉴别技术,探讨海量软件样本数据挖掘新方法、事件序列簇类模式挖掘新模型和算法及在恶意软件鉴别中的应用,并构建面向云安全的恶意软件智能鉴别系统原型以及中文钓鱼网站检测系统架构。