A novel multi-focus image fusion method based on distributed compressed sensing

Multi-focus image fusion aims to produce an all-in-focus image by merging multiple partially focused images of the same scene. The main work is identifying the focused region and then composing all the focused regions. In this paper, a novel efficient multi-focus image fusion method based on distributed compressed sensing (DCS) is proposed. Firstly, the low-frequency and high-frequency images are obtained by comparing the variance of the source images, which are further utilized to get the low-frequency and high-frequency dictionaries. Secondly, DCS using joint sparsity model-1 (JSM-1) is applied to reconstruct the precise high-frequency images. Thirdly, the decision map is obtained based on all the high-frequency images and then improved by the morphological processing. Finally, the focused pixels are chosen from the source images through the decision map. Experimental results indicate that the proposed DCS-based method can be competitive with or even outperform some state-of-the-art methods in terms of both visual and quantitative metric evaluations.     

Dynamics of a family of continued fraction maps

We explore the dynamics of a 1-parameter family of continued fraction maps of the unit interval. The family contains as special instances the Gauss continued fraction map and the Fibonacci map. We determine the transfer operators of these dynamical maps and prove that the Denjoy–Minkowski measure is a common invariant measure of the family. We show that their analytic invariant measures obey a common functional equation generalizing Lewis’ functional equation and we find a.c. invariant measures for some members of the family. We also discuss a certain involution of this family which sends the Gauss map to the Fibonacci map relating Riemann's zeta function to the so-called Fibonacci zeta function.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

二维反三角超混沌系统及其在图像加密上的应用

为了进一步提高混沌系统的混沌特性，为图像加密算法提供更可靠的混沌系统，增强图像加密算法的安全性，提出了一种基于二维反三角超混沌系统的新型图像加密算法。首先，在一维三角混沌函数的基础上构建了一个二维反三角超混沌系统，通过分岔图和Lyapunov指数等仿真实验，验证了该系统具有更广的混沌区间和更强随机性的迭代序列，遍历性更加优秀；然后，基于此混沌系统，采用"置乱-扩散"策略，根据不同密钥生成的不同超混沌序列，对图像矩阵进行无重复置乱和循环移位扩散，循环三次得到密文，完成加密过程；最后，对图像加密方案进行了直方图分析、密钥空间分析、相邻像素相关性分析、明文敏感性分析和信息熵分析等性能测试。其中密文图像的相关指标参数像素变化率（NPCR）和统一平均变化强度（UACI）的测试值非常接近于它们的理想期望值，信息熵的测试结果约为7.997，也非常接近于理想期望值8。实验结果表明，此图像加密系统具有更可靠的安全性，抵抗攻击能力强，在图像安全领域具有较好的应用前景。     

综放高瓦斯矿井煤层瓦斯涌出量综合预测

为了成功预测竹林山煤矿综放高瓦斯矿井大采高工作面煤层瓦斯涌出量,以主采3号煤层为主要研究对象,针对3号煤层以往开采情况,通过布设测点测量其煤层瓦斯含量和了解相邻矿井瓦斯含量,采用分源预测法、回归法及统计法等预测方法得到了3号煤层瓦斯含量的分布规律,并绘制了3号煤层的瓦斯含量等值线图。对矿井不同生产时期的瓦斯含量进行预测,得到了生产前期、中期及后期采区的最大绝对瓦斯涌出量和最大相对瓦斯涌出量,说明了竹林山煤矿各个时期均属于高瓦斯矿井。     

Sag in drying coatings: Prediction and real time measurement with particle tracking

Sag is a coating phenomenon characterized by gravity-driven flow after deposition; excessive amounts of sag can lead to coating defects. In this work, a new method for evaluating and quantifying sag is investigated. The motion of micron-sized Lycopodium spores on an inclined coating surface is tracked during drying, and the resulting surface velocity data is used to determine sag length. This in situ particle tracking method is minimally invasive and permits real time measurements. Measured sag lengths and real time surface velocities in aqueous polyvinyl alcohol solution coatings compare well with a theoretical model. The model is also used to develop a predictive sag regime map, which anticipates the extent of sag given coating properties and process-specific parameters. This map also identifies viable processing windows and aids in intelligent coating design given specific process constraints. The predictions of the sag regime map are compared against experimental sag results from polyvinyl alcohol solution coatings as well as four commercial latex paints, revealing good agreement for coatings with Newtonian or ‘Newtonian-like’ rheologies.     

谐振变换器的ZVS软开关同步整流技术研究

以感应电能传输(IPT)谐振变换器为研究对象,研究了谐振变换器的ZVS同步整流(SR)技术。分析了基于SR技术IPT谐振变换器的工作原理,利用系统的谐振工作特性,提出了一种新颖的ZVS软开关SR实现方法。建立了系统频闪映射稳态数学模型,给出了ZVS软开关SR的周期不动点函数、数值求解状态变量及ZVS软开关SR工作周期的算法流程。在设计控制电路的基础上,通过实验验证了提出的同步整流技术的可行性。     

An FCM–FAHP approach for managing readiness-relevant activities for ERP implementation

Any organization which plans to introduce a new enterprise resource planning (ERP) system will carry out a range of activities to improve its readiness for the new system. This paper develops a new approach for managing these interrelated activities using fuzzy cognitive maps (FCMs) and the fuzzy analytical hierarchy process (FAHP). This approach enables the organization to (1) identify the readiness-relevant activities, (2) determine how these activities influence each other, (3) assess how these activities will contribute to the overall readiness and (4) prioritize these activities according to their causal interrelationships to allocate management effort for the overall readiness improvement. The approach first uses FCMs and a fuzzy connection matrix to represent all possible causal relationships between activities. It then uses FAHP to determine the contribution weights and uses FCM inference to include the effects of feedback between the activities. Based on the contribution and interrelationships between activities, a management matrix is developed to categorize them into four management zones for effective allocation of limited management efforts. An empirical study is conducted to demonstrate how the approach works.     

Genetic algorithm and self organizing map based fuzzy hybrid intelligent method for color image segmentation

The grouping of pixels based on some similarity criteria is called image segmentation. In this paper the problem of color image segmentation is considered as a clustering problem and a fixed length genetic algorithm (GA) is used to handle it. The effectiveness of GA depends on the objective function (fitness function) and the initialization of the population. A new objective function is proposed to evaluate the quality of the segmentation and the fitness of a chromosome. In fixed length genetic algorithm the chromosomes have same length, which is normally set by the user. Here, a self organizing map (SOM) is used to determine the number of segments in order to set the length of a chromosome automatically. An opposition based strategy is adopted for the initialization of the population in order to diversify the search process. In some cases the proposed method makes the small regions of an image as separate segments, which leads to noisy segmentation. A simple ad hoc mechanism is devised to refine the noisy segmentation. The qualitative and quantitative results show that the proposed method performs better than the state-of-the-art methods.