A new multi‐focus image fusion algorithm based on BEMD and improved local energy

A multi‐focus image fusion method, which is based on bidimensional empirical mode decomposition (BEMD) and improved local energy algorithm, is presented in this paper. First, the source image is decomposed by BEMD. Then maximum criterion combined with weighted average fusion rule based on local energy is applied to bidimensional intrinsic mode function components of the corresponding frequency segment. If the phase of the bidimensional intrinsic mode function coefficients decomposed by BEMD on two source images is the same, the local energy maximum criterion is used in the frequency coefficients of the fused image; else, if the corresponding phase is opposite, bidimensional intrinsic mode function coefficients of the fused image is determined by a weighted average method based on local energy. Finally, the fusion result is obtained by the inverse BEMD transformation on the fusion coefficient. Simulation shows that the proposed algorithm significantly outperforms traditional methods such as the maximum criterion, weighted average, and wavelet fusion rules. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Non‐cooperative game‐based packet ferry forwarding for sparse mobile wireless networks

In sparse mobile wireless networks, normally, the mobile nodes are carried by people, and the moving activity of nodes always happens in a specific area, which corresponds to some specific community. Between the isolated communities, there is no stable communication link. Therefore, it is difficult to ensure the effective packet transmission among communities, which leads to the higher packet delivery delay and lower successful delivery ratio. Recently, an additional ferry node was introduced to forward packets between the isolated communities. However, most of the existing algorithms are working on how to control the trajectory of only one ferry work in the network. In this paper, we consider multiple ferries working in the network scenario and put our main focus on the optimal packet selection strategy, under the condition of mutual influence between the ferries and the buffer limitation. We introduce a non‐cooperative Bayesian game to achieve the optimal packet selection strategy. By maximizing the individual income of a ferry, we optimize the network performance on packet delivery delay and successful delivery ratio. Simulation results show that our proposed packet selection strategy improves the network performance on packet delivery delay and successful delivery ratio. Copyright © 2013 John Wiley & Sons, Ltd.     

Sparse LMS/F algorithms with application to adaptive system identification

Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal‐to‐noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is slow convergence speed in high SNR case. Many finite impulse response systems are modeled as sparse rather than traditionally dense. To take advantage of system sparsity, different sparse LMS algorithms with l_p‐LMS and l₀‐LMS have been proposed to improve adaptive identification performance. However, sparse LMS algorithms have the same drawback as standard LMS. Different from LMS filter, standard LMS/F filter can achieve better performance. Hence, the aim of this paper is to introduce sparse penalties to the LMS/F algorithm so that it can further improve identification performance. We propose two sparse LMS/F algorithms using two sparse constraints to improve adaptive identification performance. Two experiments are performed to show the effectiveness of the proposed algorithms by computer simulation. In the first experiment, the number of nonzero coefficients is changing, and the proposed algorithms can achieve better mean square deviation performance than sparse LMS algorithms. In the second experiment, the number of nonzero coefficient is fixed, and mean square deviation performance of sparse LMS/F algorithms is still better than that of sparse LMS algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

Elicitation of subjective probabilities for economic risk analysis: An investigation

This paper investigates three major issues regarding the elicitation of expert knowledge for economic risk analysis: (1) recognition of some of the implicit assumptions and beliefs; (2) development of an approach to elicit expert knowledge as accurate, calibrated and coherent subjective probabilities; and (3)a study to explore human ability to predict future events and the validity of the implicit assumptions and beliefs in the context of the expert judgements. The proposed elicitation approach combines the theoretical requirements for valid subjective probabilities with a practical process. The recognition that some of the implicit assumptions and beliefs in engineering risk analysis should be explored when dealing with the human ability to predict future events, and the inherent difficulties in developing experiments and methods to test such beliefs arc some of the benefits of the study. Directions for future work are suggested.     

钛铁试剂共振散射法测定废胶片中的银含量

在p H 3.5的B-R(Britton-Robinson)缓冲溶液中,钛铁试剂(Tiron)和Ag(Ⅰ)在室温下发生配位反应,使得体系在323 nm处产生1个较强的共振散射峰。在优化实验条件下,体系的共振散射强度增加值(ΔI)与Ag(Ⅰ)的质量浓度(0.010~4.0μg/m L范围内)呈良好的线性关系,其检出限为27.4 ng/m L。该法操作简便、灵敏度高、选择性好,用于废胶片中Ag含量的测定,回收率为96.8%~98.7%。     

Covariance‐based hardware selection part IV: Solution using the generalized benders decomposition

Recently the covariance based hardware selection problem has been shown to be of the mixed integer convex programming (MICP) class. While such a formulation provides a route to global optimality, use of the branch and bound search procedure has limited application to fairly small systems. The particular bottleneck is that during each iteration of the branch and bound search, a fairly slow semi‐definite programming (SDP) problem must be solved to its global optimum. In this work, we illustrate that a simple reformulation of the MICP and subsequent application of the generalized Benders decomposition algorithm will result in massive reductions in computational effort. While the resulting algorithm must solve multiple mixed integer linear programs, this increase in computational effort is significantly outweighed by the reduction in the number of SDP problems that must be solved. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3628–3638, 2016     

Fenton技术中残余组分对COD测定的干扰和消除研究

Fenton试剂与水样中难降解有机物反应后,残余组分会对后续水样COD测定产生干扰。实验表明,Fenton试剂残余组分中H_2O_2对COD测定产生的干扰较大,其对水样COD测定产生的影响值与H_2O_2浓度成良好的线性关系,而残余组分Fe~(2+)对COD测定产生的干扰与H_2O_2相比,影响值较小,可忽略其影响。通过对比分析掩蔽剂法、催化分解法对H_2O_2干扰消除试验得出,掩蔽剂Na_2SO_3能够迅速的与H_2O_2发生反应,消除H_2O_2的干扰,但掩蔽剂Na_2SO_3也会对水样COD产生一定的干扰,测量结果偏差较大;MnO_2催化分解H_2O_2的效率较高,很好的消除H_2O_2的干扰,但MnO_2分解后水样COD测定值需乘以折减系数0.89,满足试验精度的要求;过氧化氢酶可以将H_2O_2完全分解,分解效率较高,干扰消除效果较好。     

钼(Ⅵ)-PV-CV体系共振瑞利散射法测定痕量钼

在p H为3.5的邻苯二甲酸氢钾-盐酸缓冲溶液中,在聚乙烯醇存在下,钼(Ⅵ)与邻苯二酚紫(PV)形成的配阴离子[Mo(PV)2]2-与结晶紫(CV)阳离子结合形成的离子缔合物具有较强的共振瑞利散射光谱。其最强共振瑞利散射峰位于647 nm处。基于共振瑞利散射峰的逐渐增强,建立了测定痕量钼(Ⅵ)的共振瑞利散射法。该方法钼(Ⅵ)质量浓度在0.1~0.6 mg/L范围内与共振瑞利散射光强度呈良好的线性关系,检测限为1.5×10-4 mg/L,可用于水样中钼的测定。     

氨分解制氢催化剂研究进展

随着环保法规日趋严格,清洁氢能的生产和应用引起关注,氨分解制氢是其中重要途径之一。综述Ru、Ni和Fe等氨分解催化剂的研究进展,Ru催化剂具有较高的催化活性,但由于资源有限和价格昂贵等因素使其在工业应用方面受到限制。以Fe和Ni为代表的非贵金属催化剂资源丰富,价格低廉,氨分解反应转化率高,具有潜在的工业应用前景。我国独创的新一代Fe_(1-x)O基新型熔铁催化剂是目前世界上活性最高的氨合成催化剂,根据微观可逆性原理,新型熔铁催化剂也是氨分解反应活性最好的制氢催化剂。