Image steganography using deep learning based edge detection

This paper introduces a deep learning-based Steganography method for hiding secret information within the cover image. For this, we use a convolutional neural network (CNN) with Deep Supervision based edge detector, which can retain more edge pixels over conventional edge detection algorithms. Initially, the cover image is pre-processed by masking the last 5-bits of each pixel. The said edge detector model is then applied to obtain a gray-scale edge map. To get the prominent edge information, the gray-scale edge map is converted into a binary version using both global and adaptive binarization schemes. The purpose of using different binarization techniques is to prove the less sensitive nature of the edge detection method to the thresholding approaches. Our rule for embedding secret bits within the cover image is as follows: more bits into the edge pixels while fewer bits into the non-edge pixels. Experimental outcomes on various standard images confirm that compared to state-of-the-art methods, the proposed method achieves a higher payload.

     

A Information Retrieval Based on Question and Answering and NER for Unstructured Information Without Using SQL

Wireless Personal Communications - In today’s world, the availability of information in the form of unstructured data is in abundance. The unstructured information received is more often than...     

Analysis of deformation coupled surface remodeling in porous biomaterials

Surface remodeling of biological tissues through tissue growth or dissolution is deemed critical to their proper functioning, and is influenced by the deformation of the tissues during physiological activities. The present work attempts to develop a constitutive framework for deformation modulated surface remodeling of biological tissues. The framework is developed assuming finite deformation of the tissue, and the effect of deformation on the driving force for surface remodeling is determined from thermodynamic principles. The microscopic trends are upscaled to yield the remodeling-induced change in a macroscopic porous tissue. By way of application, the effect of deformation on the remodeling kinetics is determined for an incompressible elastic tissue. Depending on the ratio of the specific elastic stiffness and the specific Gibbs energy variation induced by the cell, the effect of deformation on the remodeling kinetics can be significant. It is found that both tensile and compressive deformation aid tissue dissolution (and dissuade growth). However, the magnitude of the effect is found to be different under tensile and compressive loadings, and critically depends on the reference frame used for the strain measurements. For Lagrangian strain measures (e.g., stretch, engineering strain), the increase in the dissolution kinetics per unit strain is higher under compressive loadings. On the other hand, for Eulerian strain measures (e.g., logarithmic or true strain), the effect of tensile loading on the dissolution kinetics is higher. This reinforces the need for proper reference frame definition for experimental strain measurements.

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Analysis of EEG signals and its application to neuromarketing

Multimedia Tools and Applications - Marketing and promotions of various consumer products through advertisement campaign is a well known practice to increase the sales and awareness amongst the...     

Comparative and sensitivity study of flutter derivatives of selected bridge deck sections,Part 2: Implications on the aerodynamic stability of long-span bridges

This study is the continuation of a comprehensive investigation on section-model aeroelastic coefficients for bridge decks (flutter derivatives) extracted from wind tunnel section-model tests. The original motivation emerged from the United States—Japan Benchmark Study on Bridge Flutter Derivatives, which promoted a series of systematic comparisons of experimental data extracted by two laboratories (Iowa State University, USA and Public Works Research Institute, Japan) as well as previous results available in the literature. Comparisons, which included both streamlined and bluff deck girder models, were summarized in a companion paper [Sarkar P, Caracoglia L, Haan FL, Sato H, Murakoshi J. Comparative and sensitivity study of flutter derivatives of selected bridge deck sections. Part 1: Analysis of inter-laboratory experimental data. Eng Struct 2009;31(1):159–69]. Differences in the flutter derivatives were mainly attributed to: distinct experimental methods in the wind tunnel (free or forced vibration methods), intrinsic variability between different laboratory environments and effects of amplitude dependency in the tests (for bluff sections).In this paper, a sensitivity study was performed to examine the implications of the perceived dissimilarities among flutter-derivative data sets discussed in [Sarkar P, Caracoglia L, Haan FL, Sato H, Murakoshi J. Comparative and sensitivity study of flutter derivatives of selected bridge deck sections. Part 1: Analysis of inter-laboratory experimental data. Eng Struct 2009;31(1):159–69], on the aeroelastic instability of long-span bridges.Numerical analyses were conducted to evaluate flutter instability boundaries of a set of long-span bridge configurations. Both single-mode and coupled-mode instability were considered, depending on the cross section type and characteristics. It is concluded that uncertainty in flutter derivatives occurring as a result of extraction method or intrinsic variability between different laboratories from negligibly small values to as much as fifty percent, as observed in [Sarkar P, Caracoglia L, Haan FL, Sato H, Murakoshi J. Comparative and sensitivity study of flutter derivatives of selected bridge deck sections. Part 1: Analysis of inter-laboratory experimental data. Eng Struct 2009;31(1):159–69], do not affect the variability in the predicted critical velocity in a proportional way. However, differences in the resulting critical velocities have been observed and estimated from as small as five percent to more than thirty percent, heavily depending on the type of bridge, the simulated conditions and type of instability, either dominated by a single mode or influenced by modal coupling.     

A duality involving Borel spaces

The purpose of the paper is to show that there is a dual equivalence between sober Borel spaces and spatial Boolean σ-frames. We show that a discrete space is sober, if and only if, its cardinality is non-measurable and also show that many well known Borel spaces are sober.     

Algorithms for Integrated Routing and Scheduling for Aggregating Data from Distributed Resources on a Lambda Grid

In many e-science applications, there exists an important need to aggregate information from data repositories distributed around the world. In an effort to better link these resources in a unified manner, many lambda-grid networks, which provide end-to-end dedicated optical-circuit-switched connections, have been investigated. In this context, we consider the problem of aggregating files from distributed databases at a (grid) computing node over a lambda grid. The challenge is (1) to identify routes (that is, circuits) in the lambda-grid network, along which files should be transmitted, and (2) to schedule the transfers of these files over their respective circuits. To address this challenge, we propose a hybrid approach that combines offline and online scheduling. We define the Time-Path Scheduling Problem (TPSP) for offline scheduling. We prove that TPSP is NP-complete, develop a Mixed Integer Linear Program (MILP) formulation for TPSP, and then propose a greedy approach to solve TPSP because the MILP does not scale well. We compare the performance of the greedy approach on a few representative lambda-grid network topologies. One key input to the offline schedule is the file transfer time. Due to dynamics at the receiving end host, which is hard to model precisely, the actual file transfer time may vary. We first propose a model for estimating the file transfer time. Then, we propose online reconfiguration algorithms so that as files are transferred, the offline schedule may be modified online, depending on the amount of time that it actually took to transfer the file. This helps in reducing the total time to transfer all the files, which is an important metric. To demonstrate the effectiveness of our approach, we present results on an emulated lambda-grid network testbed.     

A New Groundwater Management Model by Coupling Analytic Element Method and Reverse Particle Tracking with Cat Swarm Optimization

The performance of groundwater management models mostly depends upon the methodology employed to simulate flow and transport processes and the efficiency of optimization algorithms. The present study examines the effectiveness of cat swarm optimization (CSO) for groundwater management problems, by coupling it with the analytic element method (AEM) and reverse particle tracking (RPT). In this study, we propose two coupled simulation-optimization models, viz. AEM-CSO and AEM-RPT-CSO by combining AEM with RPT and CSO. Both the models utilize the added advantages of AEM, such as precise estimation of hydraulic head at pumping location and generation of continuous velocity throughout the domain. The AEM-CSO model is applied to a hypothetical unconfined aquifer considering two different objectives, i.e., maximization of the total pumping of groundwater from the aquifer and minimization of the total pumping costs. The model performance reflects the superiority of CSO in comparison with other optimization algorithms. Further, the AEM-RPT-CSO model is successfully applied to a hypothetical confined aquifer to minimize the total number of contaminant sources, within the time related capture zone of the wells, while maintaining the required water demand. In this model, RPT gets continuous velocity information directly from the AEM model. The performance evaluation of the proposed methodology, illustrates its ability to solve groundwater management problems.