A relativistic extension of the complex scaling method using oscillator basis functions

We develop the complex scaling method within the relativistic framework by expanding the Dirac spinors in the complete set of eigensolutions of a harmonic oscillator potential, and present the theoretical formalism of describing the discrete bound and resonant states on the same footing. Based on a well established and frequently used model, we demonstrate the utility and applicability of the extended method and examine the stability of the results with respect to the variations of the parameters of the model. Satisfactory agreements are found for all the calculated results in comparison with some other calculations in references. Especially, the present calculation in the nonrelativistic limit gives a consistent result with that in the nonrelativistic calculation.     

动态ERP系统中Ajax/SOA系统架构模型的构造

为了指导动态ERP系统的开发,引入Ajax的客户端,与基于SOA的服务器端之间相配合和协调,既继承了轻量级客户端/服务器端的应用优势,又满足企业的需求变化,是一种可伸缩的和易扩展的Web应用程序实现方式。依据Client/Server-Brow-ser/Server-Ajax/SOA的思路,从物理视角和逻辑视角构造一个融合Ajax技术的SOA系统架构模型,并给出模型的实现策略以及Ajax技术在其中的应用,完善了动态ERP系统的设计机制。     

养殖场的Smith圆图数据控制系统研究

分析了现有人工养殖场工作方式及已有自动监控水温和生长控制系统存在的问题,提出了一种成本较低的基于Smith圆图数据的电台式数据远传接收监控系统的设计方案.该系统可以接收幼苗生长的环境参数以及幼苗是否生病等情况的数据.养殖渔场环境以图像方式保存,当出现问题时便于场主查找原因.采用图像截取方法仅采集对识别有用的图像信息,降低对存储空间及处理速度的要求,用较低成本的处理器替代高成本专用图像处理器,在硬件采集器中实现养殖渔场数据的识别.实验结果表明该系统具有实用性.     

3种本质安全评价方法在EDC过程中的应用研究

简要叙述ISI、i-safe和IBI 3种典型的本质安全评价方法,说明其含有的参数及指数的计算方法;然后使用这3种方法评价了直接氯化法、氧氯化法、改进的氧氯化法3个EDC生产流程.评价结果表明:不同方法评价相同的几个过程,得到的各过程安全性的高低是一致的:直接氯化法最高、氧氯化法次之、改进的氧氯化法安全性最差:评价同一个流程时,ISI法评价得到的数值最大,i-Safe法次之,IBI法最小.结合评价的过程从参数的个数及覆盖面的大小、参数取值的主观性程度、获取所需信息的难易程度和结果的灵敏性4方面比较和分析3种评价方法,最后总结得到3种方法中IBI法的优势最大.     

ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.     

雷达视频回波信号实时采集、压缩转发装置

介绍了一种基于FPGA和DSP的六通道雷达视频回波实时信号采集、压缩转发装置,该装置单通道采样率为20MSPS,采样精度为12bit,采集后的数据经过DSP压缩处理后再转化为2Mbps的PCM码流,实时发送给遥测发射机进行遥测下传和实时检测;并对相位一致性控制、基于流水线的数据处理方法等关键技术做了详细介绍;该装置已成功应用于某飞行器综合匹配试验,其性能和指标均优于应用要求。     

Countering the loss of extended vigilance in supervisory control using a fuzzy logic model

When an operator first detects unusual and/or infrequent or irregular signals in a system, the operator does not need to take any action, but must increase his/her level of attention and be alert for any more serious signals that may confirm a problem with the system. This is referred to as extended vigilance. The purpose of this study was to construct a fuzzy vigilance-measuring model for countering the loss of extended vigilance. The model extends two-valued logic (“Yes” or “No”) to multi-valued logic through fuzzy sets. Then a fuzzy logic alarm was developed by the model for combating the extended vigilance decrement. The first experiment compared the effect of the fuzzy measuring model with signal detection theory (SDT) and discussed the relationship between preliminary and extended vigilance for a simulated feed-water monitoring system. The results indicated that the sensitivity of the fuzzy vigilance-measuring model is better than index d′ and β, and that the preliminary vigilance significantly influences the extended vigilance. The second experiment verified the effect of the fuzzy logic alarm. The results indicated that the effect of the fuzzy logic alarm for combating the extended vigilance decrement is significant. When the preliminary vigilance is poor, an appropriate alarm will improve the extended vigilance. However, if the preliminary vigilance is very poor, the improvement of the extended vigilance will be limited.Relevance to industry: The extended vigilance is a new and important issue in human performance problems in industry, particularly in such areas as air-traffic control, industrial inspection and power plant monitor. The measuring model of vigilance could be applied to develop an alarm for promoting supervisory performance of human and human–machine detectors.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

A decision support system for fisheries management using operations research and systems science approach

In this paper, we present a general framework, using a systems science approach, for developing a decision support system (DSS) for fisheries management. Decision support systems are quantitative tools for managers to evaluate outcomes of their policies prior to implementation. Our fishery model considers multiple stocks and fisheries simultaneously in balancing catch among targeted and protected fish abundances. Since in the Northeastern US multispecies fishery the distribution of abundance, catch-per-unit-effort and bycatch vary geographically, we focus on a spatial management approach to address their spatial variability. The core component of this DSS applies operations research techniques of simulation and optimization to determine the optimal inter-annual and intra-annual fishing plans in terms of fishing efforts in each sub-area and the time period. The result is the recommended amount to catch from each fish species at each sub-area at any time period so that while management objectives for sustainability of fish stocks are satisfied, the value of landings is maximized. The graphical user interface of the proposed DSS helps users to define inputs, to set constraints and sub-area boundaries, and to visualize the outcomes.