Adjustable prediction-based reversible data hiding

Reversible data hiding has received considerable interest recently in the field of information hiding. However, most of difference expansion (DE-based) schemes suffer from the problem that image cannot be restored into its original one free from location map. Reversible data hiding scheme with location map cannot effectively raise hiding capacity; in addition, it also incurs the computational cost during embedding and extracting. This study presents a reversible data hiding scheme that is free of location map and thus the computational cost, associated with embedding and extracting, is lower than that of most DE-based schemes. Furthermore, our scheme solves the problem of the low embedding rate of Tseng and Hsieh?s scheme because our scheme takes advantage of the bulk of relatively high small prediction-errors to raise embedding capacity. Experimental results demonstrate that the proposed scheme achieves the larger payload and the better image quality than some existing schemes by an adjustable control factor. The performance of the proposed scheme is more stable for the different images.     

Morse set classification and hierarchical refinement using Conley index

Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion. Our framework allows a Morse set to be refined through a local update of the flow combinatorialization graph, as well as the connection regions between Morse sets. The computation is fast because the most expensive computation is concentrated on a small portion of the domain. Furthermore, the present work allows the generation of a topologically consistent hierarchy of MCGs, which cannot be obtained using a global method. The classification of the extracted Morse sets is a crucial step for the construction of the MCG, for which the Poincare′ index is inadequate. We make use of an upper bound for the Conley index, provided by the Betti numbers of an index pair for a translation along the flow, to classify the Morse sets. This upper bound is sufficiently accurate for Morse set classification and provides supportive information for the automatic refinement process. An improved visualization technique for MCG is developed to incorporate the Conley indices. Finally, we apply the proposed techniques to a number of synthetic and realworld simulation data to demonstrate their utility.     

Ambiguity-free edge-bundling for interactive graph visualization

Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational data sets (e.g., transportation networks, citation networks, or social networks). Graphs with dense edges, however, are difficult to visualize because fast layout and good clarity are not always easily achieved. When the number of edges is large, edge bundling can be used to improve the clarity, but in many cases, the edges could be still too cluttered to permit correct interpretation of the relations between nodes. In this paper, we present an ambiguity-free edge-bundling method especially for improving local detailed view of a complex graph. Our method makes more efficient use of display space and supports detail-on-demand viewing through an interactive interface. We demonstrate the effectiveness of our method with public coauthorship network data.     

Scalable influence maximization for independent cascade model in large-scale social networks

Influence maximization, defined by Kempe et al. (SIGKDD 2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models. The scalability of influence maximization is a key factor for enabling prevalent viral marketing in large-scale online social networks. Prior solutions, such as the greedy algorithm of Kempe et al. (SIGKDD 2003) and its improvements are slow and not scalable, while other heuristic algorithms do not provide consistently good performance on influence spreads. In this article, we design a new heuristic algorithm that is easily scalable to millions of nodes and edges in our experiments. Our algorithm has a simple tunable parameter for users to control the balance between the running time and the influence spread of the algorithm. Our results from extensive simulations on several real-world and synthetic networks demonstrate that our algorithm is currently the best scalable solution to the influence maximization problem: (a) our algorithm scales beyond million-sized graphs where the greedy algorithm becomes infeasible, and (b) in all size ranges, our algorithm performs consistently well in influence spread—it is always among the best algorithms, and in most cases it significantly outperforms all other scalable heuristics to as much as 100–260% increase in influence spread.     

Scaling effects on flow hydrodynamics of confined microdroplets induced by Rayleigh surface acoustic wave

This paper reports an experimental and numerical investigation on the scaling effects in the flow hydrodynamics for confined microdroplets induced by a surface acoustic wave (SAW). The characteristic parameters of the flow hydrodynamics were studied as a function of the separation height, H, between the LiNbO₃ substrate and a top glass plate, for various droplets volumes and radio-frequency powers. The ratio of the gap height to attenuation length of the SAW, H/l _SAW, is shown to be an important parameter affecting the streaming flow induced in this confined regime. The reported numerical and experimental results are in good agreement over the range examined in this study and demonstrate that, at a lower gap heights of H?≤?100?μm, a significant decrease in streaming velocity or Reynolds number is induced, with the velocity approaching zero when the gap height is decreased to ~50?μm. An increase in the gap height results in an increased streaming velocity; however, if the gap height exceeds 70?% of the SAW attenuation length, any further increase in the gap height induces a drop in the streaming velocity.     

Data preprocessing using hybrid general regression neural networks and particle swarm optimization for remote terminal units

Data corruption in SCADA systems refers to errors that occur during acquisition, processing, or transmission, introducing unintended changes to the original data. In SCADA-based power systems, the data gathered by remote terminal units (RTUs) is subject to data corruption due to noise interference or lack of calibration. In this study, an effective approach based on the fusion of the general regression neural network (GRNN) and the particle swarm optimization (PSO) technique is employed to deal with errors in RTU data. The proposed hybrid model, denoted as GRNN-PSO, is able to handle noisy data in a fast speed, which makes it feasible for practical applications. Experimental results show the GRNN-PSO model has better performance in removing the unintended changes to the original data compared with existing methods.     

Superconducting properties of Pb/Ag multilayers

The electrical resistivity, ac susceptibility, critical current density, and Josephson tunneling of Pb/Ag multilayers have been measured in wide temperature ranges in order to study the proximity effect. A resistivity drop was found to occur atT _c of Pb in versusT measurement and, at low temperature, the multilayers show proximity effect. The I-V characteristic of the multilayer shows voltage steps, indicating a resistive state has occurred in the sample. The superconducting properties of the multilayer were analyzed with the bilayer theory of the proximity effect.     

The calcium-phosphorus and the simultaneous calcium-oxygen and calcium-sulfur equilibria in liquid iron

The equilibrium Ca₃P_2(s) = 3[Ca] + 2[P] was studied at 1600 ° by equilibrating liquid iron, saturated with Ca₃P₂, and contained in a TiN crucible, with Ca vapor. The source of Ca was liquid Ca contained in an Mo crucible, and the vapor pressure of Ca was varied by varying the position of the Mo crucible in the temperature gradient of a vertical tube furnace. A least-squares analysis of the data gave and. The simultaneous equilibria CaO_(s) = [Ca] + [O] and CaS_(s) = [Ca] + [S] were studied at 1600 ° by equilibrating liquid iron, contained in a pressed and sintered CaO-CaS crucible with Ca vapor. The advantage of this technique is that two equilibrium constants,K _cas andK _cao, and two interaction coefficients, and can be determined from one set of experiments. It was determined that, at 1600 °,K _cas = 5.9 × 10⁻⁸ K _cao = 5.5 × 10⁻⁹,, and. Formerly Graduate Students     

用于VLSI的SiO_xN_y薄膜的界面陷阱

采用雪崩热电子注入技术研究了用于VLSI的快速热氮化的SiO_xN_y薄膜界面陷阱。给出这种薄介质膜禁带中央界面陷阱密度随氮化时间的变化关系,观察到这种薄膜存在着不同类型的密度悬殊很大的电子陷阱。指出雪崩热电子注入过程中在Si/SiO_xN_y界面上产生两类性质不同的快界面态陷阱,并给出这两种陷阱在禁带中能级位置及密度大小关系;同时还给出禁带中央界面陷阱密度随雪崩注入剂量呈现弱“N”形变化关系,并对实验结果进行了讨论。     

Investigation of shear stress distribution in notch problem under sliding mode case

The shear stress distribution for the notch problem of plane elasticity in the sliding mode case is investigated in this paper. Particular features of the shear stress distribution beneath the crown point of notch are analyzed by means of the Muskhelishvili method [1]. It is found that the maximum shear stress _{xy, max} is always reached at some point below the surface of the notch. The smaller the radius of the notch, the larger is the maximum shear stress _{xy, max}. A relation between _{xy, max} and stress intensity factor K _II of the corresponding crack problem is found to be Several specific examples are given to prove the validity of the obtained relation.% MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbqefm0B1jxALjhiov2D% aebbfv3ySLgzGueE0jxyaibaiGc9yrFr0xXdbba91rFfpec8Eeeu0x% Xdbba9frFj0-OqFfea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs% 0dXdbPYxe9vr0-vr0-vqpWqaaeaabiGaciaacaqabeaadaqaaqGaaO% qaaiaadUeadaWgaaWcbaGaaeysaiaabMeaaeqaaOGaeyypa0ZaaSaa% aeaacaaIZaWaaOaaaeaacaaIZaGaeqiWdahaleqaaaGcbaGaaGOmaa% aadaWfqaqaaiGacYgacaGGPbGaaiyBaaWcbaGaeqyWdiNaeyOKH4Qa% aGimaaqabaGcdaGcaaqaaiabeg8aYjabeo8aZbWcbeaakmaaBaaale% aacaWG4bGaamyEaiaacYcaciGGTbGaaiyyaiaacIhadaahaaadbeqa% amXvP5wqonvsaeHbuLwBLnhiov2DGi1BTfMBG0evGueE0jxyGi0BSr% gaiuaacqWFUaGlaaaaleqaaaaa!6261!\[K_{{\text{II}}} = \frac{{3\sqrt {3\pi } }}{2}\mathop {\lim }\limits_{\rho \to 0} \sqrt {\rho \sigma } _{xy,\max ^. } \]This research project is supported by the National Science Foundation of China.