Digital Imaging Reconstruction from Multiple Angle Diversity Using Digital Filtering Technique

Microwave diffraction tomography is a process to infer the internal structure of an objectfrom multiple angle views of microwave diffraction shadow. Being sensitive to variations in refractive index of the object, the procedure can be used to measure permittivity distributions within dielectric objects and to image soft tissues for biomedical applications. The optimal resolution distance obtainable is half a wavelength, but this can rarely be achieved because of practical limitations. Some procedures, however, are available to improve the practical resolution. One, which is suitable for microwave tomography, is to use multiple angle views data and to combine the resulting images. The other, which is suitable for improving the image reconstruction resolution, is to use the digital filtering technique and the filtered backpropagation algorithm. A system operating over the X-band microwave frequency is described and some experimental results for objects in air are given.     

A Measure of Learning Model Complexity by VC Dimension

1　IntroductionMeasure of model complexity is important for understanding how difficult a modelingproblem is and for optimizing model performance.Modeling,in all its varied forms,is theprocess of logical induction. A key question regarding induction can be stated as:whatmust one know a priori about an unknown functional dependency in order to estimate itonthe basis of observations?[1 ] . In the fields of engineering and computer science,thisquestion is known as the learning problem. Recently,…     

Fuzzy preferences in conflicts

A systematic fuzzy approach is developed to model fuzziness and uncertainties in the preferences of decision makers involved in a conflict. This unique fuzzy preference formulation is used within the paradigm of the Graph Model for Conflict Resolution in which a given dispute is modeled in terms of decision makers, each decision maker＇s courses of actions or options, and each decision maker＇s preferences concerning the states or outcomes which could take place. In order to be able to determine the stability of each state for each decision maker and the possible equilibria or resolutions, a range of solution concepts describing potential human behavior under conflict are defined for use with fuzzy preferences. More specifically, strong and weak definitions of stability are provided for the solution concepts called Nash, general metarational, symmetric metarational, and sequential stability. To illustrate how these solution concepts can be conveniently used in practice, they are applied to a dispute over the contamination of an aquifer by a chemical company located in Elmira, Ontario, Canada.     

JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING

The English edition of Journal of Systems Science and Systems Engneering is distributedinternationally.It seeks to publish theoretical and applied papers pertaining to systems scienceand systems engineering.It is for researchers,engineers and teaching people engaged in theseareas. Contributions from all over the world are welcome.The authors should note that onlypapers with originality in theory and methodology and technical reports with innovativeness     

Improved Algorithm for Minimum Data Aggregation Time Problem in Wireless Sensor Networks

Wireless sensor networks promise a new paradigm for gathering data via collaboration among sensors spreading over a large geometrical region. Many applications impose delay requirements for data gathering and ask for time-efficient schedules for aggregating sensed data and sending to the data sink. In this paper, the authors study the minimum data aggregation time problem under collision-free transmission model. In each time round, data sent by a sensor reaches all sensors within its transmission range, but a sensor can receive data only when it is the only data that reaches the sensor. The goal is to find the method that schedules data transmission and aggregation at sensors so that the time for all requested data to be sent to the data sink is minimal. The authors propose a 7△/log2｜s｜＋c, new approximation algorithm for this NP-hard problem with guaranteed performance ratio which significantly reduces the current best ratio of △- 1, where S is the set of sensors containing source data, A is the maximal number of sensors within the transmission range of any sensor, and e is a constant. The authors also conduct extensive simulation, the obtained results justify the improvement of proposed algorithm over the existing one.     

Journal of Systems Science and Complexity Information for Authors

Journal of Systems Science and Complexity (JSSC) is a quarterly journal distributed internationally, seeking to publish high-quality papers on theories, methodologies and applications of systems science and complexity science. It focuses on systems theory, systems engineering, systems control, systems modeling and statistics, systems management, intelligent systems, complex systems, and complexity science for the best benefit of the scientific community in systems science, and for a promotion of developments in the emerging complexity science.Contributions from all over the world are welcome. The journal publishies papers of orginal-     

Optimal dividend strategies in the diffusion model with stochastic return on investments

This paper studies the optimal dividend problem in the diffusion model with stochastic return on investments. The insurance company invests its surplus in a financial market. More specially, the authors consider the case of investment in a Black-Scholes market with risky asset such as stock. The classical problem is to find the optimal dividend payment strategy that maximizes the expectation of discounted dividend payment until ruin. Motivated by the idea of Thonhauser and Albrecher (2007), we take the lifetime of the controlled risk process into account, that is, the value function considers both the expectation of discounted dividend payment and the time value of ruin. The authors conclude that the optimal dividend strategy is a barrier strategy for the unbounded dividend payment case and is of threshold type for the bounded dividend payment case.     

消费者异质性影响下的网络信息商品销售策略

针对网络销售模式下的信息商品的特性,文章研究消费者异质性(最大价值差异和强度差异之和)及商品关系对普通销售、纯捆绑销售和混合捆绑销售策略的影响.研究结果表明当强度差异较小,商品间互补或替代时,纯捆绑销售和普通销售分别占优势地位;当商品间无关时,纯捆绑销售与普通销售占优概率基本相等.当强度差异等于最大价值差异时,随异质性增加,普通销售明显优于纯捆绑销售.对混合捆绑的研究给出其转为普通销售和纯捆绑销售的条件,并发现在商品间互补的情况下,当强度差异较小且两种商品最大价值差异相差不大时,纯捆绑策略占优;最大价值差异相差较大且消费者对其中一种商品偏好基本一致时,混合销售策略占优.     

不完全信息下交通网络的关键路径问题

在交通运输中．车辆总是选择最短路径行驶。然而因各种突发事件（交通事故、自然灾害等）造成道路中断的现象普遍存在．车辆在行驶的过程中并不具有道路中断的完全信息．只有行进到中断处时才获得道路中断的信息．此时原来的最短路径就很可能失去其最优性．从而增加交通运输的成本。为了解决这一问题．本文提出了不完全信息下交通网络的关键路径问题．给出了相应的求解算法．并分析了其时间复杂性。然后结合实际交通网络给出算例．最后指出这对提高交通运输的效率更具有实际意义。     

离散粒子群社区检测算法

针对复杂网络中的社区检测问题,提出了一种基于节点影响力的离散粒子群社区检测方法。该方法以模块度密度作为目标函数,利用离散粒子群算法对其进行优化,在优化过程中提出了节点影响力的概念,其充分利用了网络中节点的相互关系检测网络中的社区结构。同时,在此基础上提出了基于节点影响力的粒子群初始化方法和粒子状态更新方法。利用人工网络数据集和真实网络数据集对所提算法进行测试,实验结果表明,所提算法具有较好的检测结果,能更好地对网络中社区进行划分。     

1:1的二级非一体化供应链库存运输联合优化模型

研究了非一体化供应链下单供应商-单零售商的库存运输联合优化问题,考虑了一体化的理想情况以及运输成本分别由供应商、零售商承担3种情况,并建立了数学模型.随机数据实验验证了零售商承担运输成本情形可获得较优的供应链整体利润,其值接近于理想情况下供应链的总体利润,进而采用利润分配策略,以确保供应商和零售商双方均能获得更大利润,从而促进供应链协调.数值算例和参数灵敏度分析验证了运输成本由零售商承担策略的优越性和稳定性.     

D运输问题

提出一类要求货物尽量在某一给定时间以前如数运抵目的地的运输问题。这是一类含离散目标约束的目标规划问题，我们把它称为D运输问题。建立D运输问题的数学模型，引入可实施解、最优解、解对预警时间的偏差等概念，给出D运输问题的求解方法和一个计算例子。     

高科技人才创造能力的人格特征

本文在研究高科技发展中人才的重要性时, 着重对高科技人才的创造能力进行研究, 并首次系统地采用心理测试方法对我国航空、航天、国防及国家有关高科技部门近1000名高科技人才的个体进行集体测试, 通过系统的心理测试, 每位高科技人才得到7O多个测试评价结果。为了简化这些结果, 本文采用主因素分析进行阵维处理后, 将70多个维度降为8个维度, 高科技人才创造能力为其中之一。本文最后根据降维结果对高科技人才创造能力的人格特征进行了系统分析。     

基于预知信息的占线Nomadic TSP问题

自然灾害的频繁发生使得应急减灾倍受关注, 尤其有效的应急救援车辆调度对应急减灾非常重要. 针对受灾点被提前获知但是不能立即接受救援服务的情形, 通过将受灾点(需求)的揭露时间和释放时间引入Nomadic TSP模型中构建了预知信息的占线Nomadic TSP问题, 并分别给出了问题的下界, 直线网络结构下的ENO-dd算法, 和一般网络结构下的GTR-dd算法, 并对算法进行了竞争性能分析. 结果表明两个算法随着预知信息的增多会有明显改进. 更为一般的预知信息结构以及最优的算法设计是下一步研究的方向.     

模糊定性建模与仿真集成实现

定性推理是使用定性模型 ,推理演绎物理系统以获取有用信息的技术 ,在系统诊断、功能行为仿真、产品设计与分析等领域得以广泛应用 .其面对的主要挑战是定性模型构造比较困难 ,仿真效率不高 ,得到有效解的仿真过程代价较大 .本文就此进行了研究 :利用模型片断库和面向对象的方法实现图形化建模环境 ,使得建模过程直观且易操作 ;采用模型定性仿真技术 ,拓展了传统定性仿真算法 ,提高了仿真效率 .文章最后给出软件实现和实例验证 .     

评价决策单元相对效率的修正DEA方法

在原有理论[1] 的基础上提出了一个新的DEA模型———CCRH ,给出了强有效的概念 ,论证了相关理论。CCRH模型与CCR模型相比有以下几个优点 :①描述决策单元的相对效率更确切 ;②利用参考决策单元的生产前沿面来描述评价决策单元“生产”情况得到的结果更加符合实际 ;③可以考查评价决策单元输入、输出变化时对其效率的影响。