Many forensic techniques have recently been developed to determine whether an image has undergone a specific manipulation operation. When multiple consecutive operations are applied to images, ...forensic analysts not only need to identify the existence of each manipulation operation, but also to distinguish the order of the involved operations. However, image operator chain detection is still a challenging problem. In this paper, an order forensics framework for detecting image operator chain based on convolutional neural network (CNN) is presented. Two-stream CNN architecture is designed to capture both tampering artifact evidence and local noise residual evidence. Specifically, the new CNN-based method is proposed for forensically detecting a chain made of two image operators, which could automatically learn manipulation detection features directly from image data. Further, we empirically investigate the robustness of our proposed method in two practical scenarios: forensic investigators have no access to the operating parameters, and manipulations are applied to a JPEG compressed image. Experimental results show that the proposed framework not only obtains significant detection performance but also can distinguish the order in some cases that previous works were unable to identify.
Advances in cognitive radio networks: A survey Beibei Wang; Liu, K J R
IEEE journal of selected topics in signal processing,
2011-Feb., 2011-02-00, 20110201, Letnik:
5, Številka:
1
Journal Article
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With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a ...bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.
Novel mechanisms for electromagnetic wave emission in the terahertz frequency regime emerging at the nanometer scale have recently attracted intense attention for the purpose of searching ...next-generation broadband THz emitters. Here, we report broadband THz emission, utilizing the interface inverse Rashba-Edelstein effect. By engineering the symmetry of the Ag/Bi Rashba interface, we demonstrate a controllable THz radiation (∼0.1-5 THz) waveform emitted from metallic Fe/Ag/Bi heterostructures following photoexcitation. We further reveal that this type of THz radiation can be selectively superimposed on the emission discovered recently due to the inverse spin Hall effect, yielding a unique film thickness dependent emission pattern. Our results thus offer new opportunities for versatile broadband THz radiation using the interface quantum effects.
Crowdsourcing has proliferated across disciplines and professional fields. Implementers in the public sector face practical challenges, however, in the execution of crowdsourcing. This review ...synthesizes prior crowdsourcing research and practices from a variety of disciplines and focuses to identify lessons for meeting the practical challenges of crowdsourcing in the public sector. It identifies three distinct categories of crowdsourcing: organizations, products and services, and holistic systems. Lessons about the fundamental logic of process design—alignment, motivation, and evaluation—identified across the three categories are discussed. Conclusions drawn from past studies and the resulting evidence can help public managers better design and implement crowdsourcing in the public sector.
In an indoor environment, there commonly exist a large number of multipaths due to rich scatterers. These multipaths make the indoor positioning problem very challenging. The main reason is that most ...of the transmitted signals are significantly distorted by the multipaths before arriving at the receiver, which causes inaccuracies in the estimation of the positioning features such as the time of arrival (TOA) and the angle of arrival (AOA). On the other hand, the multipath effect can be very constructive when employed in the time-reversal (TR) radio transmission. By utilizing the uniqueness of the multipath profile at each location, TR can create a resonating effect of focusing the energy of the transmitted signal only onto the intended location, which is known as the spatial focusing effect. In this paper, we propose exploiting such a high-resolution focusing effect in the indoor positioning problem. Specifically, we propose a TR indoor positioning system (TRIPS) by utilizing the location-specific characteristic of multipaths. By doing so, we decompose the ill-posed single-access-point (AP) indoor positioning problem into two well-defined subproblems. The first subproblem is to create a database by mapping the physical geographical location with the logical location in the channel impulse response (CIR) space, whereas the second subproblem is to determine the real physical location by matching the estimated CIR with those in the database. To evaluate the performance of our proposed TRIPS, we build a prototype to conduct real experiments. The experimental results show that, with a single AP working in the 5.4-GHz band under the non-line-of-sight (NLOS) condition, our proposed TRIPS can achieve perfect 10-cm localization accuracy with zero-error rate within a 0.9 m by 1 m area of interest.
We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental ...question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.
Computer experiments with qualitative and quantitative factors occur frequently in various applications in science and engineering. Analysis of such experiments is not yet completely resolved. In ...this work, we propose an additive Gaussian process model for computer experiments with qualitative and quantitative factors. The proposed method considers an additive correlation structure for qualitative factors, and assumes that the correlation function for each qualitative factor and the correlation function of quantitative factors are multiplicative. It inherits the flexibility of unrestrictive correlation structure for qualitative factors by using the hypersphere decomposition, embracing more flexibility in modeling the complex systems of computer experiments. The merits of the proposed method are illustrated by several numerical examples and a real data application. Supplementary materials for this article are available online.
Many spectrum sensing methods and dynamic access algorithms have been proposed to improve the secondary users' opportunities of utilizing the primary users' spectrum resources. However, few of them ...have considered to integrate the design of spectrum sensing and access algorithms together by taking into account the mutual influence between them. In this paper, we propose to jointly analyze the spectrum sensing and access problem by studying two scenarios: synchronous scenario where the primary network is slotted and non-slotted asynchronous scenario. Due to selfish nature, secondary users tend to act selfishly to access the channel without contribution to the spectrum sensing. Moreover, they may take out-of-equilibrium strategies because of the uncertainty of others' strategies. To model the complicated interactions among secondary users, we formulate the joint spectrum sensing and access problem as an evolutionary game and derive the evolutionarily stable strategy (ESS) that no one will deviate from. Furthermore, we design a distributed learning algorithm for the secondary users to converge to the ESS. With the proposed algorithm, each secondary user senses and accesses the primary channel with the probabilities learned purely from its own past utility history, and finally achieves the desired ESS. Simulation results shows that our system can quickly converge to the ESS and such an ESS is robust to the sudden unfavorable deviations of the selfish secondary users.
Cognitive radio technology, a revolutionary communication paradigm that can utilize the existing wireless spectrum resources more efficiently, has been receiving a growing attention in recent years. ...As network users need to adapt their operating parameters to the dynamic environment, who may pursue different goals, traditional spectrum sharing approaches based on a fully cooperative, static, and centralized network environment are no longer applicable. Instead, game theory has been recognized as an important tool in studying, modeling, and analyzing the cognitive interaction process. In this tutorial survey, we introduce the most fundamental concepts of game theory, and explain in detail how these concepts can be leveraged in designing spectrum sharing protocols, with an emphasis on state-of-the-art research contributions in cognitive radio networking. Research challenges and future directions in game theoretic modeling approaches are also outlined. This tutorial survey provides a comprehensive treatment of game theory with important applications in cognitive radio networks, and will aid the design of efficient, self-enforcing, and distributed spectrum sharing schemes in future wireless networks.
In this article, we examine a novel generic network cost minimization problem, in which every node has a local decision vector to optimize. Each node incurs a cost associated with its decision ...vector, while each link incurs a cost related to the decision vectors of its two end nodes. All nodes collaborate to minimize the overall network cost. The formulated network cost minimization problem has broad applications in distributed signal processing and control, in which the notion of link costs often arises. To solve this problem in a decentralized manner, we develop a distributed variant of Newton's method, which possesses faster convergence than alternative first-order optimization methods such as gradient descent and alternating direction method of multipliers. The proposed method is based on an appropriate splitting of the Hessian matrix and an approximation of its inverse, which is used to determine the Newton step. Global linear convergence of the proposed algorithm is established under several standard technical assumptions on the local cost functions. Furthermore, analogous to classical centralized Newton's method, a quadratic convergence phase of the algorithm over a certain time interval is identified. Finally, numerical simulations are conducted to validate the effectiveness of the proposed algorithm and its superiority over other first-order methods, especially when the cost functions are ill-conditioned. Complexity issues of the proposed distributed Newton's method and alternative first-order methods are also discussed.
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