ALBERT

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: Quality-of-experience-oriented mechanisms, not currently available in traditional database management systems, allow a system to take into consideration user-specified requirements and to adjust its operations accordingly, based on user expectations.

Description: Just as technological innovations enable identity science researchers to develop better recognition systems, they can also create novel challenges for such systems.

Description: We don't have satisfactory answers to questions that ask what we must share with our neighbor for our common good and the rights we retain in the process. Yet such answers will be the legacy of our age. The Web extra at http://youtu.be/U0piYSt35YU is a video segment in which author David Alan Grier expands on his Errant Hashtag column, in which he discusses how the idea of "smart cities" makes more sense than the idea of "smart homes."

Description: Spaces that encourage the mix of academic instruction with practical professional experience beyond the traditional computing classroom can significantly increase students' motivation to learn and to share their learning with others.

Description: Measuring student learning in computer science education presents particular challenges, making objective assessment elusive to educators and researchers. Development and validation of the FCS1 and CAS assessment tools demonstrate both the feasibility and benefits of validated assessment instruments in this discipline.

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Description: IEEE Computer Graphics and Applications editor in chief Gabriel Taubin welcomes the magazine's incoming EIC Miguel Encarnação and bids farewell to editorial-board members David Kasik, Kari Pulli, and Diego Gutierrez.

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.

Description: The winners of the 2012 IEEE Visualization Contest combined methods from molecular, flow, and scalar data visualization to reveal the characteristics and processes in the contest data. Because the simulated material didn't behave according to theory from textbooks, one challenge was to find meaningful visualizations to facilitate exploratory analysis. The contest winners created an interactive visual-analysis application based on MegaMol, their visualization framework. The tailored visualizations revealed data characteristics such as thermal vibrations and the spatial distribution of polarization domains. Domain expert knowledge verified the results. This video at http://youtu.be/RXnNKekY7VE shows the dataset used and the development of vector clusters over time.

Description: The next generation of VR simulators could take into account a novel input: the user's mental state, as measured with electrodes and a brain-computer interface. One illustration of this promising path is a project that adapted a guidance system's force feedback to the user's mental workload in real time. A first application of this approach is a medical training simulator that provides virtual assistance that adapts to the trainee's mental activity. Such results pave the way to VR systems that will automatically reconfigure and adapt to their users' mental states and cognitive processes.

Description: In conventional vehicle teleoperation systems, using low-bandwidth, high-delay transmission links causes a serious problem for remote control of the vehicles. To solve this problem, a proposed teleoperation system employs 3D maps and GPS time synchronization. Two GPS receivers measure the transmission delay, which the system uses to estimate the vehicle's location and orientation. Field experiments show that the 3D-map-based interface lets users easily comprehend the remote environment while navigating a vehicle. The experiments also show that taking communication delays into account improves maneuverability.

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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: The author has written this short message to introduce himself as the new Editor-in-Chief (EiC) of the IEEE JOURNAL OF OCEANIC ENGINEERING. He took on the role last autumn, following the untimely death of his predecessor, Bill Carey. The new EiC gives an indication of his priorities and plans; as they become fleshed out, he will provide more details in subsequent editorial messages.

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Description: This special issue features three articles on interactive 3D developments for the Web. Two articles discuss exploiting GPU ubiquity and performance; the other applies current Web3D languages to a real-world education challenge.

Description: Until recently, a major drawback of declarative-3D approaches for the Web was the encoding of scene-graph-related structured data along with a text-based description of unstructured vertex data. Loading times were long, and 3D Web content wasn't available until the full page had completely loaded. To overcome this limitation requires external mesh data containers that are referenced in the scene description. In particular, sequential image geometry containers and explicit binary containers align well with GPU buffer structures, thus enabling fast decoding and GPU uploads. Furthermore, progressive binary geometry enables simple, yet highly progressive transmission of arbitrary mesh data on the Web.

Description: This issue's article examines the digital artwork of Michael Frank.

Description: Image retargeting adjusts images to arbitrary sizes such that they can be viewed on different displays. Content-aware image retargeting has been receiving increased attention. In particular, researchers have improved a patch-wise scaling method for image retargeting at the object level. The scaling partitions the image into rectangular patches of adaptive sizes, which are comparable to the sizes of the salient objects in the image. This partitioning is based on a visual-saliency map; accordingly, the method labels the patches as important or unimportant. Then, the method scales the important patches as uniformly as possible and stretches or squeezes the unimportant patches to fit the target size. A patch-based image-similarity measure finds the optimal set of scaling factors. In experiments, the improved method performed well for three image types: lines and edges, foreground objects, and geometric structures.

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: The LiverAnatomyExplorer is a real-time surgical teaching tool based on state-of-the-art Web technologies such as SVG (Scalable Vector Graphics), X3D (Extensible3D), and WebGL (Web Graphics Library). Unlike other medical e-learning systems, the LiverAnatomyExplorer combines traditional clinical 2D imagery with interactive Web-based 3D models derived from patient-specific image data. The tool is enhanced by surgical videos, a self-assessment tool, and an online authoring tool with which instructors can manage the presented case studies and create multiple-choice quizzes.

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: In recent years, in an attempt to maximize performance, machine learning approaches for event-related potential (ERP) spelling have become more and more complex. In this paper, we have taken a step back as we wanted to improve the performance without building an overly complex model, that cannot be used by the community. Our research resulted in a unified probabilistic model for ERP spelling, which is based on only three assumptions and incorporates language information. On top of that, the probabilistic nature of our classifier yields a natural dynamic stopping strategy. Furthermore, our method uses the same parameters across 25 subjects from three different datasets. We show that our classifier, when enhanced with language models and dynamic stopping, improves the spelling speed and accuracy drastically. Additionally, we would like to point out that as our model is entirely probabilistic, it can easily be used as the foundation for complex systems in future work. All our experiments are executed on publicly available datasets to allow for future comparison with similar techniques.

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: Compressive sensing has shown significant promise in biomedical fields. It reconstructs a signal from sub-Nyquist random linear measurements. Classical methods only exploit the sparsity in one domain. A lot of biomedical signals have additional structures, such as multi-sparsity in different domains, piecewise smoothness, low rank, etc. We propose a framework to exploit all the available structure information. A new convex programming problem is generated with multiple convex structure-inducing constraints and the linear measurement fitting constraint. With additional a priori information for solving the underdetermined system, the signal recovery performance can be improved. In numerical experiments, we compare the proposed method with classical methods. Both simulated data and real-life biomedical data are used. Results show that the newly proposed method achieves better reconstruction accuracy performance in term of both L1 and L2 errors.

Description: Transcranial magnetic stimulation (TMS) is a tool for noninvasive stimulation of neuronal tissue used for research in cognitive neuroscience and to treat neurological disorders. Many TMS applications call for large electric fields to be sharply focused on regions that often lie deep inside the brain. Unfortunately, the fields generated by present-day TMS coils diffuse and decay rapidly as they penetrate into the head. As a result, they tend to stimulate relatively large regions of tissue near the brain surface. Earlier studies suggested that a focused TMS excitation can be attained using multiple nonuniformly fed coils in a multichannel array. We propose a systematic, genetic algorithm-based technique for synthesizing multichannel arrays that minimize the volume of the excited region required to achieve a prescribed penetration depth and maintain realistic values for the input driving currents. Because multichannel arrays are costly to build, we also propose a method to convert the multichannel arrays into single-channel ones while minimally materially deteriorating performance. Numerical results show that the new multi- and single-channel arrays stimulate tissue 2.4 cm into the head while exciting 3.0 and 2.6 times less volume than conventional Figure-8 coils, respectively.

Description: In difficult epileptic patients, the brain structures are explored by means of depth multicontact electrodes [stereoelectroencephalography (SEEG)]. Recently, a novel diagnostic technique allows an accurate definition of the epileptogenic zone using deep brain stimulation (DBS). The stimulation signal propagates in the brain and thus it appears on most of the other SEEG electrodes, masking the local brain electrophysiological activity. The objective of this paper is the DBS-SEEG signals detrending and denoising in order to recover the masked physiological sources. We review the main filtering methods and put forward an approach based on the combination of filtering with generalized eigenvalue decomposition (GEVD). An experimental study on simulated and real SEEG shows that our approach is able to separate DBS sources from brain activity. The best results are obtained by an original singular spectrum analysis-GEVD approach.

Description: This paper presents a novel palpation probe based on optical fiber technology. It is designed to measure stiffness distribution of a soft tissue while sliding over the tissue surface in a near frictionless manner. A novelty of the probe is its ability to measure indentation depth for nonplanar tissue profiles which are commonly experienced during surgery. Since tumors are often harder than the surrounding tissue, the proposed probe can intraoperatively aid the surgeon to rapidly identify the presence, location, and size of the tumors through the generation of a tissue stiffness map. The probe can concurrently measure tissue reaction force, indentation depth, and the orientation of the probe with respect to the tissue surface. Hence, it can generate an elasticity model of the tissue with minimum measurement inaccuracies caused by surface profile variations. Further, the probe has a tunable force range and the indentation force can be adjusted externally to match tissue limitations. The performance of the probe developed was validated using simulated soft tissues samples. Our tumor identification experiments showed that the probe can accurately identify the location and size of tumors hidden inside nonflat tissue surfaces. Further, the probe has clearly demonstrated its potential to identify tumors with tumor–tissue stiffness ratios as low as 2.1.

Description: We introduce a novel method for the automatic detection of atrial fibrillation (AF) using time-varying coherence functions (TVCF). The TVCF is estimated by the multiplication of two time-varying transfer functions (TVTFs). The two TVTFs are obtained using two adjacent data segments with one data segment as the input signal and the other data segment as the output to produce the first TVTF; the second TVTF is produced by reversing the input and output signals. We found that the resultant TVCF between two adjacent normal sinus rhythm (NSR) segments shows high coherence values (near 1) throughout the entire frequency range. However, if either or both segments partially or fully contain AF, the resultant TVCF is significantly lower than 1. When TVCF was combined with Shannon entropy (SE), we obtained even more accurate AF detection rate of 97.9% for the MIT-BIH atrial fibrillation (AF) database $(n$ = 23) with 128 beat segments. The detection algorithm was tested on four databases using 128 beat segments: the MIT-BIH AF database, the MIT-BIH NSR database ( $n$ = 18), the MIT-BIH Arrhythmia database ( $n$ = 48), and a clinical 24-h Holter AF database ( $n$ = 25). Using the receiver operating characteristic curves from the combination of TVCF and SE, we obtained a sensitivity of 98.2% and specificity of 97.7% for the MIT-BIH AF database. For the MIT-BIH NSR database, we found a specificity of 99.7%. For the MIT-BIH Arrhythmia database, the sensitivity and specificity were 91.1% and 89.7%, respectively. For the clinical database (24-h Holter data), the sensitivity and specificity were 92.3% and 93.6%, respectively. We - lso found that a short segment (12 beats) also provided accurate AF detection for all databases: sensitivity of 94.7% and specificity of 90.4% for the MIT-BIH AF, specificity of 94.4% for the MIT-BIH-NSR, the sensitivity of 92.4% and specificity of 84.1% for the MIT-BIH arrhythmia, and sensitivity of 93.9% and specificity of 84.4% for the clinical database. The advantage of using a short segment is more accurate AF burden calculation as the timing of transitions between NSR and AF are more accurately detected.

Description: In functional MRI, it is often desirable to reduce the readout duration to make the acquired data less prone to $T_2^*$ susceptibility artifacts. In addition, a shorter readout length allows for a shorter minimum TE, which is important for optimizing SNR. This can be achieved by undersampling the $k$ -space. However, the conventional Fourier transform-based reconstruction method suffers from under-sampling artifacts such as high-frequency ringing and loss of resolution. To address this problem, we revisit the constrained-model approach using the generalized-series (GS) which has been proposed to address the undersampling problem for dynamic MRI. We propose a modification to the conventional use of the model in order to reflect small hemodynamic signal changes typical in fMRI. Specifically, while realizing that having high model order is necessary to capture missing information, we found that it is not necessary to span all frequencies of GS basis functions uniformly. Instead, having $k$ -space and GS “sampling” trajectories covering low-frequencies uniformly while spanning high-frequencies sparsely, was observed to be an efficient strategy. The ability of the method over the conventional GS approach in improving resolution of functional images and activation maps while reducing undersampling ringing is demonstrated by simulations and experiments at $3$ T. Reduction in the readout time allowed an increase of statistical signal power as compared to the fully sampled acquisition. Unlike compressed sensing approaches, the proposed method is linear and hence has lower computational complexity. The method could prove useful for other imaging modalities where the signal change is smaller than the ba- eline component.

Description: Interbreath interval (IBI), the time interval between breaths, is an important measure used to analyze irregular breathing patterns in neonates. The discrete bursts of neural activity generate the IBI time series, which exhibits stochastic as well as deterministic dynamics. To quantify the irregularity of breathing, we propose a point process model of IBI using a comprehensive stochastic dynamic modeling framework. The IBIs of immature breathing patterns exhibit a long tail distribution and within a point process model, we have considered the lognormal distribution to represent the stochastic IBI characteristics. An autoregressive (AR) function is embedded within the model to capture the short-term IBI dynamics including abrupt IBI prolongations related to sporadic and periodic apneas that are common in neonates. We tested the utility of our paradigm for depicting the respiratory dynamics in neonatal rats and in preterm infants. Kolmogorov–Smirnov (KS) and independence tests reveal that the model accurately tracks the dynamic characteristics of the signals. In preterm infants, our model-derived indices of IBI instability strongly correlate with clinically derived indices of maturation. Our results validate a new class of algorithms, based on the point process theory, for defining instantaneous measures of breathing irregularity in neonates.

Description: Remote photoplethysmography (rPPG) enables contactless monitoring of the blood volume pulse using a regular camera. Recent research focused on improved motion robustness, but the proposed blind source separation techniques (BSS) in RGB color space show limited success. We present an analysis of the motion problem, from which far superior chrominance-based methods emerge. For a population of 117 stationary subjects, we show our methods to perform in 92% good agreement ( $pm hbox{1.96}sigma$ ) with contact PPG, with RMSE and standard deviation both a factor of 2 better than BSS-based methods. In a fitness setting using a simple spectral peak detector, the obtained pulse-rate for modest motion (bike) improves from 79% to 98% correct, and for vigorous motion (stepping) from less than 11% to more than 48% correct. We expect the greatly improved robustness to considerably widen the application scope of the technology.

Description: A system for capturing habitual, in-home gait measurements using an environmentally mounted depth camera, the Microsoft Kinect, is presented. Previous work evaluating the use of the Kinect sensor for in-home gait measurement in a lab setting has shown the potential of this approach. In this paper, a single Kinect sensor and computer were deployed in the apartments of older adults in an independent living facility for the purpose of continuous, in-home gait measurement. In addition, a monthly fall risk assessment protocol was conducted for each resident by a clinician, which included traditional tools such as the timed up a go and habitual gait speed tests. A probabilistic methodology for generating automated gait estimates over time for the residents of the apartments from the Kinect data is described, along with results from the apartments as compared to two of the traditionally measured fall risk assessment tools. Potential applications and future work are discussed.

Description: Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: $0.94 pm 0.08$ ) and “Euler characteristic” (AUC: $0.94 pm 0.07$ ), and GLCM-derived feature “Correlation” (AUC: $0.93 pm 0.07$ ). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

Description: We have developed a pupil-corneal reflection method-based gaze detection system, which allows large head movements and achieves easy gaze calibration. This system contains two optical systems consisting of components such as a camera and a near-infrared light source attached to the camera. The light source has two concentric LED rings with different wavelengths. The inner and outer rings generate bright and dark pupil images, respectively. The pupils are detected from a difference image created by subtracting the bright and dark pupil images. The light source also generates the corneal reflection. The 3-D coordinates of the pupils are determined by the stereo matching method using two optical systems. The vector from the corneal reflection center to the pupil center in the camera image is determined as ${bm r}$ . The angle between the line of sight and the line passing through the pupil center and the camera (light source) is denoted as $theta$ . The relationship $theta = k leftvert {bm r} rightvert$ is assumed, where $k$ is a constant. The theory implies that head movement of the user is allowed and facilitates the gaze calibration procedure. In the automatic calibration method, $k$ is automatically determined while the user looks around on the PC screen without fixating on any specific calibration target. In the one-point calibration method, the user is asked to fixate on one calibration target at the PC screen in order to correct the difference between the optical and visual axes. In the two-point calibration method, in order to correct the nonlinear relationship between $theta$ and $leftvert {bm r} rightvert$ , the user is asked to fixate on two targets. The experimental results show that the three proposed calibration methods improve the precision of gaze detection step by step. In addition, the average gaze error in the visual angle is less than 1 $^circ$ for the seven head positions of the user.

Description: We present an encapsulation scheme that combines atomic layer deposited (ALD) Al $_{2}$ O $_{3}$ and Parylene C for the encapsulation of implantable devices. The encapsulation performances of combining alumina and Parylene C was compared to individual layers of Parylene C or alumina and the bilayer coating had superior encapsulation properties. The alumina–Parylene coated interdigitated electrodes (IDEs) soaked in PBS for up to nine months at temperatures from 37 to 80 °C for accelerated lifetime testing. For 52-nm alumina and 6-μm Parylene C, leakage current was ∼20 pA at 5 VDC, and the impedance was about 3.5 MΩ at 1 kHz with a phase near −87° from electrochemical impedance spectroscopy for samples soaked at 67 °C for equivalent lifetime of 72 months at 37 °C. The change of impedance during the whole soaking period (up to 70 months of equivalent soaking time at 37 °C) over 1 to 10 $^{6}$  Hz was within 5%. The stability of impedance indicated almost no degradation of the encapsulation. Bias voltage effect was studied by continuously applying 5 VDC, and it reduced the lifetime of Parylene coating by ∼75% while it showed no measurable effect on the bilayer coating. Lifetime of encapsulation of IDEs with topography generated by attaching a coil and surface mount device (SMD) capacitor was about half of that of planer IDEs. The stable long-term insulation impedance, low leakage current, and better lifetime under bias voltage and topography made this double-layer encapsulation very promising for chronic implantable devices.

Description: Muscle sympathetic nerve activity is a primary source of cardiovascular control in humans. Traditional analyses smooth away the fine temporal structure of the sympathetic recordings, limiting our understanding of sympathetic activation mechanisms. We use multifiber spike trains extracted from standard microneurography voltage trace to characterize the sympathetic spiking at rest and during sympathoexcitation. Our analysis corroborates known features of sympathetic activity, such as bursting behavior, cardiac rhythmicity, and long conduction delays. It also elucidates new features such as large heartbeat-to-heartbeat variability of firing rates and precise pattern of spiking within cardiac cycles. We find that at low firing rates, spikes occur uniformly throughout the cardiac cycle, but at higher rates, they tend to cluster in bursts around a particular latency. This latency shortens and the clusters tighten as the firing rates grow. Sympathoexcitation increases firing rates and shifts the burst latency later. Negative rate/latency correlation and the sympathoexcitatory shift suggest that spike production of the individual fibers contributes significantly to the control of the sympathetic bursts strength. Access to fine scale temporal information, more physiologically accurate description of nerve activity, and new hypotheses about the nervous outflow control establishes sympathetic spiking as a valuable tool for the cardiovascular research.

Description: In this paper, we report the development of a flexible base array of penetrating electrodes which can be used to interface with the spinal cord. A customizable and feasible fabrication protocol is described. The flexible base arrays were fabricated and implanted into surrogate cords which were elongated by 12%. The resulting strains were optically measured across the cord and compared to those associated with two types of electrodes arrays (one without a base and one with a rigid base connecting the electrodes). The deformation behavior of cords implanted with the flexible base arrays resembled the behavior of cords implanted with individual microwires that were not connected through a base. The results of the strain test were used to validate a 2-D finite element model. The validated model was used to assess the stresses induced by the electrodes of the three types of arrays on the cord, and to examine how various design parameters (thickness, base modulus, etc.,) impact the mechanical behavior of the electrode array. Rigid base arrays induced higher stresses on the cord than the flexible base arrays which in turn imposed higher stresses than the individual microwire implants. The developed flexible base array showed improvement over the rigid base array; however, its stiffness needs to be further reduced to emulate the mechanical behavior of individual microwire arrays without a base.

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.

Description: This paper presents a novel energy management strategy for a hybridized power source small urban electric vehicle (EV). First, an analysis of load requirements for typical urban driving cycles is presented. Thereafter, the energy and power management issues are addressed for a multisource EV to define an improved management architecture. A dynamically restricted search space strategy coupled with a simulated annealing technique is exploited to accomplish the global optimization of the energy management system (EMS). The control of the dc/dc converter operations based on this EMS is also presented. The multiple sources have been simulated using an overall model implemented in Matlab/Simulink. A reduced-scale prototype has been built to analyze the performance of the energy management strategy. The results obtained show that energy management has been enhanced leading to an increase of the vehicle performance with reduced size embarked sources.

Description: Prediction intervals (PIs) are a promising tool for quantification of uncertainties associated with point forecasts of wind power. However, construction of PIs using parametric methods is questionable, as forecast errors do not follow a standard distribution. This paper proposes a nonparametric method for construction of reliable PIs for neural network (NN) forecasts. A lower upper bound estimation (LUBE) method is adapted for construction of PIs for wind power generation. A new framework is proposed for synthesizing PIs generated using an ensemble of NN models in the LUBE method. This is done to guard against NN performance instability in generating reliable and informative PIs. A validation set is applied for short listing NNs based on the quality of PIs. Then, PIs constructed using filtered NNs are aggregated to obtain combined PIs. Performance of the proposed method is examined using data sets taken from two wind farms in Australia. Simulation results indicate that the quality of combined PIs is significantly superior to the quality of PIs constructed using NN models ranked and filtered by the validation set.

Description: This paper presents a supervisory control unit (SCU) combined with short-term ahead wind speed prediction for proper and effective management of the stored energy in a small capacity flywheel energy storage system (FESS) which is used to mitigate the output power fluctuations of an aggregated wind farm. Wind speed prediction is critical for a wind energy conversion system since it may greatly influence the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. In this study, a wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction schemes including data error tolerance and ease in adaptability. The proposed SCU-based control would help to reduce the size of the energy storage system for minimizing wind power fluctuation taking the advantage of prediction scheme. The model for prediction using ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions.

Description: Due to its reduced communication overhead and robustness to failures, distributed energy management is of paramount importance in smart grids, especially in microgrids, which feature distributed generation (DG) and distributed storage (DS). Distributed economic dispatch for a microgrid with high renewable energy penetration and demand-side management operating in grid-connected mode is considered in this paper. To address the intrinsically stochastic availability of renewable energy sources (RES), a novel power scheduling approach is introduced. The approach involves the actual renewable energy as well as the energy traded with the main grid, so that the supply–demand balance is maintained. The optimal scheduling strategy minimizes the microgrid net cost, which includes DG and DS costs, utility of dispatchable loads, and worst-case transaction cost stemming from the uncertainty in RES. Leveraging the dual decomposition, the optimization problem formulated is solved in a distributed fashion by the local controllers of DG, DS, and dispatchable loads. Numerical results are reported to corroborate the effectiveness of the novel approach.

Description: The present paper investigates the effect of high penetration of photovoltaic (PV) systems on the small signal stability of a large power system. Reduced system inertia and altered power flow patterns as a result of the addition of the utility scale and residential rooftop PVs that replace a portion of conventional generation resources, may lead to decreased damping of the critical modes of the system. To identify the critical modes of the system and the effect of the high PV penetration on these modes, eigenvalue analysis is carried out on the aforementioned system under various PV penetration levels. To substantiate the results observed from the small signal analysis, transient analysis is carried out on the system under various PV penetration levels. The simulation results effectively identify the impact of high PV penetration on small signal stability of the studied system.

Description: A speed exclusion zone algorithm to prevent the rotor rotational frequency from exciting the side-side tower mode in a variable-speed wind turbine was designed. The algorithm was first tested on a simple wind turbine model developed in Simulink and then implemented and tested on an experimental test rig. Different speed exclusion zone widths were tested to observe how the performance of the wind turbine is affected. Results obtained from both simulations and experiments showed the effectiveness of the speed exclusion zone algorithm in preventing excitation of tower resonance. Results from different speed exclusion zone widths showed that with a wider exclusion zone, the tower mode is excited less at the expense of a larger power loss.

Description: A control strategy for the quasi-Z-source inverter (qZSI) with a battery-based photovoltaic (PV) power conversion system is proposed. A battery-assisted qZSI can buck/boost PV panel voltage by introducing shoot-through states, and make full use of PV power by the energy-stored battery paralleled to the quasi-Z-source capacitor. A dynamic small-signal model of the battery-assisted qZSI is established to design a closed-loop controller for regulating shoot-through duty ratio and managing the battery's energy storage. A modified space vector modulation (SVM) technique for the qZSI is applied to achieve low harmonics, high voltage utilization, and high efficiency. A P-Q decoupled grid-tie power injection is fulfilled with the maximum power capture from PV panels and the unity power factor. The validity of the proposed PV system is proved by experimental results, showing an efficient method for the energy-stored PV power generation.

Description: Doubly-fed induction generator (DFIG)-based wind turbines (WTs) are reported to suffer reliability problems due to the presence of slip-rings, brushes, and the gearbox. These disadvantages encouraged several research groups to investigate the viability of employing single or double-frame brushless cascade DFIGs (BCDFIGs) in grid-connected multimegawatt WTs especially offshore and in solar chimney power plants. In this regard, this paper tackles three main issues. Initially, the expected reduction in gear ratio when BCDFIGs are used instead of DFIGs is examined from a steady state perspective. A reduction would lead to less frequent maintenance and an improved return on investment. Next, a detailed comparison between DFIG-WTs and BCDFIG-WTs under unbalanced grid voltage is presented. Finally, the extent to which a multimegawatt BCDFIG-WT is grid code compliant in terms of fault ride-through capability is studied. This is illustrated by comparing and quantifying the response of a DFIG-WT and a BCDFIG-WT to a severe three-phase voltage dip. Simulation and experimental results indicate promising behavior for BCDFIGs during disturbances.

Description: We analyze the potential benefits of colocating wind and concentrating solar power (CSP) plants in the southwestern U.S. Using a location in western Texas as a case study, we demonstrate that such a deployment strategy can improve the capacity factor of the combined plant and the associated transmission investment. This is because of two synergies between wind and CSP: 1) the negative correlation between real-time wind and solar resource availability and 2) the use of low-cost high-efficiency thermal energy storage in CSP. The economic tradeoff between transmission and system performance is highly sensitive to CSP and transmission costs. We demonstrate that a number of deployment configurations, which include up to 67% CSP, yield a positive net return on investment.

Description: Renewable energy resources, especially wind power, are expected to provide a considerable portion of the world energy requirements in the near future. Large-scale wind power penetration impacts the electricity industry in many aspects and raises a number of technical challenges for the electricity network. A day-ahead network-constrained market clearing formulation is proposed which considers demand side resources. The proposed approach can provide flexible load profile and reduce the need for ramp up/down services by the conventional generators. This method can potentially facilitate a large penetration of wind power by shifting the wind power generation from the off-peak periods to the high-peak hours. The validity of the proposed approach has been verified using the IEEE 30 bus and 57 bus test systems.