Synthesis,lattice energy and microwave dielectric properties of BaCu2-xCoxSi2O7 ceramics

BaCu_2-xCo_xSi₂O₇ solid solutions with orthorhombic structure (Pnma) were prepared by solid-state reaction method. The phase synthesis process, structural evolution and microwave dielectric properties of BaCu_2-xCo_xSi₂O₇ ceramics were investigated. Single BaCu₂Si₂O₇ phase was obtained when calcined at 950 °C for 3 h and was decomposed into BaCuSi₂O₆ phase when calcined at 1075 °C for 3 h. The sintering process was effectively promoted when Cu²⁺ was replaced by Co²⁺ and the maximum solubility of BaCu_2-xCo_xSi₂O₇ was located between 0.15 and 0.20. P-V-L complex chemical bond theory and Raman spectra were used to explain the structure-property correlations of BaCu_2-xCo_xSi₂O₇ ceramics. The corrected dielectric constant (ε_r-corr) of BaCu_2-xCo_xSi₂O₇ ceramics decreased monotonously with the susceptibility (Σχ^μ) and ionic polarizability of primitive unit cell. The quality factor (Q × f) increased with bond strength and lattice energy (U_cal), especially the lattice energy of the Si-O bond. The temperature coefficient of resonant frequency (τ_f) was determined by the susceptibility and lattice energy of the Cu/Co-O bond. The following optimum microwave dielectric properties were obtained at x = 0.15 when sintered at 1000 °C for 3 h: ε_r = 8.45, Q×f =58958 GHz and τ_f = -34.4 ppm/°C.     

Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.     

Nickel foam-supported Fe,Ni-Polyporphyrin microparticles: Efficient bifunctional catalysts for overall water splitting in alkaline media

Developing highly active, stable and sustainable electrocatalysts for overall water splitting is of great importance to generate renewable H₂ for fuel cells. Herein, we report the synthesis of electrocatalytically active, nickel foam-supported, spherical core-shell Fe-poly(tetraphenylporphyrin)/Ni-poly(tetraphenylporphyrin) microparticles (FeTPP@NiTPP/NF). We also show that FeTPP@NiTPP/NF exhibits efficient bifunctional electrocatalytic properties toward both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER). Electrochemical tests in KOH solution (1 M) reveal that FeTPP@NiTPP/NF electrocatalyzes the OER with 100 mA cm⁻² at an overpotential of 302 mV and the HER with 10 mA cm⁻² at an overpotential of 170 mV. Notably also, its catalytic performance for OER is better than that of RuO₂, the benchmark OER catalyst. Although its catalytic activity for HER is slightly lower than that of Pt/C (the benchmark HER electrocatalyst), it shows greater stability than the latter during the reaction. The material also exhibits electrocatalytic activity for overall water splitting reaction at a current density of 10 mA cm⁻² with a cell voltage of 1.58 V, along with a good recovery property. Additionally, the work demonstrates a new synthetic strategy to an efficient, noble metal-free-coordinated covalent organic framework (COF)-based, bifunctional electrocatalyst for water splitting.     

Electrochemical characteristics of heme proteins in hydroxyethylcellulose film

A stable film made from hydroxyethylcellulose (HEC) on pyrolytic graphite (PG) electrode was employed for incorporating hemoglobin (Hb), myoglobin (Mb) and horseradish peroxidase (HRP), and the electrochemical characteristics of the proteins were studied correspondingly. Experimental results revealed that HEC film could greatly accelerate electron transfer between the proteins and electrode, and the proteins showed a thin layer electrochemical behavior in the film. Moreover, all the proteins in the film exhibited good catalytic activity towards the reduction of hydrogen peroxide (H₂O₂) in the low H₂O₂ concentration range. In the high concentration range, H₂O₂ would exhibit toxicity effect on the proteins. The electrochemical properties and electrocatalytic abilities of the three heme proteins in HEC film have been compared, and the optimal conditions for H₂O₂ biosensor fabrication have been obtained.     

An SVD-based image watermarking in wavelet domain using SVR and PSO

The paper presents a novel blind watermarking scheme for image copyright protection, which is developed in the discrete wavelet transform (DWT) and is based on the singular value decomposition (SVD) and the support vector regression (SVR). Its embedding algorithm hides a watermark bit in the low–low (LL) subband of a target non-overlap block of the host image by modifying a coefficient of U component on SVD version of the block. A blind watermark-extraction is designed using a trained SVR to estimate original coefficients. Subsequently, the watermark bit can be computed using the watermarked coefficient and its corresponding estimate coefficient. Additionally, the particle swarm optimization (PSO) is further utilized to optimize the proposed scheme. Experimental results show the proposed scheme possesses significant improvements in both transparency and robustness, and is superior to existing methods under consideration here.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.     

Safety-based availability assessment at design stage

The availability of a system or equipment is one of the crucial characteristics that measures the customer satisfaction and strongly influences his final choice decision between concurrent products. The aim of this work is to provide an approach to improve the products availability assessment by taking into account the safety criteria by considering the use situations at design stage. Our work focuses on the routine design of complex products. The availability is often simply estimated considering reliability and maintainability. Basically, the intrinsic availability is the probability that it is operating satisfactorily at any point in time when used under conditions stated by design specifications. The time considered includes operating time and active repair time. Thus, intrinsic availability excludes from consideration all other times in the product lifecycle such as: accident management time, storage time, administrative time or logistic time. But many studies show that the loss of availability performance is also due to accidents that occur in different unforeseeable utilization situations. This engenders stops of the system to ensure the users safety according to standards recommendations. In this purpose, we consider the structural product architecture and the different use cases that correspond to the operational states and downtimes due to stop events that may happen during the utilization like failures, maintenance tasks and accidents. Then, we propose a product behavioral analysis including the use cases to describe interactions between the product and users or maintenance operators. We use Markov chains to model the use cases corresponding to operating time (OT), maintenance time (MT) and preparing time after accidents (RT). Then these three parameters are considered to specify a generic approach to improve the availability assessment. Such an approach provides the traceability of the product behavior along its lifecycle. In this way, the main causes of stop can be identified and this may guide the designer for improving the availability of the product future versions. To validate our approach, an application is presented considering a printing line. The comparison of our simulation considering an industrial case study shows a good agreement about the influence of safety on the availability.     

改进Mask R-CNN算法的带钢表面缺陷检测

在带钢的生产过程中可能会因为生产工艺的问题导致带钢表面出现缺陷,传统的带钢表面检测方法存在检测速度慢、检测精度低等问题。在计算机深度学习快速发展的今天,为实现带钢表面缺陷快速有效的检测,提出改进的掩码区域卷积神经网络（Mask R-CNN）算法,使用[k]-means II聚类算法改进区域建议网络（RPN）锚框生成方法;同时调整Mask R-CNN模型的网络结构,去掉掩码分支,提高了模型的缺陷检测速度。实验在NEU-DET数据集的5种缺陷检测中将原算法的均值平均精度（mAP）从0.810?2提升到0.960?2,检测速度达到5.9?frame/s。并且能够实现对缺陷目标的检测和实例分割,以便研究人员观测缺陷的大小和形状,从而改进工艺。相比于目前其他深度学习的缺陷检测算法,更能满足带钢的生产检测要求。     

彩色图像的稀疏分解

图像稀疏分解是基于过完备原子库的一种图像表示方法,主要在灰度图像中应用.本文在分析灰度图像稀疏分解的基础之上,将其应用到彩色图像处理之中,实现了在RGB和YUV两种颜色模型下的匹配追踪稀疏分解.实验表明,YUV颜色模型更适合低码率彩色图像稀疏分解.