Sharing your view: A distributed user interface approach for reviewing emergency plans

Emergency planning is an ongoing activity in which a multidisciplinary group of experts intermittently collaborate to define the most appropriate response to risks. One of the most important tasks of emergency planning is the review of plans as a way of maintaining, refining, and improving them. This review of plans is based on exchanging knowledge and experiences in order to take into account different perspectives and generate alternative solutions. An exploratory case study carried out within municipal organizations has disclosed how the application of rigid plan reviewing practices hinders team creativity and, consequently, effective decision-making. This paper presents a computer-based collaborative environment aimed at supporting unstructured team discussion during the post-hoc review of emergency plan. This collaborative environment allows emergency planning team members to share their view in a free manner by interacting with user interface components distributed across several input and output dimensions. The usage of the environment has proved how the application of new interactive technologies can create more dynamic work settings, fostering team creativity.     

一种多参数优化的联合信源信道编码方法*

针对JPEG2000码流的渐进传输特性,提出了一种多参数优化的联合信源信道编码方法,即MPO-JSCC。在码率分配的基础上,动态地选择Turbo码交织长度、迭代译码次数,通过优化编码器多个参数更好地执行不等差错保护策略,同时加入JPEG2000容错工具,在接收端利用错误掩藏机制以提高图像解码成功率。将该方法应用于噪声信道的图像传输系统中,仿真结果表明,MPO-JSCC既能在不增加系统复杂度及延迟时间的同时提高重建图像的质量,又能节省系统发射功率,具有一定的现实指导意义。     

交织和BCH编码对蓝牙2.0数据传输性能的改善

蓝牙2.0+EDR规范新增DH分组没有有效的纠错机制,其抗干扰能力差。通过在新规范中加入BCH编码和交织编码,以改善蓝牙的数据传输吞吐量及抗干扰能力。对于新增的数据分组,根据蓝牙标准协议,推导了相应的分组特性;建立了GE信道下数据传输速率与信道突发错误水平的关系模型;获得了在不同信道突发错误水平下的数据传输吞吐量。结果表明,在蓝牙2.0+EDR新规范中加入BCH编码和交织编码,在较高突发错误水平的信道中,其数据传输吞吐量提高了一倍以上,明显改善了数据传输的抗干扰能力。     

数字光接收机性能指标的优化设计

首次提出一种新型数字光接收机模型,改进了其中均衡器的设计;以S.D.Personick理论为基础,推导并计算了此光接收机基于"最坏情况"下判决时刻的噪声平均功率。研究结果表明,此模型在输入脉冲展宽较为严重的情况下表现出了良好的噪声性能;进而提高了数字光接收机的灵敏度,优化了数字光纤传输系统的误码性能;为改善数字光接收机性能指标提出了新的途径。     

准正交空时分组码的自适应设计

为了能在满足空时分组码完全分集的同时尽可能降低译码复杂度,提出了准正交空时分组码的自适应设计方案. 在准正交空时分组码的编码结构上添加自适应系数,根据当前信道状态信息计算自适应系数的具体数值. 设计的目的是保证传输的数据符号之间相互正交,彼此没有干扰,从而实现完全分集,并能采用复杂度低的单符号译码方法. 仿真结果表明,准正交空时分组码自适应方案的误码率性能要明显好于采用星座旋转的准正交空时分组码方案,只需要采用有限反馈的方法就能实现近似理想反馈的误码率性能.      

车载自组织网络分布式入侵检测算法研究

随着汽车产业的发展,汽车给我们带来便利的同时也给我们带来一系列的问题,例如交通拥堵、交通安全等。为了解决这些问题车载自组织网络应运而生。但是车载自组织网络中信息安全问题一直存在,采用分布式入侵检测模型和基于此模型下的改进随机森林分类算法可以很好地解决这个问题。     

The design and analysis of unequal error protection fountain coding for multiple source networks over binary erasure channels

A novel network model of multiple source fountain coding is developed and a novel class of generic multiple source fountain codes with unequal error protection(UEP)property is proposed.The And–Or tree analysis technique is generalized to analyze the asymptotic performance of the proposed codes and a joint optimization method employing both linear and nonlinear programs is developed to optimize the degree distributions.Furthermore,we propose three basic methods to achieve UEP property and the performance of each method is discussed.We employ these analytical results and optimization method to design and discuss several UEP codes with two and four sources for different application scenarios.Simulation results verify that the proposed codes can be applied to the networks with any number of sources and can provide strong UEP property in various ways based on the proposed three basic methods.     

A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network

This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts; (2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.     

Blind recognition algorithm for IRA codes in noisy environment

For noisy environment, the parity-check matrix of Irregular Repeat-Accumulate(IRA) codes is hard to reconstruct, moreover, the relationships of the large-scale complex interleaver are hard to recover. To solve the problems, a novel blind recognition algorithm is proposed. First, the code's length and synchronization are identified by applying rank criteria. Second, by implementing matrix transformation, the dual vectors of codewords are found. Then, by setting a threshold, the effective parity-check vectors of dual space are selected. According to the sparse characteristics of the IRA codes' parity-check matrix, the parity matrix can be reconstructed with effective parity-check vectors Finally, relationships of the interleaver can be recovered according to the characteristics of IRA codes. Simulation results show that the proposal can be used to estimate IRA codes encoding parameters and complete the blind recognition in the non-cooperative context with noise.