Framework to manage multiple goals in community-based energy sharing network in smart grid

Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

Adaptive solutions to the mutual exclusion problem

Summary Algorithms for mutual exclusion that adapt to the current degree of contention are developed. Afilter and a leader election algorithm form the basic building blocks. The algorithms achieve system response times that are independent of the total number of processes and governed instead by the current degree of contention. The final algorithm achieves a constant amortized system response time. Manhoi Choy was born in 1967 in Hong Kong. He received his B.Sc. in Electrical and Electronic Engineerings from the University of Hong Kong in 1989, and his M.Sc. in Computer Science from the University of California at Santa Barbara in 1991. Currently, he is working on his Ph.D. in Computer Science at the University of California at Santa Barbara. His research interests are in the areas of parallel and distributed systems, and distributed algorithms. Ambuj K. Singh is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara. He received a Ph.D. in Computer Science from the University of Texas at Austin in 1989, an M.S. in Computer Science from Iowa State University in 1984, and a B.Tech. from the Indian Institute of Technology at Kharagpur in 1982. His research interests are in the areas of adaptive resource allocation, concurrent program development, and distributed shared memory.A preliminary version of the paper appeared in the 12th Annual ACM Symposium on Principles of Distributed ComputingWork supported in part by NSF grants CCR-9008628 and CCR-9223094     

A space- and time-efficient local-spin spin lock

A simple code transformation is presented that reduces the space complexity of Yang and Anderson's local-spin mutual exclusion algorithm. In both the original and the transformed algorithm, only atomic read and write instructions are used; each process generates Θ(logN) remote memory references per lock request, where N is the number of processes. The transformed algorithm uses Θ(N) distinct variables, which is clearly optimal.     

N个振荡器相互注入锁定同步振荡系统

本文对Ｎ个振荡器相互注入锁定同步振荡系统提出了一种通用的分析方法。建立了该系统的完整非线性等效模型，导出了系统的状态方程。对于各种不同电路形式的振荡系统，只要将具体的电路参数代入，就可计算其输出功率，功率合成效率及工作频率等参数，从而使这类系统的计算机辅助分析和设计成为可能。     

大型数据集的多维变量关联性挖掘

为了探索多维数据集中各变量之间的关系,特别是非函数关系,对数据集所在的n维立方体的各个维度进行划分,在得到的n维网格中定义自然概率密度函数,以此得到数据集在特定划分下的互信息值。对所有的划分取互信息最大值,正态化后即为所定义的特征张量的一项,取特征张量在给定最大网格数下的最大项的值定义为MIC,它度量了多维变量间的关联程度。     

Distributed match-making

In many distributed computing environments, processes are concurrently executed by nodes in a store- and-forward communication network. Distributed control issues as diverse as name server, mutual exclusion, and replicated data management involve making matches between such processes. We propose a formal problem called distributed match-making as the generic paradigm. Algorithms for distributed match-making are developed and the complexity is investigated in terms of messages and in terms of storage needed. Lower bounds on the complexity of distributed match-making are established. Optimal algorithms, or nearly optimal algorithms, are given for particular network topologies.The work of the second author was supported in part by the Office of Naval Research under Contract N00014-85-K-0168, by the Office of Army Research under Contract DAAG29-84-K-0058, by the National Science Foundation under Grant DCR-83-02391, and by the Defence Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125. Current address of both authors: CWI, Kruislaan 413, 1098 SJ Amsterdam, The Netherlands.     

Mutual Prodrugs of 5-Fluorouracil: From a Classic Chemotherapeutic Agent to Novel Potential Anticancer Drugs

The development of potent antitumor agents with a low toxicological profile against healthy cells is still one of the greatest challenges facing medicinal chemistry. In this context, the “mutual prodrug” approach has emerged as a potential tool to overcome undesirable physicochemical features and mitigate the side effects of approved drugs. Among broad-spectrum chemotherapeutics available for clinical use today, 5-fluorouracil (5-FU) is one of the most representative, also included in the World Health Organization model list of essential medicines. Unfortunately, severe side effects and drug resistance phenomena are still the primary limits and drawbacks in its clinical use. This review describes the progress made over the last ten years in developing 5-FU-based mutual prodrugs to improve the therapeutic profile and achieve targeted delivery to cancer tissues.     

疲劳与蠕变复合作用下PS的应变与寿命

对PS在疲劳/蠕变复合作用下应变与寿命进行了研究。结果表明：其疲劳/蠕变曲线与纯蠕变曲线十分相似。加载时间周期越短和疲劳载荷变化越频繁。结束普弹应变阶段应变越小，进入延迟弹性变形的平台应变阶段越早。在疲劳/蠕变复合作用下聚苯乙烯存在疲劳和蠕变的交互损伤，其断裂寿命比纯疲劳或纯蠕变的断裂寿命低。断裂寿命减小，疲劳/蠕变的交互损伤程度与温度密切相关，PS在较低温度的疲劳/蠕变交互损伤作用大于较高温度的交互损伤作用。随温度升高，疲劳/蠕变断裂寿命下降是疲劳和蠕变各自的单独损伤增加所致。