ALBERT

Description: Mobile broadband services have expanded considerably in recent years, driving operators to improve and densify their radio access network (RAN). It has become clear that small cells as well as macrocells must be included in a heterogeneous network, due to the scale of densification required. In order to maximize the end user experience, some level of radio coordination between these small and macrocells is needed ?? this coordination will be signaled across a mobile backhaul network. Mobile backhaul typically refers to the network between the base station site and the network controller site, but can also include interconnection between base station sites. Mobile backhaul includes a spectrum of networks and network technologies, including the RAN and core networks. There is considerable market interest on the development of small cell backhaul solutions that are an evolution of existing backhaul networks. Packet synchronisation mechanisms that are being developed are key to support the mobile backhaul application. Various standards bodies such as the Next Generation Mobile Networks Alliance (NGMN), Small Cell Forum (SCF), Metro Ethernet Forum (MEF), and Broadband Forum (BBF) are also studying what the implications would be on their defined mobile backhaul network architectures.

Description: Heterodyne generation of parallel random bit streams from chaotic emission of an optically injected semiconductor laser is investigated. The continuous-wave optical injection invokes chaotic dynamics in the laser. The broadband chaotic emission is detected through optical heterodyning and electrical heterodyning into different channels. The channels digitize the signals into parallel independent random bit streams. Because of efficient utilization of different portions of the chaos bandwidth, heterodyne detections enable parallel generation of random bit streams, offer high total output bit rates, and require no high-bandwidth analogue-to-digital converters. In the experiment, two optical heterodyne channels and four electrical heterodyne channels are implemented. Each channel is required to digitize only 2.5 GHz of a much broader chaos bandwidth. The sampling rate is 10 GHz with five least significant bits selected from every 8-bit sample. The total output bit rate reaches 100 Gb/s and 200 Gb/s for optical and electrical heterodyning, respectively. The standard test suite of the National Institute of Standards and Technology verifies the randomness of both individual and interleaved output bit streams.

Description: In this article, we introduce the EstiNet OpenFlow network simulator and emulator, and present its support for testing the functions and evaluating the performances of software-defined networks?? OpenFlow controller??s application programs. EstiNet uses an unique kernel reentering simulation methodology to enable unmodified real applications to run on nodes in its simulated network. As a result, without any modification, real NOX/POX or Floodlight OpenFlow controllers can readily run on a host in an EstiNet simulated network to control thousands of simulated OpenFlow switches. EstiNet has the characteristics of a simulator and an emulator at the same time. It combines the advantages of the simulation and emulation approaches without their respective shortcomings. EstiNet uses real OpenFlow controller programs, real network application programs, and the real TCP/IP protocol stack in the Linux kernel to generate correct, accurate, and repeatable SDN application performance results. In this article, we compare EstiNet with ns-3 and Mininet regarding their capabilities, performance, and scalability.

Description: This article discusses novel wireless and optical technologies to address the radical new challenges of small cell mobile backhaul (MBH). Specifically, we examine 60 GHz and 70??80 GHz millimeter-wave technologies for high-capacity last mile and pre-aggregation backhaul, and orthogonal frequency-division multiple access passive optical networks as the optical technology complement for enabling flexible cost-efficient hybrid backhaul coverage. Flexible high-capacity hybrid millimeter wave/optical MBH network operation is next verified via network simulations in the context of a demanding, urban small-cell backhaul application. Finally, a novel software defined networking tool called the backhaul resource manager is introduced for automated dynamic resource provisioning and capacity-aware path computation that improves fairness, network utilization and end-to-end user quality of experience. The introduction of the novel wireless, optical, and software-defined technologies thus has the potential to truly revolutionize the future MBH network.

Description: In this article we discuss different technology alternatives for small cell backhaul, and we present high-frequency microwave technology as a very interesting alternative for wireless backhauling of small cells. In fact, we demonstrate that high-frequency microwave technology can be used for NLOS wireless backhauling of small cells, which opens up new applications for microwave technology. We discuss urban NLOS channel propagation at high frequencies, and we show both measurement and simulation results to validate the use of high-frequency microwave technology for NLOS small cell backhaul.

Description: A novel design and assembly technology is developed for a three-dimensional (3-D) flexible thermal flow sensor based on convective heat transfer to reduce detection error caused by position variation of a sensor inside the flow of narrow and curved geometries, such as coronary artery. The 3-D sensor has three independent sensing elements equally distributed around the catheter tube. This arrangement introduces three independent information channels, and cross-comparisons are used to provide accurate flow measurement. The resistance of the sensing elements is measured at ${sim}{1}-1.2~{rm k}Omega$ with the temperature coefficient of resistance at $0.086%/^{circ}{rm C}$ . Using a constant-current circuit, the three sensing elements are heated to ${sim}10^{circ}{rm C}$ above ambient temperature. Flow testing is implemented in a pipe channel at two positions: on the wall and along the center line. Experimental results from these two positions are discussed and computational fluid dynamic simulation based on Newtonian fluid properties is implemented, showing comparable results within an acceptable range of experimental to simulation errors. Therefore, we demonstrate the capability of 3-D thermal flow sensor for detecting the position of the catheter in the flow channel, thereby providing an accurate flow measurement.

Description: Currently, online social networks such as Facebook, Twitter, Google+, LinkedIn, and Foursquare have become extremely popular all over the world and play a significant role in people??s daily lives. People access OSNs using both traditional desktop PCs and new emerging mobile devices. With more than one billion users worldwide, OSNs are a new venue of innovation with many challenging research problems. In this survey, we aim to give a comprehensive review of state-of-the-art research related to user behavior in OSNs from several perspectives. First, we discuss social connectivity and interaction among users. Also, we investigate traffic activity from a network perspective. Moreover, as mobile devices become a commodity, we pay attention to the characteristics of social behaviors in mobile environments. Last but not least, we review malicious behaviors of OSN users, and discuss several solutions to detect misbehaving users. Our survey serves the important roles of both providing a systematic exploration of existing research highlights and triggering various potentially significant research in these topics.

Description: We discuss the fabrication and performance of an all-polymer, flexural plate wave gravimetric sensor using flexible, piezoelectric Polyvinylidene fluoride as the substrate and an inkjet-printed interdigital transducer (IDT) employing conductive poly(3, 4-ethylenedioxythiophene) poly(styrenesulfonate) to excite Lamb waves within the film. Lamb waves are measured both electronically, using a second IDT, and mapped directly using a scanning laser Doppler vibrometer. Pulsed wave excitation is utilized to isolate the weak acoustic signal from the electromagnetic crosstalk, enabling the measurement of relative changes in the resonant frequency, $Delta f/f_{0}$ , in response to added mass, $Delta m$ , to the sensing area. A gravimetric mass sensitivity equivalent to $Delta f/(f_{0}Delta m)=-153~{rm cm}^{2}/{rm g}$ is measured by mass loading the sensor with printed polymer layers. It is found that the low stiffness of the substrate contributes significantly to the response of the sensor, yielding a measured overall sensitivity of $Delta f/(f_{0}Delta m)=-83~{rm cm}^{2}/{rm g}$ .

Description: In this paper, we propose a novel technological approach for the implementation of large-area flexible artificial skin based on arrays of piezoelectric polymer transducers. Polyvinylidene fluoride (PVDF) transducers are chosen for the high electromechanical transduction frequency bandwidth (up to 1 kHz). A low-cost and scalable technique for extracting PVDF signals is used to directly provide the piezoelectric film with patterned electrodes. If the skin is meant to cover large areas of a robot body, specific requirements have to be fulfilled from the point of view of the overall system and of the technology. Experimental tests on the prototype skin modules demonstrate the feasibility of the proposed approach and reveal the potentiality to build large area flexible skin.

Description: This paper presents ultra-thin silicon chips (flex–chips) on flexible foils, realized through post-processing steps such as wafer thinning, dicing, and transferring the thinned chips to flexible polyimide foils. The cost effective chemical etching is adopted for wafer thinning and the transfer printing approach, to transfer quasi 1-D structures such as micro/nanoscale wires and ribbons, that is adapted for transferring large ultra-thin flex–chips (widths 4.5–15 mm, lengths 8–36 mm, and thickness ${approx}{rm 15}~mu{rm m}$ ). The post-processing capability is demonstrated with passive structures such as metal interconnects realized on the flex–chips before carrying out the chip thinning step. The resistance values of metal interconnects do not show any appreciable change because of bending of chips for the tested range viz., radius of curvature 9 mm and above. Further, the bending mechanics of silicon membranes on foil is investigated to evaluate the bending limits before a mechanical fracture/failure occurs. The distinct advantages of this paper are: attaining bendability through post-processing of chips, cost effective fabrication process, and easy transfer of chips to the flexible substrates without using conventional and sophisticated equipment such as pick and place set up.

Description: A sensor was made of a polymer composite composed of electrically-conductive carbon nanotubes embedded in elastic polyurethane. The composite was prepared using a polyurethane filter membrane, enmeshing it, and melding together with carbon nanotubes. Testing has shown that the composite can be elongated as much as 400% during which the electrical resistance is increased 270 times. The composite is also sensitive to compression and to organic solvent vapors. These properties indicate the composite could have applications as a highly-deformable strain and chemical vapors sensing element and also as flexible electromagnetic shielding or protection against lightning. As an example of the use of the composite as a strain sensor, the pressure variation between a shoe and floor during walking and knee flexion during cycling has been monitored.

Description: This paper presents a novel concept for stretchable conductors. Metal coated polymer spheres were densely packed in biocompatible silicone tubes. The resistivity of the conductors were in the approximate range of $1times 10^{-4}~Omega{rm m}$ at 0% strain and 50% strain could be applied before degrading their electrical performance. Initial results showed good reproducibility and no drift in resistance values up to 1000 cycles with 0%–25% strain. This make the conductors well suited for digital low speed data transmission. The initial application is intended for integration of electronics in clothing; the conductors have been tested with success transmitting data from a commercial digital combined humidity and temperature sensor.

Description: Recently, there are innovative mechanoluminescent (ML) particles made available, each of which repeatedly emits light in response to small applied stresses even in elastic region. When dispersedly coated onto a structure, each particle acts as a sensitive mechanical sensor, while the two-dimensional emission pattern of the whole assembly reflects the dynamical stress distribution inside the structure and the mechanical information around the crack and defect. To use the remarkable advantage of the ML sensor in flexibility, electricity/lead-free, low-cost, and so forth, and to answer social needs for historical-log of stress/damage accumulation on social infra-structure, we investigate historical-log recording system for crack opening and fatigue crack growth, and finally succeed to record it with responding position and intensity reflecting the trace of propagating crack tip and stress intensity factor around the tip. Furthermore, crack mouse opening displacement accompanied by general traffic of bridge in use is successfully detected.

Description: Spectrum sharing potentially holds the promise of solving the emerging spectrum crisis. However, technology innovators face the conundrum of developing spectrum sharing technologies without the ability to experiment and test with real incumbent systems. Interference with operational incumbents can prevent critical services, and the cost of deploying and operating an incumbent system can be prohibitive. Thus, the lack of incumbent systems and frequency authorization for technology incubation and demonstration has stymied spectrum sharing research. To this end, industry, academia, and regulators all require a test facility for validating hypotheses and demonstrating functionality without affecting operational incumbent systems. This article proposes a four-phase program supported by our spectrum accountability architecture. We propose that our comprehensive experimentation and testing approach for technology incubation and demonstration will accelerate the development of spectrum sharing technologies.

Description: This special issue focuses on the sensors and sensing systems having features like flexibility, bendability, conformability, stretchability, and presence over large areas and 3D surfaces. Like conventional sensors, flexible sensors are also used to measure parameters and agents like pH, temperature, humidity, force, gasses, velocity, flow etc. In addition, they possess the ability to bend. This requires special front-end processing techniques compatible with the flexible materials that these sensors are made of. In response to the call for papers for this special issue, 114 manuscripts were received. Of those, 39 were found not to fit to the scope of the special issue and were separated to be handled by the permanent editors of the Journal. The peer review process resulted in 29 innovative manuscripts to be published here submitted from over 45 institutions, with a few trailing manuscripts to be published at a later issue due to time constraints. Of the work presented here, nine papers describe sensors for health and medical applications. Five papers detail sensors for the general fields of environmental and structural health monitoring. Four are on robotic applications. Although majority of the manuscripts focus on a single sensing function such as fluidic flow, force, pH, temperature or presence of a specific gas, four papers present multifunctional flexible sensors.

Description: Thin, highly compliant sensing skins could provide valuable information for a host of grasping and locomotion tasks with minimal impact on the host system. We describe the design, fabrication, and characterization of a novel soft multi-axis force sensor made of highly deformable materials. The sensor is capable of measuring normal and in-plane shear forces. This soft sensor is composed of an elastomer (modulus: 69 kPa) with embedded microchannels filled with a conductive liquid. Depending on the magnitude and the direction of an applied force, all or part of the microchannels will be compressed, changing their electrical resistance. The two designs presented in this paper differ in their flexibility and channel configurations. The channel dimensions are approximately 200 $,times,$ 200 $mu{rm m}$ and 300 $,times,$ 700 $mu{rm m}$ for the two prototypes, respectively. The overall size of each sensor is 50 $,times,$ 60 $,times,$ 7 mm. The first prototype demonstrated force sensitivities along the two principal in-plane axes of 37.0 and ${-}{rm 28.6}~{rm mV/N}$ . The second prototype demonstrated the capability to detecting and differentiating normal and in-plane forces. In addition, this paper presents the results of a parameter study for different design configurations.

Description: We have developed a fabric sensor knitted of tension-sensitive electro-conductive yarns. Each yarn has an elastic core, around which is wound two other separate, tension-sensitive electro-conductive threads, making this sensor inherently flexible and stretchable and allowing it to conform to any complicated surface on a robot, acting as a robotic skin. The pile-shaped surface of the sensor enhances its ability to detect tangential traction, while also enabling it to sense a normal load. Our aim is to use this sensor in applications involving relative sliding between its surface and a touched object, such as contact recognition, slip detection, and surface identification through a sliding motion. We carefully analyzed the static and dynamic characteristics of this sensor while varying the load and stretching force to fully understand its response and determine its degree of flexibility and stretchability. We found that a discrete wavelet transformation may be used to indicate stick/slip states while the sensor is sliding over surfaces. This method was then used to detect slippage events acting on the sensor's surface, and to decode textures in a classification test using an artificial neural network. Because of its flexibility and sensitivity, this sensor can be used widely as a robotic skin in humanoid robots.

Description: Carbon nanotubes (CNTs) are demonstrated as one of the most interesting materials for gas sensing. The possibility to obtain CNT thin-films via solution-processing techniques has paved the way for low-cost applications of such sensors. In this paper, we demonstrate that high performance gas sensors based on CNT thin-films can be obtained by direct spray deposition onto flexible substrates. The results obtained for ${rm NH}_{3}$ sensing using CNT films deposited on polyimide show exceptionally high as well as immediate response to the test gas, with performance comparable with that obtained on oxidized silicon substrates. In addition, a good repeatability of the sensor response to defined gas concentrations is demonstrated. This represents a major step toward low-cost large-scale production of this class of devices.

Description: We present a calibration technique for an acoustic imaging microphone array, combined with a digital camera. Computer vision and acoustic time of arrival data are used to obtain microphone coordinates in the camera reference frame. Our new method allows acoustic maps to be plotted onto the camera images without the need for additional camera alignment or calibration. Microphones and cameras may be placed in an ad-hoc arrangement and, after calibration, the coordinates of the microphones are known in the reference frame of a camera in the array. No prior knowledge of microphone positions, inter-microphone spacings, or air temperature is required. This technique is applied to a spherical microphone array and a mean difference of 3 mm was obtained between the coordinates obtained with this calibration technique and those measured using a precision mechanical method.

Description: In this paper, we present a transform scheme where a secondary transform is applied after the conventional DCT for intra as well as inter prediction residues. Our approach is applicable to any block-based video codec that employs transforms along the horizontal and vertical direction separably. The secondary transform is applied to the lower K ( ${rm K}={4}$ or 8) frequency coefficients of the output of conventional DCT at block with dimensions 8 and larger. The proposed transform scheme has low complexity as it is applied only to the top-left portion of the DCT output, especially in the context of large blocks such as 32 $,times,$ 32 where an alternate non-DCT 32 $,times,$ 32 transform would have a prohibitive implementation hardware cost. The proposed technique is single-pass, and the choice of whether to use the secondary transform is solely based on the prediction direction for intra residue, and on transform unit location in the prediction unit for the inter residue. The scheme requires no additional signaling information or R-D search. Our simulation results show that the proposed transform scheme provides significant BD-rate improvement over the conventional DCT-based coding scheme. Finally, we also show how to implement the proposed secondary transforms with low latency in hardware.

Description: In this paper, we describe a novel algorithm for unsupervised segmentation of images with low depth of field (DOF). First of all, a multi-scale reblurring model is used to detect the object of interest (OOI) in saliency space. Then, to determine the boundary of OOI, an active contour model based on hybrid energy function is proposed. In this model, a global energy item related with the saliency map is adopted to find the global minimum, and a local energy term regarding the low DOF image is used to improve the segmentation precision. In addition, an adaptive parameter is attached to this model to balance the weight of global and local energy. Furthermore, an unsupervised curve initialization method is designed to reduce the number of evolution iterations. Finally, we conduct experiments on various low DOF images, and the results demonstrate the high robustness and precision of the proposed approach.

Description: In this paper, we propose a novel method that treats pose estimation as a problem with the constraints of human segmentation consistency from single images. Different from the previous paper, we integrate pose estimation and object segmentation into a joint optimization. With the support of segmentation consistency, we can obtain more reliable pose results. Through analyzing the energy function of pose estimation and human segmentation, we convert the pose estimation into a binary optimization problem that has the same formation as segmentation. The top-down pose shape cues, bottom-up visual cues, and the consistency constraints that penalize the mismatching of pose and human foreground are incorporated into our final objective function. Qualitative and quantitative experimental results demonstrate the merits of our method in pose estimation on Ramanan benchmark and Buffy data sets.

Description: A real-time and accurate object detection framework, ${rm C}^{4}$ , is proposed in this paper. ${rm C}^{4}$ achieves 20 fps speed and the state-of-the-art detection accuracy, using only one processing thread without resorting to special hardware such as GPU. The real-time accurate object detection is made possible by two contributions. First, we conjecture (with supporting experiments) that contour is what we should capture and signs of comparisons among neighboring pixels are the key information to capture contour cues. Second, we show that the CENTRIST visual descriptor is suitable for contour based object detection, because it encodes the sign information and can implicitly represent the global contour. When CENTRIST and linear classifier are used, we propose a computational method that does not need to explicitly generate feature vectors. It involves no image preprocessing or feature vector normalization, and only requires $O(1)$ steps to test an image patch. ${rm C}^{4}$ is also friendly to further hardware acceleration. It has been applied to detect objects such as pedestrians, faces, and cars on benchmark data sets. It has comparable detection accuracy with state-of-the-art methods, and has a clear advantage in detection speed.

Description: Previous image clutter metrics were proposed on the thought that clutter was just a perceptual effect, while we identify clutter as both perceptual and cognitive effects. Under this identification, we give a new definition of image clutter metric by analyzing the research results in the fields of visual psychology and psychophysics. According to the definition, we further put forward a DisSIMilarity (DSIM) based image clutter metric, which can also be taken as a kind of HVS-based signal-to-clutter ratio. The earlier image clutter metrics produced limited success in predicting targeting performance mainly since they did not consider brain cognitive characteristics. We develop a brain cognitive dissimilarity measure (BCDM) as a quantitative estimate of the selection weights which are allocated by brain attentional mechanism to affect visual selection processes. A human vision perceptual dissimilarity measure (VPDM), fully embodying vision perceptual properties, is first established between the target and clutter images, and then we utilize the BCDM between the two images as selection weights to pool the VPDM to be a clutter metric, which can be called DSIM metric. The metric is tested in Search_2 dataset provided by TNO Human Factors Research Institute of Netherlands. Error analysis and correlation tests demonstrate that the DSIM metric makes a more significant improvement than previously proposed metrics in predicting 62 observers' targeting performances including detection probability, false alarm probability and search time.

Description: Despite continuous improvements in optical flow in the last three decades, the ability for optical flow algorithms to handle illumination variation is still an unsolved challenge. To improve the ability to interpret apparent object motion in video containing illumination variation, an illumination-robust optical flow method is designed. This method decouples brightness into reflectance and illumination components using a stochastic technique; reflectance is given higher weight to ensure robustness against illumination, which is suppressed. Illumination experiments using the Middlebury and University of Oulu databases demonstrate the decoupled method's improvement when compared with state-of-the-art. In addition, a novel technique is implemented to visualize optical flow output, which is especially useful to compare different optical flow methods in the absence of the ground truth.

Description: Accurate grain segmentation on 3D superalloy images is very important in materials science and engineering. From grain segmentation, we can derive the underlying superalloy grains' micro-structures, based on how many important physical, mechanical, and chemical properties of the superalloy samples can be evaluated. Grain segmentation is, however, usually a very challenging problem because: 1) even a small 3D superalloy sample may contain hundreds of grains; 2) carbides and noises may degrade the imaging quality; and 3) the intensity within a grain may not be homogeneous. In addition, the same grain may present different appearances, e.g., different intensities, under different microscope settings. In practice, a 3D superalloy image may contain multichannel information where each channel corresponds to a specific microscope setting. In this paper, we develop a multichannel edge-weighted centroidal Voronoi tessellation (MCEWCVT) algorithm to effectively and robustly segment the superalloy grains from 3D multichannel superalloy images. MCEWCVT performs segmentation by minimizing an energy function, which encodes both the multichannel voxel-intensity similarity within each cluster in the intensity domain and the smoothness of segmentation boundaries in the 3D image domain. In the experiment, we first quantitatively evaluate the proposed MCEWCVT algorithm on a four-channel Ni-based 3D superalloy data set (IN100) against the manually annotated ground-truth segmentation. We further evaluate the MCEWCVT algorithm on two synthesized four-channel superalloy data sets. The qualitative and quantitative comparisons of 18 existing image segmentation algorithms demonstrate the effectiveness and robustness of the proposed MCEWCVT algorithm.

Description: Local binary pattern (LBP) is sensitive to noise. Local ternary pattern (LTP) partially solves this problem. Both LBP and LTP, however, treat the corrupted image patterns as they are. In view of this, we propose a noise-resistant LBP (NRLBP) to preserve the image local structures in presence of noise. The small pixel difference is vulnerable to noise. Thus, we encode it as an uncertain state first, and then determine its value based on the other bits of the LBP code. It is widely accepted that most of the image local structures are represented by uniform codes and noise patterns most likely fall into the non-uniform codes. Therefore, we assign the value of an uncertain bit hence as to form possible uniform codes. Thus, we develop an error-correction mechanism to recover the distorted image patterns. In addition, we find that some image patterns such as lines are not captured in uniform codes. Those line patterns may appear less frequently than uniform codes, but they represent a set of important local primitives for pattern recognition. Thus, we propose an extended noise-resistant LBP (ENRLBP) to capture line patterns. The proposed NRLBP and ENRLBP are more resistant to noise compared with LBP, LTP, and many other variants. On various applications, the proposed NRLBP and ENRLBP demonstrate superior performance to LBP/LTP variants.

Description: It is known that if the objective of a wireless sensor network is not to reconstruct individual sensor readings at a fusion center but rather to compute a linear function of them, then the interference property of the wireless channel can be beneficially harnessed by letting nodes transmit simultaneously. Recently, an analog computation scheme was proposed to show that it is possible to take the advantage of the interference property even if nonlinear functions are to be computed. The scheme involves some pre-processing on the sensor readings and post-processing on the superimposed signals observed by the fusion center. Correspondingly, this paper provides a thorough base for a theory of analog-computing functions over wireless channels by specifying what is the maximum achievable. This means it is determined for networks of arbitrary topology which functions are generally analog-computable over the channel and how many wireless resources are needed. It turns out that the considerations are closely related to the famous 13th Hilbert problem and that analog-computations can be universally performed in the sense that the pre-processing at sensor nodes is independent of the function to be computed. Universality reduces the complexity of transmitters and the signaling overhead, and it is shown that this property is preserved if nodes leave or join the network. Analog-computability is therefore of high practical relevance as it allows for an efficient computation of functions in sensor networks.

Description: We study the application of matrix completion in the process of calibrating physical devices. In particular we propose an algorithm together with reconstruction bounds for calibrating circular ultrasound tomography devices. We use the time-of-flight (ToF) measurements between sensor pairs in a homogeneous medium to calibrate the system. The calibration process consists of a low-rank matrix completion algorithm to de-noise and estimate random and structured missing ToFs, and the classic multi-dimensional scaling method to estimate the sensor positions from the ToF measurements. We provide theoretical bounds on the calibration error. Several simulations are conducted to evaluate the theoretical results presented in this paper.

Description: We propose a particle filtering technique to track multiple maneuvering targets in the presence of clutter. We treat data association and state estimation, which are the two important sub-problems in tracking, as separate problems. We develop a game-theoretic framework to solve the data association, in which we model each tracker as a player and the set of measurements as strategies. We develop utility functions for each player, and then use a regret-based learning algorithm to find the equilibrium of this game. The game-theoretic approach allows us to associate measurements to all the targets simultaneously. Further, in contrast to the traditional Monte-Carlo data association algorithms that use samples of the association vector obtained from a proposal distribution, our method finds the association in a deterministic fashion. We then use Monte-Carlo sampling on the reduced dimensional state of each target, independently, and thereby mitigate the curse-of-dimensionality problem that is known to occur in particle filtering. We provide a number of numerical results to demonstrate the performance of our proposed filtering algorithm.

Description: To overcome the difficulties in applying gradient-based operators to color images, Di Zenzo introduced the color tensor, an operator that provides a gradient field for multichannel images. An elegant application for this operator was developed in the domain of multichannel image visualization: Socolinsky and Wolff proposed to reintegrate Di Zenzo's gradient by solving a Poisson equation, yielding a greyscale representation of the multispectral contrast of the input image. Di Zenzo's gradients are, however, generally not integrable and some approximation must be introduced. Thus, the resulting image can suffer from artifacts such as the smearing of edges. In this paper, we focus on the integrability of Di Zenzo's gradients. We show that the integrability of the obtained field can be improved dramatically through a simple desaturation of the color image (as in the HSV color space). This result can be readily extended to multispectral images by defining an analogue to saturation. We present several results explaining what happens to color tensors as the saturation changes. Significantly we show that small changes of the saturation in the linear image space can result in large improvements in the integrability of tensor gradients calculated in logarithmic color space. This result is important for two reasons. 1) Log-differences are more perceptually meaningful. 2) In log-space we can operate with retinex algorithms, which are well known techniques for contrast enhancement. We propose that they can be used to “put back” any contrast that might be lost in the desaturation step and, more importantly, they can enhance contrast at the same time as reintegrating the gradient field because of their relation to partial differential equations. Finally, we evaluate our method psychophysically. Compared with other commonly used image fusion methods, experiments show that our data fusion using the Di Zenzo color tensor after desaturating the image and where a si- ple contrast boost is applied is strongly preferred.

Description: In this paper we deal with the problem of detecting an extended target embedded in homogeneous Gaussian interference with unknown but structured covariance matrix. We model the possible target echo, from each range bin under test, as a deterministic signal with an unknown scaling factor accounting for the target response. At the design stage, we exploit some a-priori knowledge about the operating environment enforcing the inverse interference plus noise covariance matrix to belong to a set described via unitary invariant continuous functions. Hence, we derive the constrained Maximum Likelihood (ML) estimates of the unknown parameters, under both the $H_{0}$ and $H_{1}$ hypotheses, and design the Generalized Likelihood Ratio Test (GLRT) for the considered decision problem. At the analysis stage, we assess the performance of the devised GLRT for some covariance matrix uncertainty sets of practical relevance both for spatial and Doppler processing. The results highlight that correct use of the a-priori knowledge can lead to a detection performance quite close to the optimum receiver which supposes the perfect knowledge of the interference plus noise covariance matrix.

Description: Describes the above-named upcoming special issue or section. May include topics to be covered or calls for papers.

Description: In this paper, we present a novel memory-efficient high-throughput scalable architecture for multi-level 2-D DWT. We studied the existing DWT architectures and observed that data scanning method has a significant impact on the memory efficiency of DWT architecture. We propose a novel parallel stripe-based scanning method based on the analysis of the dependency graph of the lifting scheme. With the new scanning method for multi-level 2D DWT, a high memory efficient scalable parallel pipelined architecture is developed. The proposed architecture requires no frame memory and a temporal memory of size only $3 N +682$ for the 3-level DWT decomposition with an image of size $N times N$ pixels with 32 pixels processed concurrently. The elimination of frame memory and the small temporal memory lead to significant reduction in overall size. The proposed architecture has a regular structure and achieves 100% hardware utilization. The synthesis results in 90 nm CMOS process show that the proposed architecture achieves a better area-delay product by 60% and higher throughput by 97% when compared to the best existing design for the CDF (Cohen-Daubechies-Favreau) 9/7 2-D DWT.

Description: A scalable monolithically integrated photonic space switch is proposed which uses a combination of Mach–Zehnder modulators and semiconductor optical amplifiers (SOAs) for improved crosstalk performance and reduced switch loss. This architecture enables the design of high-capacity, high-speed, large-port count, low-energy switches. Extremely low crosstalk of better than −50 dB can be achieved using a 2 × 2 dilated hybrid switch module. A “building block” approach is applied to make large port count optical switches possible. Detailed physical layer multiwavelength simulations are used to investigate the viability of a 64 × 64 port switch. Optical signal degradation is estimated as a function of switch size and waveguide induced crosstalk. A comparison between hybrid and SOA switching fabrics highlights the power-efficient, high-performance nature of the hybrid switch design, which consumes less than one-third of the energy of an equivalent SOA-based switch. The significantly reduced impairments resulting from this switch design enable scaling of the port count, compared to conventional SOA-based switches.

Description: We consider a multiple-input multiple-output (MIMO) interference channel (IC), where a single data stream per user is transmitted and each receiver treats interference as noise. The paper focuses on the open problem of computing the outermost boundary (so-called Pareto boundary-PB) of the achievable rate region under linear transceiver design. The Pareto boundary consists of the strict PB and non-strict PB. For the two user case, we compute the non-strict PB and the two ending points of the strict PB exactly. For the strict PB, we formulate the problem to maximize one rate while the other rate is fixed such that a strict PB point is reached. To solve this non-convex optimization problem which results from the hard-coupled two transmit beamformers, we propose an alternating optimization algorithm. Furthermore, we extend the algorithm to the multi-user scenario and show convergence. Numerical simulations illustrate that the proposed algorithm computes a sequence of well-distributed operating points that serve as a reasonable and complete inner bound of the strict PB compared with existing methods.

Description: We have studied plasmonic slot nanoresonators (PSNRs) embedded in a gold-coated microfiber. Light is coupled from the plasmonic waveguide into the PSNR, showing strong localization in three dimensions. Single bow-tie and rectangular PSNRs, as well as cascades of multiple bow-tie PSNRs, have been considered. The intensity enhancement and the resonance wavelength depend on both the PSNR and microfiber dimensions. The PSNRs embedded in plasmonic microfibers could find wide range of applications, such as surface enhanced Raman scattering, optical filtering, bio-sensing, and spectroscopy.

Description: This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy performance as the system is interference-limited. In the literature, assuming that the receiver operates in half duplex (HD) mode, the aforementioned problem has been addressed via use of cooperating nodes who act as jammers to confound the eavesdropper. This paper investigates an alternative solution, which assumes the availability of a full duplex (FD) receiver. In particular, while receiving data, the receiver transmits jamming noise to degrade the eavesdropper channel. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. For the case in which global channel state information is available, we aim to design the optimal jamming covariance matrix that maximizes the secrecy rate and mitigates loop interference associated with the FD operation. We consider both fixed and optimal linear receiver design at the destination, and show that the optimal jamming covariance matrix is rank-1, and can be found via an efficient 1-D search. For the case in which only statistical information on the eavesdropper channel is available, the optimal power allocation is studied in terms of ergodic and outage secrecy rates. Simulation results verify the analysis and demonstrate substantial performance gain over conventional HD operation at the destination.

Description: This paper addresses the problem of logical topology design for optical backbone networks subject to stochastic traffic demands. The network design problem is broken into three tasks: traffic routing, capacity allocation, and link placement. While the routing and capacity allocation subproblem can be formulated using convex optimization, it is prohibitive to add the link placement component to the nonlinear formulation since the link placement problem involves integer variables. To address this issue, we develop a linear formulation for the routing and capacity allocation subproblem by applying tools from robust optimization. We show that this linear formulation performs comparably to the optimal nonlinear formulation. Our formulation can then be used to solve the link-placement subproblem for stochastic traffic. We show that optimal logical topologies for deterministic traffic demands are not necessarily optimal for stochastic traffic demands. We develop algorithms for finding logical topologies optimized for stochastic traffic.

Description: We report novel rocking long period gratings (R-LPGs) made by introducing permanent periodic twist along a standard single mode fiber. Very high coupling efficiency of 32.5 dB was achieved with 23 periods and a 2° rocking angle. The responses of R-LPGs to temperature, strain, and torsion were tested. Compared with a normal LPG written under the same conditions, the R-LPGs were found to have a similar sensitivity to temperature, five times smaller sensitivity to strain, and insensitive to twist.

Description: This paper presents a complete analytical framework for modeling memoryless nonlinear effects in an intensity modulation and direct detection optical wireless communication system based on orthogonal frequency division multiplexing. The theory employs the Bussgang theorem, which is widely accepted as a means to characterize the impact of nonlinear distortions on normally distributed signals. This paper proposes a new method to generalize this approach, and it describes how a closed-form analytical expression for the system bit error rate can be obtained for an arbitrary memoryless distortion. Major distortion effects at the transmitter stage such as quantization and nonlinearity from the light emitting diode are analyzed. Four known orthogonal-frequency-division-multiplexing-based modulation schemes for optical communication are considered in this paper: direct-current-biased optical OFDM, asymmetrically clipped optical OFDM, pulse-amplitude-modulated discrete multitone modulation, and unipolar orthogonal frequency division multiplexing.

Description: This paper presents a downlink scheme that permits the coexistence, on a passive optical network branch, of future DSP-based optical network units (ONUs) that can receive advanced modulation signals and legacy ONUs that can receive only on–off keying (OOK) signals. In the proposed scheme, the two types of signals, advanced modulation signals and OOK signals, are multiplexed by using a hierarchical star quadrature amplitude modulation (QAM) format and transmitted simultaneously on a single carrier. The design criteria and the feasibility of the proposal are discussed. The coexistence of 10G-class ONUs and DSP-based ONUs using hierarchical star 8-QAM format is numerically analyzed and experimentally evaluated. The results confirm that a 10-Gbps OOK signal and 30-Gbps star 8-QAM signal can be received with 30.5-dB loss budget by an APD and intradyne detector with DSP, respectively. The ability of the proposed approach to expand the coverage area is also introduced.

Description: A novel filter for nonlinear and non-Gaussian systems is proposed in this paper. The unscented Kalman filter is designed to give a preliminary estimation of the state. An additional RBF-network is added to the UKF innovation term to compensate for the non-Gaussianity of the whole system. The Renyi's entropy of the innovation is introduced and parameters of the RBF-network are updated using minimum entropy criterion at each time step. It has been shown that the proposed algorithm has a high accuracy in estimation because entropy can characterize all the randomness of the residual while UKF only cares for the mean and the covariance. It has been proved that with properly chosen bandwidth $Sigma$ , the minimum entropy problem of the innovation is convex. Therefore, the proposed adaptive nonlinear filter will be globally convergent and the misadjustment will be proportional to the step size $mu$ . The effectiveness of the proposed method is shown by simulation.

Description: We report on the results of numerical investigations into the effects of slot geometry of horizontal slot microdisk resonators on their performance as optical biosensors. We find that for resonator-based biosensors, the mode overlap is the limiting factor for the performance. With this finding, we suggest that slot resonators are superior to conventional, evanescent-field based resonators primarily for the surface sensing, where a high optical field created by the thin slots can be used. Possible mixing of modes reduces the mode overlap and thus need to be avoided by proper design of the resonator structure. We further propose an optimized triple-slot structure to double the possible detector sensitivity.

Description: We demonstrated 3.2-Tb/s (32 $,times,$ 120-Gb/s) unrepeatered transmission over 445-km fiber with ${rm A}_{rm eff}$ -managed-span. This was achieved by employing co-propagating second-order pumped Raman amplification and remote optically pumped amplifier, which was counter-propagating second-order Raman pumped. This letter also discusses design tradeoff on the nonlinear tolerance and Raman gain efficiency within ${rm A}_{rm eff}$ -managed-span for performance enhancement of unrepeatered transmission.

Description: We report a new approach to photonic generation of binary phase-coded microwave signals based on the asymmetric phase modulation indexes of a phase modulator in the TE and TM polarization states. The proposed system is extremely simplified compared with any other techniques reported in the previous literature since we only use one phase modulator. The microwave carrier frequency is widely tunable, and the $pi$ phase shift of the microwave signal is independent of the amplitude of the electrical driving signal. The proposed technique is theoretically analyzed and experimentally verified at carrier frequencies of 10 and 25 GHz, respectively.

Description: This letter reports a cost-effective transmitter solution for future generations of long reach passive optical networks (PONs). It is based on the direct adaptive orthogonal frequency division multiplexing modulation of a hybrid III/V-on-silicon laser. Because of low-noise and good linearity of the hybrid laser, modulation formats as high as 32-quadrature amplitude modulation are achieved. Data-rates of 21.5 and 12.4 Gb/s are demonstrated, respectively, in optical back-to-back and 50 km single-mode fiber (SMF)-link free from amplifiers, while on-off keying transmission is limited to ${〈}{rm 7}~{rm Gb}/{rm s}$ at 20 km SMF. The proposed solution stands as a cost-effective solution for next-generation time and wavelength division multiplexing PONs with extended reach, as the hybrid laser can further be made tunable.

Description: We propose a photonic technique for millimeter-wave ultra-wideband (MMW-UWB) signal generation via direct frequency up-conversion using a dual-parallel Mach–Zehnder modulator (DPMZM). By properly setting the dc bias voltages of the DPMZM, the baseband UWB pulse is up-converted to the MMW band without pulse distortion. In addition, the excessive residual local oscillator component is perfectly suppressed. The electrical spectrum of the up-converted UWB signal satisfies the Federal Communications Commission spectral mask very well.

Description: We developed a multiframe observation method of femtosecond laser pulse propagating in transparent medium based on optical polarigraphy technique. An echelon was introduced into the probe light and divided it into multipulses both in time and space, allowing a multiframe detection of the intense laser pulse propagating in materials. Using this method, we realized a multiframe observation of a single femtosecond laser pulse propagating in CS2 with ultrafast self-modulation such as filamentation. This imaging method has been demonstrated to be of a femtosecond time resolution and a frame rate of ${sim}{rm THz}$ .

Description: An in-line submillimeter hole fabricated by micro-drilling plastic optical fiber (POF) directly has been proposed as a compact refractive index sensor. Since the hole behaves as a concave lens if it is filled with a liquid having lower refractive index than that of the fiber core, transmittance increases in proportion to the refractive index. Analysis of the sensor transmittance has been performed using a simple ray optics model. Through immersing a 1.5-mm POF with a 0.35-mm-radius hole into various liquids, transmittance of the sensor has been measured at 670 nm. It has been shown that the experimental and analytical results are in excellent agreement.

Description: We experimentally demonstrate two types of silicon-on-insulator microring devices: 1) a slotted conventional microring resonator (MRR) using a multimode interferometer (MMI) coupler as the coupling element; and 2) an MMI-coupled slotted Mach–Zehnder interferometer (MZI) racetrack microring. We achieved a high bandwidth of 1.1 nm and a quality factor Q of ${sim}{1300}$ at the wavelength of 1510 nm for the conventional MRRs with a radius of 20 $mu{rm m}$ . A high extinction ratio (17–25 dB) is exhibited over a wavelength range from 1490 to 1520 nm. At the 1515-nm resonance wavelength, the MMI-coupled MZI racetrack microring demonstrates a quasi-free spectral range of 22.6 nm with a high extinction ratio of 25 dB. The demonstrated devices have many applications such as biochemical and gas sensing and modulation in communication systems.

Description: We report an experimental demonstration of a nonuniformly spaced photonic microwave delay-line filter implemented using an incoherent broadband optical source and a spatially discrete chirped fiber Bragg grating (SD-CFBG). The SD-CFBG performs simultaneously three functions: 1) to slice the spectrum of the broadband optical source for generating the filter taps; 2) to provide nonuniform time delays; and 3) to control the weights of the filter taps. Since negative or complex coefficients are equivalently generated based on the nonuniform sampling, a filter with an arbitrary spectra response is achieved. To verify the effectiveness of the proposed method, a flat-top bandpass microwave filter with seven all-positive nonuniformly spaced taps at 12 GHz is experimentally demonstrated. The proposed method offers a cost-effective and easy-to-implement solution for photonic microwave filters having arbitrary frequency responses.

Description: An Si photonic transmitter is integrated in a 130-nm silicon-on-insulator complementary metal–oxide–semiconductor technology. A high-speed photonic ring modulator is designed for 25-Gb/s operation with an 8-dB extinction ratio. The ring is driven with a $2.4hbox{-}{rm V}_{rm pp}$ swing using a low-power inverter driver. With a reference receiver, the 25-Gb/s link is measured with a bit error rate (BER) of $10^{-12}$ . The total transmitter power consumption is 17 mW at 25 Gb/s for an energy efficiency of 680 fJ/b excluding laser and ring tuning power.

Description: A higher order statistics (HOS)-based method is proposed in this letter to estimate the nonlinear amplitude-to-phase (AM/PM) conversion function of power amplifiers (PAs) in communications systems. By utilizing the symmetry property of the modulated signal, the proposed method estimates the AM/PM conversion function using only the PA output signal, from which the phase predistorter (PD) function can be derived. Simulation results show that the HOS-based method can accurately determine the phase PD function required to compensate for the AM/PM distortion in the PA, yielding a linearization performance close to that of non-blind methods in terms of adjacent channel power ratio and error vector magnitude.

Description: We introduce a method to create lossy versions of one image, either by successively merging the constant regions of the original image, or by iteratively splitting the regions from a created lossy image using horizontal or vertical line segments. Merging and split decisions are greedily taken, according to the best slope towards next point in the rate-distortion curve. For each created lossy image, the region contours and the optimal depth values can be entropy coded in three ways: with a new algorithm, or with two existing lossless coding algorithms. The obtained results compare favorably with the existing lossy methods.

Description: Water reflection, a typical imperfect reflection symmetry problem, plays an important role in image content analysis. Existing techniques of symmetry recognition, however, cannot recognize water reflection images correctly because of the complex and various distortions caused by the water wave. Hence, we propose a novel water reflection recognition technique to solve the problem. First, we construct a novel feature space composed of motion blur invariant moments in low-frequency curvelet space and of curvelet coefficients in high-frequency curvelet space. Second, we propose an efficient algorithm including two sub-algorithms: low-frequency reflection cost minimization and high-frequency curvelet coefficients discrimination to classify water reflection images and to determine the reflection axis. Through experimenting on authentic images in a series of tasks, the proposed techniques prove effective and reliable in classifying water reflection images and detecting the reflection axis, as well as in retrieving images with water reflection.

Description: Poisson inverse problems arise in many modern imaging applications, including biomedical and astronomical ones. The main challenge is to obtain an estimate of the underlying image from a set of measurements degraded by a linear operator and further corrupted by Poisson noise. In this paper, we propose an efficient framework for Poisson image reconstruction, under a regularization approach, which depends on matrix-valued regularization operators. In particular, the employed regularizers involve the Hessian as the regularization operator and Schatten matrix norms as the potential functions. For the solution of the problem, we propose two optimization algorithms that are specifically tailored to the Poisson nature of the noise. These algorithms are based on an augmented-Lagrangian formulation of the problem and correspond to two variants of the alternating direction method of multipliers. Further, we derive a link that relates the proximal map of an $ell_{p}$ norm with the proximal map of a Schatten matrix norm of order $p$ . This link plays a key role in the development of one of the proposed algorithms. Finally, we provide experimental results on natural and biological images for the task of Poisson image deblurring and demonstrate the practical relevance and effectiveness of the proposed framework.

Description: In this paper, we propose an object-aware holistic superpixel selection (HPS) method to automatically select the discriminative superpixels of an image for image classification purpose. Through only considering the selected superpixels, the interference of cluttered background on the object can be alleviated effectively and thus the classification performance is significantly enhanced. In particular, for an image, HPS first selects the discriminative superpixels for the characteristics of certain class, which can together match the object template of this class well. In addition, these superpixels compose a class-specific matching region. Through performing such superpixel selection for several most probable classes, respectively, HPS generates multiple class-specific matching regions for a single image. Then, HPS merges these matching regions into an integral object region through exploiting their pixel-level intersection information. Finally, such object region instead of the original image is used for image classification. An appealing advantage of HPS is the ability to alleviate the interference of cluttered background yet not require the object to be segmented out accurately. We evaluate the proposed HPS on four challenging image classification benchmark datasets: Oxford-IIIT PET 37, Caltech-UCSD Birds 200, Caltech 101, and PASCAL VOC 2011. The experimental results consistently show that the proposed HPS can remarkably improve the classification performance.

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Description: Should broadband be treated as a public utility or be left solely to the private sector? Should state or municipal governments provide basic services, act as anchor tenants, or simply monitor progress? Whichever side of the debate you stand on, there is a growing consensus on the importance of high-quality broadband connections for everyone to ensure sustainable social and economic growth. Policy makers, legal scholars, and CEOs have shared their perspective. It's time for computer scientists to join the conversation.

Description: The Internet's growth, and the proliferation of online collaboration tools and platforms and the federated systems that support them, have enabled ad hoc processes in which people interact in a dynamic collective way. Such activities are characterized by their flexibility and data-driven nature, which makes them more difficult to analyze and support than traditionally rigid processes. Systems that handle dynamic collective work activities must address three main challenges: finding patterns in ad hoc execution behavior, handling concurrent users and concurrently executing tasks, and providing operational support. This special issue provides a snapshot of ongoing work in this area that addresses these challenges.

Description: MailOfMine aims at automatically building a set of workflow models--which represent the artful processes behind knowledge workers' activities--on top of a collection of email messages. Such models formalize the unspecified agile processes that knowledge workers autonomously perform: because these models aren't defined a priori by experts but are rather inferred from real-life scenarios, they're guaranteed to respect true workflow executions. Moreover, knowledge workers can share, compare, and preserve such models to put in evidence their best practices and thus benefit the entire business. Finally, workers and organizations can analyze such processes to determine bottlenecks and delays in actual executions. MailOfMine describes workflow models according to a declarative approach, with a specific visual notation.

Description: Organizations require tools that can assess their online reputations as well as the impact of their marketing and public outreach activities. The Media Watch on Climate Change is a Web intelligence and online collaboration platform that addresses this requirement. It aggregates large archives of digital content from multiple stakeholder groups and enables the co-creation and visualization of evolving knowledge archives. Here, the authors introduce the base platform and a context-aware document editor as an add-on that supports concurrent authoring by multiple users. While documents are being edited, semantic methods analyze them on the fly to recommend related content. The system computes positive or negative sentiment automatically to provide a better understanding of third-party perceptions. The editor is part of an interactive dashboard that uses trend charts and map projections to show how often and where relevant information is published, and to provide a real-time account of concepts that stakeholders associate with a topic.

Description: Casebook embraces social and collaboration technology, analytics, and intelligence to advance the state of the art in case management from systems of record to a system of engagement for knowledge workers. It addresses complex, inefficient work practices, information loss during hand offs between teams, and failure to learn from previous case experience. Intelligent agents help people adapt to changing work practices by tracking process evolution and providing updates and recommendations. Social collaboration surrounding cases integrates communication with information and supports collaborative roadmapping to enable people to work as they collaborate, thus accelerating how quickly and accurately they handle cases.

Description: As large energy consumers, base stations need energy-efficient wireless access networks. This article compares the design of Long-Term Evolution (LTE) networks to energy-efficient LTE-Advanced networks. LTE-Advanced introduces three new functionalities--carrier aggregation, heterogeneous networks, and extended multiple-input, multiple-output (MIMO) support. The authors develop a power consumption model for LTE and LTE-Advanced macrocell and femtocell base stations, along with an energy efficiency measure. They show that LTE-Advanced's carrier aggregation and MIMO improve networks' energy efficiency up to 400 and 450 percent, respectively.

Description: In a previous article, the authors demonstrated that effectively discovering Web services helps developers avoid several common design errors in Web Service Description Language (WSDL) documents. Their proposed guidelines are unfortunately applicable only when publishers follow the top-down, or contract-first, method of building services, which isn't very popular due to its inherent costs. Here, they present an approach for preventing such errors when using a counterpart method--namely, bottom-up or code-first--and measure the approach's impact on service discovery. The rationale behind the study is that because code-first service interfaces are automatically generated by tools that--given a service implementation--deterministically map programming language constructs onto WSDL elements, the measurable properties of service implementations could influence resulting service interfaces.

Description: In this article, the authors propose a new approach to distributed computing with Web browsers and introduce the WeevilScout prototype framework. The proliferation of Web browsers and the performance gains being achieved by current JavaScript virtual machines raises the question whether Internet browsers can become yet another middleware for distributed computing. With 2 billion users online, computing through Internet browsers has the potential to amass immense resources, thus transforming the Internet into a distributed computer ideal for common classes of distributed scientific applications such as parametric studies. As a proof of concept, the authors demonstrate how a cluster of globally distributed Internet browsers is used to compute thousands of bio-informatics tasks.

Description: Very large datasets, also known as big data, originate from many domains, including healthcare, energy, weather, business, and social networks. Deriving knowledge is more difficult than ever when we must do it by intricately processing big data. Organizations rely on third-party, commodity computing resources or clouds to gather the computational resources required to manipulate data of this magnitude. Although social networks are perhaps among the largest big data producers, the collaboration that results from leveraging this paradigm could help to solve big data processing challenges. Here, the authors explore using personal ad hoc clouds comprised of individuals in social networks to address such challenges.

Description: Cloud computing services are traditionally deployed on centralized computing infrastructures confined to a few data centers, while cloud applications run in a single data center. However, the cloud's centralized nature can be limiting in terms of performance and cost for applications where users, data, and computation are distributed. The authors present an overview of distributed clouds that might be better suited for such applications. They briefly describe the distributed cloud landscape and introduce Nebula, a highly decentralized cloud that uses volunteer edge resources. The authors provide insights into some of its key properties and design issues, and describe a distributed MapReduce application scenario to illustrate the benefits and trade-offs of using distributed and decentralized clouds for distributed data-intensive computing applications.

Description: In current architectures for infrastructure networks, a single (logically centralized) network element is in charge of managing mobility. As new requirements arise from the widespread use of sophisticated end-user devices, new standard solutions are emerging that challenge the status quo and aim for an evolution toward distributed mobility management.

Description: Recent sensing-based systems involve a multitude of users, devices, and places. These types of systems challenge existing approaches for conducting valid system evaluations. Here, the author discusses such evaluation challenges and revisits existing system evaluation methodologies.

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Description: After 40 years of relational databases and of cohabitation between flat tables and object-oriented programming, a new generation of data stores is emerging. Sometimes referred to as NoSQL, this new generation supports hierarchical, heterogeneous data such as XML, JavaScript Object Notation, and Binary JSON. While the abstract querying primitives of the relational algebra (join, selection, projection, and so on) also make a lot of sense in the NoSQL world, a need exists for a tailor-made language for querying hierarchical, heterogeneous datasets. This article briefly summarizes the history of databases, then describes the JSONiq language. JSONiq was designed from the ground up to support JSON data and run against all JSON- or BSON-based data stores, turning them into full-fledged databases.

Description: Passwords are an old-fashioned authentication mechanism that remains ubiquitous, but modern processing hardware with massive parallelism has suddenly undercut the security of the traditional eight-character password. Administrators and users need to understand the increased risks and to find ways to use and protect longer passwords.

Description: Douglas Engelbart, J.C.R. Licklider, DARPA, augmented human intellect, Google Glass, and silicon sapience: what a fascinating amalgam of leaders, devices, and concepts! With today's cloud computing and with the legacy of giants like Engelbart and Licklider, we are at the beginning of a new age in machine intelligence that could result in a remarkable partnership between computers and humans, reinforcing the strengths of both.

Description: 2013-2014 Editorial Calendar

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Description: We investigate the operation of directionally bistable semiconductor-ring lasers as all-optical flip-flops. We demonstrate fast switching between the two lasing directions by injection of optical pulses acting as set and reset control signals with switching times as fast as 20 ps, delay times as short as 60 ps, and switching energy of 150 fJ.

Description: Mode beating via third order nonlinearity in semiconductor ring lasers has been analyzed using a frequency-domain multimode rate equation model. Compared with Fabry–Perot lasers, semiconductor ring lasers are 1.33, 2, and 4 times more efficient in self-gain compression, cross-gain compression, and four-wave mixing processes, respectively, due to its travelling-wave nature. It is shown that, using dual (pump and signal) external optical injections into the ring laser cavity, multiple modes can be locked in phase via the strong four wave mixing phenomenon. This results in modulation of the light wave at the mode beating frequencies which could be used for RF optical carrier generation.

Description: Through selectively controlling the stimulated Brillouin scattering in optical fibers with different lengths, a continuously tunable time-delay scheme enabling to work in a large range is proposed in this letter. This is realized by connecting a fixed long single-mode fiber (SMF) to one of the several selectable short SMFs that successively have an equal increment in length. These short-length fibers are, respectively, fixed to the different channels between two identical optical switches. Therefore, a wide-range and continuously tunable slow-light delay line can be constructed by changing the power of the pump beam, assisted by switching to different channels. In the experiment, a time delay from 0 to 201.29 ns is demonstrated for a five-channel configuration. A further large-range time delay can be expected if one adds the number of channels accordingly.

Description: We demonstrate active coherent polarization locking of two high power polarization-maintained fiber amplifiers using single frequency dithering technique. When the active phasing system is in the closed loop, a 481-W single frequency and polarization-maintained laser beam with near-diffraction-limited beam quality is generated in the circumstance of imbalanced power ratio of the two amplifiers. The beam quality ( ${rm M}^{2}$ factor) of the coherently polarization locked beam is measured to be ${〈}{1.2}$ and the polarization extinction ratio of the phasing beam can be as high as 10 dB (91%).

Description: We demonstrate a stable gain-switched thulium fiber laser pumped with an acousto-optically modulated Er, Yb co-doped fiber laser at 1.56 $mu{rm m}$ . The laser produced 1850 nm pulses with 2.5 $mu{rm J}$ pulse energy and 75 ns pulsewidth at a repetition rate of 500 kHz, resulting in a maximum average output power of 1.32 W and slope efficiency of 54.7% with respect to absorbed pump power. The dependence of laser output characteristics on the pump power and repetition rate was presented and discussed. Repetition rate of gain-switched pulses was tuned continuously from 68 kHz to over 1 MHz at the maximum pump power-level of 8 W. The broad tuning range of pulse repetition rate makes this laser suitable for various applications.

Description: This paper proposes a novel image-based framework to manipulate the illumination of human face through adaptive layer decomposition. According to our framework, only a single reference image, without any knowledge of the 3D geometry or material information of the input face, is needed. To transfer the illumination effects of a reference face image to a normal lighting face, we first decompose the lightness layers of the reference and the input images into large-scale and detail layers through weighted least squares (WLS) filter with adaptive smoothing parameters according to the gradient values of the face images. The large-scale layer of the reference image is filtered with the guidance of the input image by guided filter with adaptive smoothing parameters according to the face structures. The relit result is obtained by replacing the largescale layer of the input image with that of the reference image. To normalize the illumination effects of a non-normal lighting face (i.e., face delighting), we introduce similar reflectance prior to the layer decomposition stage by WLS filter, which make the normalized result less affected by the high contrast light and shadow effects of the input face. Through these two procedures, we can change the illumination effects of a non-normal lighting face by first normalizing the illumination and then transferring the illumination of another reference face to it. We acquire convincing relit results of both face relighting and delighting on numerous input and reference face images with various illumination effects and genders. Comparisons with previous papers show that our framework is less affected by geometry differences and can preserve better the identification structure and skin color of the input face.

Description: In this paper a contrast-guided image interpolation method is proposed that incorporates contrast information into the image interpolation process. Given the image under interpolation, four binary contrast-guided decision maps (CDMs) are generated and used to guide the interpolation filtering through two sequential stages: 1) the 45 $^{circ}$ and 135 $^{circ}$ CDMs for interpolating the diagonal pixels and 2) the 0 $^{circ}$ and 90 $^{circ}$ CDMs for interpolating the row and column pixels. After applying edge detection to the input image, the generation of a CDM lies in evaluating those nearby non-edge pixels of each detected edge for re-classifying them possibly as edge pixels. This decision is realized by solving two generalized diffusion equations over the computed directional variation (DV) fields using a derived numerical approach to diffuse or spread the contrast boundaries or edges, respectively. The amount of diffusion or spreading is proportional to the amount of local contrast measured at each detected edge. The diffused DV fields are then thresholded for yielding the binary CDMs, respectively. Therefore, the decision bands with variable widths will be created on each CDM. The two CDMs generated in each stage will be exploited as the guidance maps to conduct the interpolation process: for each declared edge pixel on the CDM, a 1-D directional filtering will be applied to estimate its associated to-be-interpolated pixel along the direction as indicated by the respective CDM; otherwise, a 2-D directionless or isotropic filtering will be used instead to estimate the associated missing pixels for each declared non-edge pixel. Extensive simulation results have clearly shown that the proposed contra- t-guided image interpolation is superior to other state-of-the-art edge-guided image interpolation methods. In addition, the computational complexity is relatively low when compared with existing methods; hence, it is fairly attractive for real-time image applications.

Description: We address the following subspace learning problem: supposing we are given a set of labeled, corrupted training data points, how to learn the underlying subspace, which contains three components: an intrinsic subspace that captures certain desired properties of a data set, a penalty subspace that fits the undesired properties of the data, and an error container that models the gross corruptions possibly existing in the data. Given a set of data points, these three components can be learned by solving a nuclear norm regularized optimization problem, which is convex and can be efficiently solved in polynomial time. Using the method as a tool, we propose a new discriminant analysis (i.e., supervised subspace learning) algorithm called Corruptions Tolerant Discriminant Analysis (CTDA), in which the intrinsic subspace is used to capture the features with high within-class similarity, the penalty subspace takes the role of modeling the undesired features with high between-class similarity, and the error container takes charge of fitting the possible corruptions in the data. We show that CTDA can well handle the gross corruptions possibly existing in the training data, whereas previous linear discriminant analysis algorithms arguably fail in such a setting. Extensive experiments conducted on two benchmark human face data sets and one object recognition data set show that CTDA outperforms the related algorithms.

Description: In this paper, we explore a sequential Bayesian bound for state-space models focusing on hybrid continuous and discrete random states. We provide an analytic recursion for the sequential Weiss–Weinstein (SWW) bound for linear state-space models with solutions for Gaussian, uniform, and exponential distributions as derived, as well as for a combination of these. We compare the SWW bound for discretized states with the corresponding bound for the continuous states. The SWW bound is contrasted with the sequential Cramér–Rao bound for Gaussian distributions. Practical issues of SWW bounds are discussed and numerical simulation results provide insights into their behavior.

Description: Achieving better imaging of weak sources in the presence of strong interfering sources is a major challenge in various fields of signal processing, such as radio astronomy, SAR imaging, SONAR and wideband signal processing. We present a new algorithm for parameter estimation that can be implemented when a moving array is used. This adaptive beamformer can be employed in a variety of applications, such as radio astronomy with synthetic aperture arrays, SAR imaging, DOA estimation in towed array SONAR and wideband DOA estimation. Analytic performance analysis is provided together with simulations and tests on a new radio astronomy array. All these indicate a significant improvement compared to currently used filterbank techniques such as the MVDR, when strong interference is present, either inside or outside the field of view of the array. The latter case is especially important when directional antennas are used.

Description: We observe stimulated Brillouin scattering (SBS) in polymer optical fibers (POFs) using a pump–probe technique without lock-in detection, and fully investigate the dependences of the Brillouin gain spectrum on the POF length, pump power, probe power, and temperature. Since the POF has relatively high propagation loss of 250 dB/km at 1.55 μm, an optimal POF length exists for SBS observation, which is found to be approximately 3.8 m with 21.1-dBm pump and 22.2-dBm probe waves. As the probe and pump powers are increased, the Stokes power is also raised but nonlinearly. The temperature dependence of the Brillouin frequency shift is –4.02 MHz/K, which agrees well with the previous report. These results indicate that the Brillouin signal in POFs observed with this technique can be directly applied to the development of POF-based Brillouin optical time-domain analysis systems for high-precision temperature sensing.

Description: An exact analytical formulism obtained directly by solving a system of rate and propagation equations in the presence of pump excited-state absorption is presented on the basis of four-band transition scheme in radially symmetric and longitudinally uniform monomode erbium doped silica fiber lasers. The exact analytical expressions are determined for overall gain, small-signal gain, pump intensity threshold, lasing threshold condition, and optimal fiber length in terms of alleviative measurable quantities of photon intensities, transition rates, absorption and emission cross sections, and reflectivity of mirrors. Mutatis mutandis, the formulas bear a verisimilitude to analytical expressions appearing in the literature for these parameters.

Description: This paper addresses the problem of adaptive waveform design for estimation of parameters of linear systems. This problem arises in several applications such as radar, sonar, or tomography. In the proposed technique, the transmit/input signal waveform is optimally determined at each step based on the observations in the previous steps. The waveform is determined to minimize the Bayesian Cramér-Rao bound (BCRB) or the Reuven-Messer bound (RMB) for estimation of the unknown system parameters at each step. The algorithms are tested for spatial transmit waveform design in multiple-input multiple-output radar target angle estimation at very low signal-to-noise ratio. The proposed techniques allow to automatically focusing the transmit beam toward the target direction. The simulations show that the proposed adaptive waveform design methods achieve significantly higher rate of performance improvement as a function of the pulse index, compared to other signal transmission methods, in terms of estimation accuracy.

Description: This letter deals with the Kalman filter (KF) based on a third-order integrated random walk model (RW3). The resulting filter, noted as RW3-KF, is well suited to track slow time-varying parameters with strong trend behaviour. We first prove that the RW3-KF in steady-state admits an equivalent structure to the third-order digital phase-locked loops (DPLL). The approximate asymptotic mean-squared-error (MSE) is obtained by solving the Riccati equations, which is given in a closed-form expression as a function of the RW3 model parameter: the state noise variance. Then, the closed-form expression of the optimum state noise variance is derived to minimize the asymptotic MSE. Simulation results are given for the particular case where the parameter to be estimated is a Rayleigh channel coefficient with Jakes' Doppler spectrum.

Description: In this paper, we present a finite difference method (FDM) based on layered and adaptive meshing to extract substrate resistance. To allow adaptive meshing, a novel synchronization method is introduced which expresses the potential at other points than the centroids of panels by modifying the finite difference equations. This method makes it possible to overcome the high computational cost of the FDM due to tight uniform meshing requirements while enjoying a straightforward implementation and easy handling of irregular/arbitrary substrate structures to extract the substrate coupling of integrated circuits.

Description: In nanometer technologies, local interconnects are believed to cause a major impact on timing and power in VLSI circuits. To assess the impact of the interconnects on timing and power in a real high performance microprocessor design in a quantitative manner, this article presents results from an extensive study carried out on RTL-to-layout synthesized blocks in a 45-nm technology core. The study shows that the interconnects in these blocks account for 30% of the cycle time, on an average, on the worst internal timing paths and contribute nearly one-third to the power dissipation. This points to severity of impact due to the interconnects in today's high performance designs.

Description: We established a novel theoretical analysis framework for optimizing the cooling system configuration of chips employing thermoelectric cooling (TEC) elements by extending the theory of inverse-positive matrices and the eigenvalue/eigenvector theory in linear algebra. In this brief, we present a new theorem and its formal proof, which is the key enabler to achieving a provably optimal solution for configuring bias current levels of TEC devices.

Description: Image quality metrics (IQMs), such as the mean squared error (MSE) and the structural similarity index (SSIM), are quantitative measures to approximate perceived visual quality. In this paper, through analyzing the relationship between the MSE and the SSIM under an additive noise distortion model, we propose a perceptually relevant MSE-based IQM, MSE-SSIM, which is expressed in terms of the variance of the source image and the MSE between the source and distorted images. Evaluations on three publicly available databases (LIVE, CSIQ, and TID2008) show that the proposed metric, despite requiring less computation, compares favourably in performance to several existing IQMs. In addition, due to its simplicity, MSE-SSIM is amenable for the use in a wide range of image and video tasks that involve solving an optimization problem. As an example, MSE-SSIM is used as the objective function in designing a Wiener filter that aims at optimizing the perceptual visual quality of the output. Experimental results show that the images filtered with a MSE-SSIM-optimal Wiener filter have better visual quality than those filtered with a MSE-optimal Wiener filter.

Description: In this paper, we propose a unified energy minimization model for segmentation of non-smooth image structures, e.g., textures, based on Mumford–Shah functional and linear patch model. We consider that image patches of a non-smooth image structure can be modeled by a patch subspace, and image patches of different non-smooth image structures belong to different patch subspaces, which leads to a computational framework for segmentation of non-smooth image structures. Motivated by the Mumford–Shah model, we show that this segmentation framework is equivalent to minimizing a piecewise linear patch reconstruction energy. We also prove that the error of segmentation is bounded by the error of the linear patch reconstruction, meaning that improving the linear patch reconstruction for each region leads to reduction of the segmentation error. In addition, we derive an algorithm for the linear patch reconstruction with proven global optimality and linear rate of convergence. The segmentation in our method is achieved by minimizing a single energy functional without requiring predefined features. Hence, compared with the previous methods that require predefined texture features, our method can be more suitable for handling general textures in unsupervised segmentation. As a by-product, our method also produces a dictionary of optimized orthonormal descriptors for each segmented region. We mainly evaluate our method on the Brodatz textures. The experiments validate our theoretical claims and show the clear superior performance of our methods over other related methods for segmentation of the textures.

Description: Look-up table (LUT) halftoning is an efficient way to construct halftone images and approximately simulate the dot distribution of the learned halftone image set. In this paper, a general mechanism named multiple look-up table (MLUT) halftoning is proposed to generate the halftones of direct binary search (DBS), whereas the high efficient characteristic of the LUT is still preserved. In the MLUT, the standard deviation is adopted as an important feature to classify various tables. In addition, the proposed quick standard deviation evaluation is employed to yield an extremely low computational complexity in calculating the standard deviation. In the parameter optimization, the autocorrelation is adopted because it can fully characterize the periodicity of dot distribution. Experimental results demonstrate that the dot distribution generated by the proposed method approximates to that of the DBS, which enables the proposed scheme as a very competitive candidate in the copying and printing industry.