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Purpose: This paper aims to figure out the conundrum that the corrosion resistance longevity of steel wires for bridge cables was arduous to meet the requirements. Design/methodology/approach: The "two-step" hot-dip coating process for cable steel wires was developed, which involved first hot-dip galvanizing and then hot-dip galvanizing of aluminum magnesium alloy. The corrosion rate, polarization curve and impedance of Zn–6Al–1Mg and Zn–10Al–3Mg alloy-coated steel wires were compared through acetate spray test and electrochemical test, and the corrosion mechanism of Zn–Al–Mg alloy-coated steel wires was revealed. Findings: The corrosion resistance of Zn–10Al–3Mg alloy-coated steel wires had the best corrosion resistance, which was more than seven times that of pure zinc-coated steel wires. The corrosion current of Zn–10Al–3Mg alloy-coated steel wires was lower than that of Zn–6Al–1Mg alloy-coated steel wires, whereas the capacitive arc and impedance value of the former were higher than that of the latter, making it clear that the corrosion resistance of Zn–10Al–3Mg was better than that of Zn–6Al–1Mg alloy coating. Moreover, the Zn–Al–Mg alloy-coated steel wires for bridge cables had the function of coating "self-repairing." Originality/value: Controlling the temperature and time of the hot dip galvanizing stage can reduce the thickness of transition layer and solve the problem of easy cracking of the transition layer in the Zn–Al–Mg alloy coating due to the Sandelin effect. [ABSTRACT FROM AUTHOR]

Nowadays information is crucial in many fields such as medicine, science and business, where databases are used effectively for information sharing. However, the databases face the risk of being pirated, stolen or misused, which may result in a lot of security threats concerning ownership rights, data tampering and privacy protection. Watermarking is utilized to enforce ownership rights on shared relational databases. Many reversible watermarking methods are proposed recently to protect rights of owners along with recovering original data. Most state-of-the-art methods modify the original data to a large extent, result in data quality degradation, and cannot achieve good balance between robustness against malicious attacks and data recovery. In this paper, we propose a robust and reversible database watermarking technique, Genetic Algorithm and Histogram Shifting Watermarking (GAHSW), for numerical relational database. The genetic algorithm is used to select the best secret key for grouping database, where the watermarking can be embedded with balanced distortion and capacity. The histogram of the prediction error is shifted to embed the watermark with good robustness. Experimental results demonstrate the effectiveness of GAHSW and show that it outperforms state-of-the-art approaches in terms of robustness against malicious attacks and preservation of data quality. [ABSTRACT FROM AUTHOR]

Abstract As the commonest part of social networks, sharing images in social network not only provides more information, but also gives more intuitive view than text. However, images also can leak out information more easily than text, so the audit of image content is particularly essential. The disclosure of a tiny image, which involves sensitive information about individual, society even the state, may trigger a series of serious problems. In this paper, we design a kind of intelligent image firewall to detect and filter sensitive or privacy images. Two different approaches of the firewall are proposed. In the first approach, we propose an image firewall based on joint sparse representation, which can provide accurate and robust privacy prediction, and also can provide rich spatial relationship information. In the second approach, we propose a method based on the deep learning (Faster RCNN), which can predict the privacy relationships or actions (like kiss, hug and hand in hand) among the persons of an image. Experimental results show the effectiveness of the two kinds of approaches. [ABSTRACT FROM AUTHOR]

Efficiently photodegradation of 2-chlorophenol via preferential dechlorination on Z-scheme valence-mixed FePc/(1 0 0) BMO heterojunction with enhanced charge separation and Fe0/Fe2+ sites. [Display omitted] • Ultrathin (1 0 0)-BMO nanosheets with selective 2-CP adsorption were synthesized. • H-FePc/BMO heterojunction was prepared via H-bond assembly and H 2 – treatment. • Preferential dechlorination on BMO facilitate 2-CP degradation. • Z-scheme charge transfer between H-FePc and BMO enhanced charge separation. • Fe0/Fe2+ species promoted O 2 activation to further improve the activity. It is vital for selectively preferential dechlorination by visible-light photocatalysis to eliminate high-risk 2-chlorophenol (2-CP) contaminant. However, selective adsorption and efficient charge separation remain challenging. Herein, ultrathin (1 0 0) facet-exposed Bi 2 MoO 6 (BMO) nanosheets (∼6 nm thickness) with enhanced selective adsorption for 2-CP due to the Bi-Cl interaction and highly visible-light activity for 2-CP degradation have been synthesized via a pH-controlled microwave-assisted hydrothermal process. The visible-light activity could be improved by modifying iron phthalocyanines (FePc) via H-bond induced assembly and subsequent H 2 thermal treatment. The visible-light activity of as-optimized H 2 -treated heterojunction (H-FePc/BMO) was 4.5 and 2.5-time higher than BMO and FePc/BMO. Raman spectra, X-ray photoelectron spectrum, electron paramagnetic resonance, photoelectrochemical measurements, radical trapping experiment and ion chromatography, confirmed that the improved photoactivity of H-FePc/BMO could be attributed to the selective adsorption of 2-CP inducing photogenerated-holes as dominating active species with nearly 100% preferential dechlorination, the enhanced charge separation via Z-scheme transfer and the promoted O 2 activation from valence-mixed Fe0/Fe2+ species in FePc after H 2 treatment. This study may open up a new way to the high-efficiency degradation of chlorophenols using bismuth-containing oxide-based photocatalysts. [ABSTRACT FROM AUTHOR]

A series of novel cationic gemini surfactants, bis-( N-(3-alkylamido-propyl)- N, N-dimethyl)- p-phenylenediammonium dichloride, were synthesized. The structures of the gemini surfactants were characterized by IR, H NMR and C NMR. The Krafft temperatures of surfactants were determined through conductivity, the surface active properties in aqueous solution were studied at various temperatures by surface tension and conductivity. The thermodynamic functions of micellization process of the surfactants were also calculated by conductivity. The Krafft temperatures of the surfactants were 12, 13 and 28 °C. The values of CMC and Γ decreased with increasing the length of hydrophobic chains, but the values of CMC and α increased with increasing temperature. The process of micellization is a spontaneous, exothermic and entropy-driven process. [ABSTRACT FROM AUTHOR]

Due to structural heterogeneity, the main function and structure of networked systems are significantly influenced by some important nodes rather than each member. In practical, the properties of important nodes could be different from network to network, and thus a variety of algorithms have been specially designed to identify important nodes of different networks and of different dynamics. In this paper we propose a widely applicable algorithm by employing the percolation model in statistical physics, which describes the behavior of connected clusters when nodes are connected randomly. This algorithm appropriately combines the local and global properties of a network, thus it stresses the significance of nodes that neither have a visibly local importance, such as degree and clustering, nor have a visibly global importance, such as betweenness. The effectiveness of our algorithm has been illustrated in a series of networks, including model networks with different degree distributions and different degree correlations, and empirical networks. As a shell decomposition process, the framework of our algorithm has extensive application prospects in analyzing network structure, such as community, core–periphery structure, and shell structures. [ABSTRACT FROM AUTHOR]

The polarimetric synthetic aperture radar (PolSAR) usually has to be calibrated before practical application, so as to compensate for polarimetric distortion. The varying platform attitude is one of the factors causing distortion but has rarely been considered in existing polarimetric calibration algorithms. With the resolution of PolSAR systems improving and the synthetic aperture time prolonging, this factor cannot simply be ignored. The varying attitude will distort the polarimetric information by rotating the polarimetric orientation angle, and such distortion changes with azimuth time. In this article, we modified the conventional polarimetric system model to take account of the time-variant impact of the unstable platform attitude. A calibration algorithm is proposed to compensate the time-variant attitude impact on the raw return data. The proposed calibration algorithm is tested on the data collected by Institute of Electronics, Chinese Academy of Sciences P-band PolSAR system. Results show that it can achieve better performance by reducing crosstalk error than two conventional methods. [ABSTRACT FROM PUBLISHER]

The signal processing of the medium-Earth-orbit synthetic aperture radar (SAR) is more challenging than that of the current low-Earth-orbit SAR because the imaging geometry is more complicated, and the range and azimuth variances are more severe. This paper deals with these imaging problems in three aspects. First, an advanced hyperbolic range equation (AHRE) is proposed for the first time, which is more precise for a spaceborne SAR than the conventional hyperbolic range equation (CHRE). Second, the point target spectrum based on the AHRE is analytically derived, which is useful for developing efficient SAR processing algorithms. Third, the well-known nonlinear chirp scaling (NLCS) algorithm is modified according to this new spectrum, and the so-called AHRE-based advanced NLCS (A-NLCS) algorithm is established. The simulation results validate the correctness of our method for L-band SAR systems at altitudes from 1000 to 10 000 km with an azimuth resolution around 3 m. It is also shown that the A-NLCS algorithm has better performance than the CHRE-based algorithms in longer integration time cases. Therefore, we recommend the A-NLCS algorithm for a spaceborne SAR with a lower frequency, finer resolution, and higher satellite altitude. [ABSTRACT FROM AUTHOR]

In geosynchronous synthetic aperture radar (GEO SAR), the azimuth FM rate drastically falls and comes close to the variation rate of the Doppler centroid, due to the higher altitude. The effect of the variation of the Doppler parameters becomes significant and affects the azimuth resolution results. A concise azimuth resolution expression is deduced from the azimuth ambiguity function which involves the azimuth variance property and third‐order range equation. It is more accurate for GEO SAR than the conventional expression. Meanwhile, the phenomenon where the traditional frequency algorithm becomes invalid is found. However, the time domain algorithm is still applicable when the azimuth FM rate approaches zero. Finally, the simulation results of the point targets at five typical areas verify the analysis. [ABSTRACT FROM AUTHOR]

Under the premise of ensuring good speech quality and resistance to steganalysis, how to embed as much information as possible into low-bit-rate speech is a challenge. The existing research mainly focuses on least significant bits in the compressed speech streams or line spectral frequencies in the encoding processes of the G.723.1 and G.729a codecs. In this paper, we are concentrating on steganography in Internet Low Bitrate Codec speech streams. Specifically, we present a novel steganographic method on the basis of the gain quantization (GQS), which is included in the vector quantization of dynamic codebooks. The secret information is embedded by modifying the search range of the gain codebook to quantize the gain value. The experimental results show that the proposed GQS method achieves a higher hiding capacity, less signal distortion, and better resistance to steganalysis. [ABSTRACT FROM AUTHOR]

Abstract Herein, we report a feasible and rapid route for the preparation of Sm-Cu intermetallic compounds used as an effective metal catalyst. The electrochemical processes of the co-reduction of Sm(III) and Cu(II) ions on Mo electrode or copper-coated Mo electrode in molten LiCl-KCl-CuCl 2 -SmCl 3 system at 873 K were explored. The electrochemical behaviors of Sm(III), Cu(II) ions and intermetallic compounds formation in the melt were investigated by cyclic voltammetry (CV), chronopotentiometry, square wave voltammetry (SWV) and open-circuit chronopotentiometry (OCP), respectively. Our studies showed that the reduction of Cu(II) ions to Cu(0) metal involves two electrochemical steps, Cu(II)/Cu(I) and Cu(I)/Cu(0). Subsequently, Sm-Cu intermetallic compounds (SmCu 6 , SmCu 5 and SmCu) were synthesized by a potentiostatic electrolysis method. As the electrode potential becomes increasingly negative, the formation of Sm-Cu intermetallic compounds gradually changes from Cu-rich side phases (SmCu 6) to Sm-rich side phases (SmCu) with Sm-Cu alloys formed as single-crystal intermetallics. The crystal structures of Sm-Cu intermetallic compounds were characterized by X-ray diffraction (XRD), selected-area electron diffraction (SAED) and high-resolution transmission electron microscopy (HRTEM). Moreover, the morphology and chemical state of the constituting elements were investigated by scanning electron microscopy (SEM) with energy dispersive spectrometry (EDS) analyses and X-ray photoelectron spectroscopy (XPS). The dendritic formation of Sm-Cu intermetallic compounds was characterized through nitrogen adsorption-desorption isotherms analysis. The formed Sm-Cu alloys contain hierarchical mesopores with different identified types of mesoporosity. The surface areas of SmCu 6 , SmCu 5 and SmCu calculated from Brunauer-Emmett-Teller (BET) equation were 2.798 m2/g, 3.801 m2/g, 1.688 m2/g, respectively. Highlights • The Sm-Cu intermetallic compounds with different phases were successfully fabricated by molten salt electrolysis. • Dendrite grain refinement and phase transformation during codeposition were investigated. • The effects of different potentials on the morphology of the porous structure of Sm-Cu intermetallic compounds were studied. • A significant improvement in the surface areas and parameter C values was achieved. [ABSTRACT FROM AUTHOR]

Highlights: [•] We present an attribute-generalization reduct for decision tables with AVTs. [•] We analyze relationships between the attribute reduct and the generalization reduct. [•] We develop a heuristic algorithm AGR-SCE to find the generalization reduct. [•] The generalization reduct can objectively control the generalization process. [•] The generalization reduct can avoid over-generalization or under-generalization. [Copyright &y& Elsevier]

Abstract: Identity disclosure is one of the most serious privacy concerns in many data mining applications. A well-known privacy model for protecting identity disclosure is k-anonymity. The main goal of anonymizing classification data is to protect individual privacy while maintaining the utility of the data in building classification models. In this paper, we present an approach based on rough sets for measuring the data quality and guiding the process of anonymization operations. First, we make use of the attribute reduction theory of rough sets and introduce the conditional entropy to measure the classification data quality of anonymized datasets. Then, we extend conditional entropy under single-level granulation to hierarchical conditional entropy under multi-level granulation, and study its properties by dynamically coarsening and refining attribute values. Guided by these properties, we develop an efficient search metric and present a novel algorithm for achieving k-anonymity, Hierarchical Conditional Entropy-based Top-Down Refinement (HCE-TDR), which combines rough set theory and attribute value taxonomies. Theoretical analysis and experiments on real world datasets show that our algorithm is efficient and improves data utility. [Copyright &y& Elsevier]