The paper proposes an algorithm to expose spliced photographs. Firstly, a graph-based segmentation, which defines a predictor to measure boundary evidence between two neighbor regions, is used to make greedy decision. Then the algorithm gets prediction error image using non-negative linear least-square prediction. For each pair of segmented neighbor regions, the proposed algorithm gathers their statistic features and calculates features of gray level co-occurrence matrix. K-means clustering is applied to create a dictionary, and the vector quantization histogram is taken as the result vector with fixed length. For a tampered image, its noise satisfies Gaussian distribution with zero mean. The proposed method checks the similarity between noise distribution and a zero-mean Gaussian distribution, and follows with the local flatness and texture measurement. Finally, all features are fed to a support vector machine classifier. The algorithm has low computational cost. Experiments show its effectiveness in exposing forgery.

In this paper, we propose a low-complexity widely-linear minimum mean square error (WL-MMSE) signal detection based on the Chebyshev polynomials accelerated symmetric successive over relaxation (SSORcheb) algorithm for uplink (UL) over-loaded large-scale multiple-input multiple-output (MIMO) systems. The technique of utilizing Chebyshev acceleration not only speeds up the convergence rate significantly, and maximizes the data throughput, but also reduces the cost. By utilizing the random matrix theory, we present good estimates for the Chebyshev acceleration parameters of the proposed signal detection in real large-scale MIMO systems. Simulation results demonstrate that the new WL-SSORcheb-MMSE detection not only outperforms the recently proposed linear iterative detection, and the optimal polynomial expansion (PE) WL-MMSE detection, but also achieves a performance close to the exact WL-MMSE detection. Additionally, the proposed detection offers superior sum rate and bit error rate (BER) performance compared to the precision MMSE detection with substantially fewer arithmetic operations in a short coherence time. Therefore, the proposed detection can satisfy the high-density and high-mobility requirements of some of the emerging wireless networks, such as, the high-mobility Internet of Things (IoT) networks.

This paper proposes two efficient rate control algorithms for Motion JPEG2000. Both methods provide accurate visual quality control under buffer constraints. Frames of the same scene usually have the similar rate-distortion (R-D) characters. The proposed methods predict the R-D models of uncoded frames forwardly or bilaterally according to those of coded frames. Experimental results demonstrate that the proposed algorithms offer visual quality improvements over similar competing methods and save a large amount of memory simultaneously.

In this paper, a Many Integrated Core Architecture (MIC) accelerated parallel method of moment (MoM) algorithm is proposed to solve electromagnetic problems in practical applications, where MIC means a kind of coprocessor or accelerator in computer systems which is used to accelerate the computation performed by Central Processing Unit (CPU). Three critical points are introduced in this paper in detail. The first one is the design of the parallel framework, which ensures that the algorithm can run on distributed memory platform with multiple nodes. The hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) programming model is designed to achieve the purposes. The second one is the out-of-core algorithm, which greatly breaks the restriction of MIC memory. The third one is the pipeline algorithm which overlaps the data movement with MIC computation. The pipeline algorithm successfully hides the communication and thus greatly enhances the performance of hybrid MIC/CPU MoM. Numerical result indicates that the proposed algorithm has good parallel efficiency and scalability, and twice faster performance when compared with the corresponding CPU algorithm.

As GML is becoming the de facto standard for geographic data storage, transmission and exchange, more and more geographic data exists in GML format. In applications, GML documents are usually very large in size because they contain a large number of verbose markup tags and a large amount of spatial coordinate data. In order to speedup data transmission and reduce network cost, it is essential to develop effective and efficient GML compression tools. Although GML is a special case of XML, current XML compressors are not effective if directly applied to GML, because these compressors have been designed for general XML data. In this paper, we propose GPress, a compressor for effectively compressing GML documents. To the best of our knowledge, GPress is the first compressor specifically for GML documents compression. GPress exploits the unique characteristics of GML documents to achieve good performance. Extensive experiments over real-world GML documents show that GPress evidently outperforms XMill (one of the best existing XML compressors) in compression ratio, while its compression efficiency is comparable to the existing XML compressors.

The arrangement graph An,k is not only a generalization of star graph (n-k=1), but also more flexible. Designing efficient broadcasting algorithm on a regular interconnection network is a fundamental issue for the parallel processing techniques. Two contributions are proposed in this paper. Initially, we elucidate a first result to construct n-k edge-disjoint spanning trees in an An,k. Second, we present efficient (one/all)-to-all broadcasting algorithms by using constructed n-k spanning trees, where height of each spanning tree is 2k-1. The arrangement graph is assumed to use one-port and all-port communication models and packet-switching (or store-and-forward) technique. Using n-k spanning trees allows us to present efficient broadcasting algorithm in the arrangement graphs and outperforms previous results. This is justified by our performance analysis.

In this paper, we investigate a combination scheme of subcarrier intensity-modulation (SIM) with spatial modulation (SM) for optical wireless communication. Using computer simulation, the performances of the proposed SIM/SM scheme are investigated and compared with those of the conventional SIM scheme in the additive white gaussian noise (AWGN) as well as in outdoor environment with turbulence induced fading characteristics. Numerical results show that the proposed SIM/SM scheme can outperform the conventional SIM in an environment with different spectral efficiencies. When the spectral efficiency is varied from 2bits/s/Hz to 4bits/s/Hz, an Eb/N0 gain of 2dB to 5dB is achieved, when the bit error rate of 10-5 is maintained. It shows that the employment of SM may further improve the power efficiency of SIM, when the number of subcarriers increases according to the spectral efficiency. When the spectral efficiency is 4bits/s/Hz, the SIM/SM scheme for 0.5 of log-irradiance variance in the log-normal turbulence channel shows the same performance as SIM with variance of 0.3. This means that the SIM/SM can be an alternative choice in even worse environments.

An efficient resistive random access memory (ReRAM) structure is developed for accelerating convolutional neural network (CNN) powered by the in-memory computation. A novel ReRAM cell circuit is designed with two-directional (2-D) accessibility. The entire memory system is organized as a 2-D array, in which specific memory cells can be identically accessed by both of column- and row-locality. For the in-memory computations of CNNs, only relevant cells in an identical sub-array are accessed by 2-D read-out operations, which is hardly implemented by conventional ReRAM cells. In this manner, the redundant access (column or row) of the conventional ReRAM structures is prevented to eliminated the unnecessary data movement when CNNs are processed in-memory. From the simulation results, the energy and bandwidth efficiency of the proposed memory structure are 1.4x and 5x of a state-of-the-art ReRAM architecture, respectively.

Rateless erasure code is an error correction code that is able to encode a message of k uncoded symbols into an infinite number of coded symbols. One may reconstruct the original message from any k(1+ε) coded symbols, where ε denotes the decoding inefficiency. This paper proposes a hybrid code that combines the stepping code and random code and name it as Stepping-Random (SR) code. The Part I (first k) coded symbols of SR code are generated with stepping code. The rest of the coded symbols are generated with random code and denoted as Part II coded symbols. The numerical results show that the new hybrid code is able to achieve a complete decoding with no extra coded symbol (ε=0) if all the Part I coded symbols are received without loss. However, if only a portion of Part I coded symbols are received, a high probability of complete decoding is still achievable with k+10 coded symbols from the combination of Part I and II. SR code has a decoding complexity of O(k) in the former and O((βk)3) in the latter, where β ∈ R for 0 ≤ β ≤ 1, is the fraction of uncoded symbols that fails to be reconstructed from Part I coded symbols.

The endurance time of smartphone still suffer from the limited battery capacity, and smartphone apps will increase the burden of the battery if they download large data over slow network. So how to manage the download tasks is an important work. To this end we propose a smartphone download strategy with low energy consumption which called CLSA (Concentrated Download and Low Power and Stable Link Selection Algorithm). The CLSA is intended to reduce the overhead of large data downloads by appropriate delay for the smartphone, and it based on three major factors: the current network situation, the length of download requests' queue and the local information of smartphone. We evaluate the CLSA using a music player implementation on ZTE V880 smartphone running the Android operation system, and compare it with the other two general download strategies, Minimum Delay and WiFi Only. Experiments show that our download algorithm can achieve a better trade-off between energy and delay than the other two.

The paper employed an Alexnet, which is a deep learning framework, to automatically diagnose the damages of wind power generator blade surfaces. The original images of wind power generator blade surfaces were captured by machine visions of a 4-rotor UAV (unmanned aerial vehicle). Firstly, an 8-layer Alexnet, totally including 21 functional sub-layers, is constructed and parameterized. Secondly, the Alexnet was trained with 10000 images and then was tested by 6-turn 350 images. Finally, the statistic of network tests shows that the average accuracy of damage diagnosis by Alexnet is about 99.001%. We also trained and tested a traditional BP (Back Propagation) neural network, which have 20-neuron input layer, 5-neuron hidden layer, and 1-neuron output layer, with the same image data. The average accuracy of damage diagnosis of BP neural network is 19.424% lower than that of Alexnet. The point shows that it is feasible to apply the UAV image acquisition and the deep learning classifier to diagnose the damages of wind turbine blades in service automatically.

In Ad Hoc networks, communication between a pair of hosts uses channel resources, such that the channel cannot be used by the neighboring hosts. A channel used by one pair of hosts can be reused by another pair of hosts only if their communication ranges do not overlap. Channels are limited resources, accounting for why exploiting channel reuse opportunities and enhancing the channel utilization is essential to increasing system capacity. However, exploiting channel reuse opportunities may cause a co-channel interference problem. Two pairs of communicating hosts that use the same channel may gradually move toward to each other. A channel reassignment operation must be applied to these hosts to maintain their communication. This investigation presents a channel assignment protocol that enables the channel resources to be highly utilized. Following this protocol, a channel reassignment protocol is also proposed to protect the communicating hosts from co-channel interference caused by mobility. The proposed reassignment protocol efficiently reassigns a new available channel to a pair of hosts that suffers from co-channel interference. The performance of the proposed protocols is also examined. Experimental results reveal that the proposed protocols enable more hosts to communicate simultaneously and prevent their communication from failing.

A mobile ad hoc network (MANET) is characterized by multi-hop wireless links in the absence of any cellular infrastructure as well as by frequent host mobility. This paper proposes a SMPQ: Spiral-Multi-Path QoS routing protocol in a MANET, while the MAC sub-layer adopts the CDMA-over-TDMA channel model. This work investigates the bandwidth reservation problem of on-demand QoS routing in a wireless mobile ad-hoc network. The proposed approach increases the ability of a route to identify a robust path, namely a spiral-multi-path, from source host to destination host, in a MANET to satisfy certain bandwidth requirements. Two important contributions of the proposed spiral-multi-path are: (1) the spiral-multi-path strengthens route-robustness and route-stability properties and (2) the spiral-multi-path increases the success rate of finding the QoS route. Performance analysis results demonstrate that our SMPQ protocol outperforms other protocols.

The multimedia applications have recently generated much interest in wireless network infrastructure with supporting the quality-of-service (QoS) communications. In this paper, we propose a lantern-tree-based QoS on-demand multicast protocol for wireless ad hoc networks. Our proposed scheme offers a bandwidth routing protocol for QoS support in a multihop mobile network, where the MAC sub-layer adopts the CDMA-over-TDMA channel model. The QoS on-demand multicast protocol determines the end-to-end bandwidth calculation and bandwidth allocation from a source to a group of destinations. In this paper, we identify a lantern-tree for developing the QoS multicast protocol to satisfy certain bandwidth requirement, while the lantern-tree is served as the multicast-tree. Our lantern-tree-based scheme offers a higher success rate to construct the QoS multicast tree due to using the lantern-tree. The lantern-tree is a tree whose sub-path is constituted by the lantern-path, where the lantern-path is a kind of multi-path structure. This obviously improves the success rate by means of multi-path routing. In particular, our proposed scheme can be easily applied to most existing on-demand multicast protocols. Performance analysis results demonstrate the achievements of our proposed protocol.

A mobile ad hoc network (MANET) is a characterized by multi-hop wireless links, absence of any cellular infrastructure, and frequent host mobility. Existing MANET routing protocols are divided into location-aware and non-location-aware routing protocols. In a location-aware routing protocol, location information can be exploited to facilitate routing. Our protocol, namely multi-eye spiral-hopping (MESH) routing protocol, is a location-aware routing protocol. Most promising routing protocols are constructed by the route-discovery, route-reply, and route-maintenance phases. Our MESH protocol utilizes the location-information to confine the blind-flooding region in the route-discovery phase, minimize route-reply packets in the route-reply phase, and promote the routing robustness in the route-maintenance phase. Two major contributions of this paper are introduced: (1) a multi-eye scheme is presented to confine route-discovery region for reducing redundant packets, and (2) a special multi-path scheme, called as spiral-hopping scheme, is introduced to provide on-line route-recovery capability. Extensive simulations are conducted to evaluate the protocol.

This paper studies a harvested power-oriented simultaneous wireless information and power transfer (SWIPT) scheme over multiple-input multiple-output (MIMO) interference channels in which energy harvesting (EH) circuits exhibit nonlinearity. To maximize the power harvested by all receivers, we propose an algorithm to jointly optimize the transmit beamforming vectors, power splitting (PS) ratios and the receive decoding vectors. As all variables are coupled to some extent, the problem is non-convex and hard to solve. To deal with this non-convex problem, an iterative optimization method is proposed. When two variables are fixed, the third variable is optimized. Specifically, when the transmit beamforming vectors are optimized, the transferred objective function is the sum of several fractional functions. Non-linear sum-of-ratios programming is used to solve the transferred objective function. The convergence and advantage of our proposed scheme compared with traditional EH circuits are validated by simulation results.