Parameterized complexity of control problems in Maximin election

Elections are a central model in a variety of areas. This paper studies parameterized computational complexity of five control problems in the Maximin election. We obtain the following results: constructive control by adding candidates is W[2]-hard with respect to the parameter “number of added candidates”; both constructive and destructive control by adding/deleting voters are W[1]-hard with respect to the parameter “number of added/deleted voters”.     

A class of aggregation functions encompassing two-dimensional OWA operators

In this paper we prove that, under suitable conditions, Atanassov’s K_α operators, which act on intervals, provide the same numerical results as OWA operators of dimension two. On one hand, this allows us to recover OWA operators from K_α operators. On the other hand, by analyzing the properties of Atanassov’s operators, we can generalize them. In this way, we introduce a class of aggregation functions - the generalized Atanassov operators - that, in particular, include two-dimensional OWA operators. We investigate under which conditions these generalized Atanassov operators satisfy some properties usually required for aggregation functions, such as bisymmetry, strictness, monotonicity, etc. We also show that if we apply these aggregation functions to interval-valued fuzzy sets, we obtain an ordered family of fuzzy sets.     

Embedding HMMs-based models in a Euclidean space: the topological hidden Markov models

Current extensions of hidden Markov models such as structural, hierarchical, coupled, and others have the power to classify complex and highly organized patterns. However, one of their major limitations is the inability to cope with topology: When applied to a visible observation (VO) sequence, the traditional HMM-based techniques have difficulty predicting the n-dimensional shape formed by the symbols of the VO sequence. To fulfill this need, we propose a novel paradigm named “topological hidden Markov models” (THMMs) that classifies VO sequences by embedding the nodes of an HMM state transition graph in a Euclidean space. This is achieved by modeling the noise embedded in the shape generated by the VO sequence. We cover the first and second level topological HMMs. We describe five basic problems that are assigned to a second level topological hidden Markov model: (1) sequence probability evaluation, (2) statistical decoding, (3) structural decoding, (4) topological decoding, and (5) learning. To show the significance of this research, we have applied the concept of THMMs to: (i) predict the ASCII class assigned to a handwritten numeral, and (ii) map protein primary structures to their 3D folds. The results show that the second level THMMs outperform the SHMMs and the multi-class SVM classifiers significantly.     

Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data

In order to obtain high quality data, the correction of atmospheric perturbations acting upon land surface reflectance measurements recorded by a space-based sensor is an important topic within remote sensing. For many years the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and the Simplified Method for Atmospheric Correction (SMAC) codes have been used for this atmospheric correction, but previous studies have shown that in a number of situations the quality of correction provided by the SMAC is low. This paper describes a method designed to improve the quality of the SMAC atmospheric correction algorithm through a slight increase in its computational complexity. Data gathered from the SEVIRI aboard Meteosat Second Generation (MSG) is used to validate the additions to SMAC, both by comparison to simulated data corrected using the highly accurate 6S method and by comparison to in-situ and 6S corrected SEVIRI data gathered for two field sites in Africa. The additions to the SMAC are found to greatly increase the quality of atmospheric correction performed, as well as broaden the range of atmospheric conditions under which the SMAC can be applied. When examining the Normalised Difference Vegetation Index (NDVI), the relative difference between SMAC and in-situ values decreases by 1.5% with the improvements in place. Similarly, the mean relative difference between SMAC and 6S reflectance values decreases by a mean of 13, 14.5 and 8.5% for Channels 1, 2 and 3 respectively. Furthermore, the processing speed of the SMAC is found to remain largely unaffected, with only a small increase in the time taken to process a full SEVIRI scene. Whilst the method described within this paper is only applicable to SEVIRI data, a similar approach can be applied to other data sources than SEVIRI, and should result in a similar accuracy improvement no matter which instrument supplies the original data.     

基于Web Services的教学支持系统的设计与实现

随着信息技术的迅速发展,教育公司追求教学支持手段的信息化。针对合作院校数量多、参与者角色复杂、教学资料种类繁多等特点,构建基于Web Services上的B/S三层架构的教学支持系统,协助公司日常教学支持和实现资料的分享。通过该系统,合作院校的教学负责人能实现对本校教师的动态管理;支持人员能随时了解讲师授课情况;院校授课讲师能随时下载教学资料等。系统的初步成功运行,证明了应用Web Services技术方案的可行性,这对教育支持手段的信息化有一定的参考意义。     

基于无线通信实现方式的PLC网络研究

针对PLC控制系统在工业领域中的应用需求,分析了PLC-DCS控制网络结构,对比总结了三类PLC网络的无线通讯实现方式;通过对不同类型实现PLC无线网络的硬件拓扑结构和组网要点的分析,总结了各种方式的应用特点,并比对了它们的适用场合及局限性,以便针对不同PLC的无线通讯模式,进行具体方案的设计。     

基于S3C2440的嵌入式Linux内核设计

该文介绍了三星公司的基于ARM9内核S3C2440芯片嵌入式Linux系统设计。在确认已经移植好的U-boot的基础上,进行控制模块基于ARM9的Linux嵌入式系统设计方案,裁剪并移植Linux内核。     

$3C2510A的SCARA机械臂控制系统设计

在目前机械臂控制系统中,如何减小系统体积、降低系统功耗一直是传统控制方式（即“PC／工控机＋运动控制卡”）的难点。本文在对SCARA机械臂深入研究的基础上通过S3C25IOA实现了带有PCI接口的控制系统,并进行了Bootloader的移植以及PCI驱动程序的编写。     

Cortex—M3的生态物联网数据采集分站设计

以Cortex—M3处理器LM3S811为核心,设计了面向森林生态监测的物联网数据采集终端分站系统。通过单总线数字式温湿度传感器、烟雾传感器、CO2传感器和环境光亮度传感器分别采集温度、湿度、可燃性颗粒物、CO2含量和光照等与林木生态相关的环境信息和林场防火的相关信息。由LM3S81l处理器处理并添加分站ID和校验码后...     

A high quality and small shadow size visual secret sharing scheme based on hybrid strategy for grayscale images

Many secret sharing schemes for digital images have been developed in recent decades. Traditional schemes typically must deal with the problem of computational complexity, and other visual secret sharing schemes come with a higher transmission cost and storage cost; that is, each shadow size is m times as big as the original secret image. The new (2,n) secret sharing scheme for grayscale images proposed in this paper is based a combination of acceptable image quality using block truncation coding (BTC), high compression ratio discrete wavelet transform (DWT) and good subjective performance of the vector quantization (VQ) technique. Experimental results confirm that our proposed scheme not only generates a high quality reconstructed original image but also generates small, random-like grayscale shadows.