Abstract: Interlocking is a suitable method to fix iron cores made of electrical steel sheets along the stack direction. However, this will increase iron loss of the core and, as a result, lower the efficiency and power density of electrical machines. In this paper, the influence of interlocking on the magnetic properties of ring cores is studied and evaluated by measurements. A linear increase of the inverse of magnetic field and iron loss with increasing number of interlocks shows that the influence of interlocking is local. This behavior coincides with the proposed model. Interlaminar eddy currents have no serious impact on the iron-loss properties. Averaged magnetic properties of the magnetically deteriorated regions are calculated according to the magnetic model. These data will be useful for accurate finite-element method calculations of iron losses in electrical machines.
Abstract: In this paper, we study the effect of the signal-to-noise ratio of magnetization measurements on the determination of the Curie temperature from the analysis of the magnetocaloric response. The procedure has been compared with the method of the inflection point of the magnetization versus temperature curves. Magnetization data have been simulated using the Arrott–Noakes equation of state, with the addition of different noise levels (either 1% of the measured signal or 0.3% of the measurement range). It is shown that the obtained values of the Curie temperature are more accurate in the case of the magnetocaloric procedure, although this method requires more data analysis than the inflection point method. Moreover, the field independence of the Curie temperature obtained from the magnetocaloric procedure allows us to perform a statistical analysis of the obtained values, reducing the associated error in the Curie temperature determination.
Autors: L. M. Moreno-Ramírez;V. Franco;M. Pękała;A. Conde;
Abstract: Fe–Ga (Galfenol) is a rare-earth-free alloy with useful magnetostrictive properties of nominal cost and robust mechanical properties advantageous for sensing, actuating, and energy harvesting. Understanding magnetostriction and magnetization behaviors under stress while at temperatures up to +250 °C is needed to explore the potential of harsh environment applications for magnetostrictive non-contact sensors, for use in applications such as monitoring torque changes in engines and rotorcraft shafts. Galfenol thin patches have the potential to operate in these applications, but alloy performance at these temperatures while under stress has not been studied. Thus, in this paper, we investigate simultaneous effects of temperature and compressive stresses on magnetic and magnetostrictive behaviors of single crystal Fe–Ga samples at temperatures from +25 °C to +250 °C while under compressive stresses of 0, 15, and 23 MPa. The samples are also subjected to temperatures up to +250 °C and no stress to acquire simultaneous magnetostriction and magnetization values. Building upon this experimental data, this paper attempts to relate temperature dependence and shape anisotropy to determine the effect on magnetic susceptibility at elevated temperatures. Understanding the roles of temperature and compressive stress as well as shape anisotropy on magnetostrictive, Fe–Ga alloys can provide an advanced understanding of the material properties and thus facilitate their use in a wider range of applications.
Abstract: For the first time, the influence of fast pulse induced skin effect on the current distribution inside the grounded-gate NMOS (GGNMOS) is reported. The skin effect results in the current crowding at the finger edges of the GGNMOS, leading to the high photoemission and high substrate potential at those regions. This report comprehensively explains some of the decades-old unexplained physical phenomena.
Abstract: Air gaps are often used in a design of power inductors. Different arrangements of air gap in a magnetic circuit influence the parameters of an inductor. Understanding this dependence allows a design of more efficient inductors. In this paper, the influence of different air-gap arrangements on the distribution of the magnetic flux density, the value of saturation current, and the power losses is presented. The 3-D finite-element analyses and laboratory measurements were realized for the exemplary inductor made of grain-oriented steel and copper foil. Additionally, the main rules of the design of inductors with distributed air-gap arrangement are also given.
Abstract: Two parties observing correlated random variables seek to run an interactive communication protocol. How many bits must they exchange to simulate the protocol, namely to produce a view with a joint distribution within a fixed statistical distance of the joint distribution of the input and the transcript of the original protocol? We present an information spectrum approach for this problem whereby the information complexity of the protocol is replaced by its information complexity density. Our single-shot bounds relate the communication complexity of simulating a protocol to tail bounds for information complexity density. As a consequence, we obtain a strong converse and characterize the second-order asymptotic term in communication complexity for independent and identically distributed observation sequences. Furthermore, we obtain a general formula for the rate of communication complexity, which applies to any sequence of observations and protocols. Connections with results from theoretical computer science and implications for the function computation problem are discussed.
Abstract: The use of online healthcare communities to acquire health-related information and reduce uncertainty over illnesses is currently hampered by the lack of understanding of how health information-seeking behavior can be stimulated in such environments. By drawing upon the theoretical notion of social self and personal self, and conducting a field survey among 101 online healthcare community users, this study investigates how social identity in online healthcare communities and individual users’ perceived disease severity jointly influence the health information-seeking propensity. This study contributes to the literature on health information seeking by investigating the influence of social self (social identity), personal self (perceived disease severity), and their interplay in online communities. The findings can guide healthcare providers and community managers in formulating strategic plans for promoting health information-seeking behavior.
Autors: Na Liu;Yu Tong;Hock Chuan Chan;
Appeared in: IEEE Transactions on Engineering Management
Abstract: Cutting a cake is a metaphor for the problem of dividing a resource (cake) among several agents. The problem becomes non-trivial when the agents have different valuations for different parts of the cake (i.e., one agent may like chocolate, while the other may like cream). A fair division of the cake is one that takes into account the individual valuations of agents and partitions of the cake based on some fairness criterion. Fair division may be accomplished in a distributed or centralized way. Due to its natural and practical appeal, it has been a subject of study in economics. To the best of our knowledge, the role of partial information in fair division has not been studied so far from an information theoretic perspective. Given the diversity of problems in fair division, we consider certain specific (yet important) problems that capture different aspects of information exchange in a fair division setting. From the class of distributed algorithms, we consider the classical divide and choose (DC) problem between two parties. Here, we study the effect of partial spying and voluntarily sharing of information in both one-shot and asymptotic scenarios. Furthermore, we consider implicit information transmission through actions for the repeated version of the problem. While identifying subgame perfect Nash equilibrium in repeated games with incomplete information on both sides is very difficult in general, for the special case of division of two items, we find a more stringent trembling hand perfect equilibrium. Next, from the class of centralized algorithms, we consider the Adjusted Winner (AW) algorithm between two players Alice and Bob. Brams and Taylor showed that if Alice can fully spy on Bob, she can trick the algorithm. We consider the same setup when partial spying is allowed and study the growth rate of Alice’s utility per spying bit. Via a transformation from AW to DC, it is shown that the problem reduces to the one studied-
earlier for DC. However, if Alice is forced to only spy certain simple structured functions of Bob’s valuation, an upper bound on the growth rate of utility per spying bit is derived. This bound is shown to be tight in some cases. We also consider a centralized algorithm for maximizing the overall welfare of the agents under the Nash collective utility function (CUF). This corresponds to a clustering problem. By observing a link between this problem and the portfolio selection problem in stock markets, we provide an upper bound on the increase of the Nash CUF for a clustering refinement.
Autors: Payam Delgosha;Amin Gohari;
Appeared in: IEEE Transactions on Information Theory
Abstract: In this paper, we consider a cache aided network in which each user is assumed to have individual caches, while upon users’ requests, an update message is sent through a common link to all users. First, we formulate a general information theoretic setting that represents the database as a discrete memoryless source, and the users’ requests as side information that is available everywhere except at the cache encoder. The decoders’ objective is to recover a function of the source and the side information. By viewing cache aided networks in terms of a general distributed source coding problem and through information theoretic arguments, we present inner and outer bounds on the fundamental tradeoff of cache memory size and update rate. Then, we specialize our general inner and outer bounds to a specific model of content delivery networks: file selection networks, in which the database is a collection of independent equal-size files and each user requests one of the files independently. For file selection networks, we provide an outer bound and two inner bounds (for centralized and decentralized caching strategies). For the case when the user request information is uniformly distributed, we characterize the rate versus cache size tradeoff to within a multiplicative gap of 4. By further extending our arguments to the framework of Maddah-Ali and Niesen, we also establish a new outer bound and two new inner bounds in which it is shown to recover the centralized and decentralized strategies, previously established by Maddah-Ali and Niesen. Finally, in terms of rate versus cache size tradeoff, we improve the previous multiplicative gap of 72 to 4.7 for the average case with uniform requests.
Abstract: The design and characterization of millimeter-scale GaAs photovoltaic (PV) cells are presented and demonstrate highly efficient energy harvesting in the near infrared (NIR). Device performance is improved dramatically by optimizing the device structure for the NIR spectral region and improving surface and sidewall passivation with the ammonium sulfide treatment and subsequent silicon nitride deposition. The power conversion efficiency of a 6.4-mm2 cell under 660-nW/mm2 NIR illumination at 850 nm is greater than 30%, which is higher than commercial crystalline silicon solar cells under similar illumination conditions. Critical performance limiting factors of submillimeter-scale GaAs PV cells are addressed and compared to theoretical calculations.
Autors: Eunseong Moon;David Blaauw;Jamie D. Phillips;
Appeared in: IEEE Transactions on Electron Devices
Abstract: In order to resolve the starting problem for position sensorless interior permanent magnet synchronous motor, an improved initial rotor position estimation method based on square-wave signal injection is presented in this paper. Instead of the conventional sinusoidal voltage injection, square-wave voltage signals are injected into stator windings to obtain magnet pole position. On the basis of saturation and saliency principle, the voltage pulse injection method was adopted to identify the magnet polarity. Detecting the magnet pole position by using the square-wave voltage injection, the error signal can be calculated without low-pass filters and time delays. The proposed method is verified via a 1.5 kW interior permanent magnet synchronous motor drive platform.
Autors: Xuan Wu;Yaojing Feng;Xiao Liu;Shouddao Huang;Xiaofang Yuan;Jian Gao;Jian Zheng;
Abstract: Synchronous motors are installed in numerous applications within the pulp and paper industry, and their reliability is essential to the successful operation of a mill. Critical steps in the installation of synchronous motors are frequently misunderstood, and maintenance practices often overlook the most common causes of motor failure. Limitations on time and resources may exacerbate these deficiencies, but a carefully planned installation and maintenance program should not burden a mill with excessive work and will ultimately increase reliability of the equipment.
Abstract: Time-frequency analysis (TFA) is an effective tool to identify the signal frequency components and to reveal their time variant features. In this paper, a new instantaneous frequency (IF) estimation method is proposed for signals with heavy noise, which is based on a polynomial chirplet transform and a ridge curve extraction scheme. Based on this method, an iterative stepwise refinement algorithm is developed to generate a time-frequency distribution (TFD) with satisfactory energy concentration. Both simulated signals and experimental vibration signals are used to validate the performance of the proposed methods. The results demonstrate that the proposed TFA method is more effective in processing the nonstationary signals with heavy noise. Further, it can perform an accurate evaluation of the IF and obtain a clear TFD.
Abstract: In this paper we present a method for the addition of integral action to nonpassive outputs of a class of port-Hamiltonian (pH) systems. The proposed integral controller is a dynamic extension, constructed from the open-loop system, such that the closed loop preserves the pH form. It is shown that the controller is able to reject the effects of both matched and unmatched disturbances, preserving the regulation of the nonpassive outputs. Previous solutions to this problem have relied on a change of coordinates whereas the presented solution is developed using the original state vector and, therefore, retains its physical interpretation. In addition, the resulting closed-loop dynamics have a natural interpretation as a control by interconnection scheme.
Autors: Joel Ferguson;Alejandro Donaire;Richard H. Middleton;
Appeared in: IEEE Transactions on Automatic Control
Abstract: Freeway bottlenecks lead to traffic congestion and speed reduction, resulting in increased risks of rear-end collision. This paper aimed to develop a control strategy of an integrated system of cooperative adaptive cruise control (CACC) and variable speed limit (VSL) to reduce rear-end collision risks near freeway bottlenecks. A microscopic simulation testbed was first constructed, in which the realistic PATH CACC models and surrogate safety measures of the time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) were used. A feedback control algorithm was then developed for the proposed vehicle to infrastructure system of CACC and VSL. The simulation results showed that the proposed integration system with 100% CACC penetration rate can reduce the rear-end collision risks effectively, with the TIT and TET declined by 98%. The average travel time was also decreased by 33%, compared with the manual vehicles without any control. Moreover, the safety improvements of the proposed integrated system are quite stable at the various bottlenecks with different magnitudes of speed reductions. The sensitivity analyses suggested that the penetration rate of CACC has significant impact on safety performance. The VSL control plays an important role in reducing rear-end collision risks when the penetration rate of CACC is low. The combination of CACC and VSL controls mitigates the negative effects of the mixed traffic flow of the manual and CACC vehicles.
Autors: Ye Li;Chengcheng Xu;Lu Xing;Wei Wang;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Abstract: This paper presents a methodology for integrated planning of real-life medium-voltage networks based on the utility planning concepts. The research is motivated by the need to develop a methodology that would line-up with utility day-to-day businesses and could be applied in real-life. Its core is a two-stage optimization process, where the first stage solves the static investment optimization and the second stage considers operational problem. A probabilistic decision tree approach is proposed for the solution of the entire problem to consider uncertainties in the planning period. The overall formulation is given first, which is followed by details of the investment model and outlines of the proposed operation planning. The novelty of the investment problem, which determines optimal network reinforcements, is explicit modeling of network security constraints of radially operated networks, whilst considering different operating regimes. Additional novel features include modeling of real-life supply restoration rules through network reconfiguration and optimal placement of new switching devices, as well as consideration of “customer flows” on the network. Connection of new distributed generation and demand centers and construction of circuits on new corridors are also included. Two investment models are formulated as mixed-integer nonlinear optimization problems, tested on several MV networks and compared with established methods. The proposed operational problem is solved in two stages, quality-of-supply and operation cost optimization. Computational aspects are also presented.
Abstract: Power systems are exceedingly faced with extreme events such as natural disasters and deliberate attacks. In comparison, the underground natural gas system is considered less vulnerable to such extreme events. We consider that the overhead power grid can be hardened by replacing segments of electric power grid with underground natural gas pipelines as an energy transportation system to countereffect extreme events which can damage interdependent infrastructures severely. In this paper, an integrated electricity and natural gas transportation system planning algorithm is proposed for enhancing the power grid resilience in extreme conditions. A variable uncertainty set is developed to describe the interactions among power grid expansion states and extreme events. The proposed planning problem is formulated as a two-stage robust optimization problem. First, the influence of extreme events representing natural disasters is described by the proposed variable uncertainty set and the proposed robust model for the integrated planning is solved with the grid resilience represented by a set of constraints. Second, the investment decisions are evaluated iteratively using the conditional events. The integrated electricity and natural gas planning options are analyzed using the modified IEEE-RTS 1979 for enhancing the power grid resilience. The numerical results point out that the proposed integrated planning is an effective approach to improving the power grid resilience.
Abstract: This paper proposes an integrated framework for wind farm maintenance that combines i) predictive analytics methodology that uses real-time sensor data to predict future degradation and remaining lifetime of wind turbines, with ii) a novel optimization model that transforms these predictions into profit-optimal maintenance and operational decisions for wind farms. To date, most applications of predictive analytics focus on single turbine systems. In contrast, this paper provides a seamless integration of the predictive analytics with decision making for a fleet of wind turbines. Operational decisions identify the dispatch profiles. Maintenance decisions consider the tradeoff between sensor-driven optimal maintenance schedule, and the significant cost reductions arising from grouping the wind turbine maintenances together—a concept called opportunistic maintenance. We focus on two types of wind turbines. For the operational wind turbines, we find an optimal fleet-level condition-based maintenance schedule driven by the sensor data. For the failed wind turbines, we identify the optimal time to conduct corrective maintenance to start producing electricity. The economic and stochastic dependence between operations and maintenance decisions are also considered. Experiments conducted on i) a 100-turbine wind farm case, and ii) a 200-turbine multiple wind farms case demonstrate the advantages of our proposal over traditional policies.
Autors: Murat Yildirim;Nagi Z. Gebraeel;Xu Andy Sun;
Abstract: Tracking multiple targets across nonoverlapping cameras aims at estimating the trajectories of all targets, and maintaining their identity labels consistent while they move from one camera to another. Matching targets from different cameras can be very challenging, as there might be significant appearance variation and the blind area between cameras makes the target’s motion less predictable. Unlike most of the existing methods that only focus on modeling the appearance and spatiotemporal cues for inter-camera tracking, this paper presents a novel online learning approach that considers integrating high-level contextual information into the tracking system. The tracking problem is formulated using an online learned conditional random field (CRF) model that minimizes a global energy cost. Besides low-level information, social grouping behavior is explored in order to maintain targets’ identities as they move across cameras. In the proposed method, pairwise grouping behavior of targets is first learned within each camera. During inter-camera tracking, track associations that maintain single camera grouping consistencies are preferred. In addition, we introduce an iterative algorithm to find a good solution for the CRF model. Comparison experiments on several challenging real-world multicamera video sequences show that the proposed method is effective and outperforms the state-of-the-art approaches.
Autors: Xiaojing Chen;Bir Bhanu;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Abstract: Boosting the resilience of power systems is one of the core requirements of smart grid. In this paper, an integrated resilience response framework is proposed, which not only links the situational awareness with resilience enhancement, but also provides effective and efficient responses in both preventive and emergency states. The core of the proposed framework is a two-stage robust mixed-integer optimization model, whose mathematical formulation is presented in this paper as well. To solve the above model, an algorithm based on the nested column-and-constraint generation decomposition is provided, and computational efficiency improvement techniques are proposed. Preventive response in this paper considers generator re-dispatch and topology switching, while emergency response includes generator re-dispatch, topology switching and load shedding. Several numerical simulations validate the effectiveness of the proposed framework and the efficiency of the solution methodology. Key findings include the following: 1) in terms of enhancing power grid resilience, the integrated resilience response is preferable to both independent preventive response and independent emergency response; 2) the power grid resilience could be further enhanced by utilizing topology switching in the integrated resilience response.
Autors: Gang Huang;Jianhui Wang;Chen Chen;Junjian Qi;Chuangxin Guo;
Abstract: This paper presents an intelligent multi-area power control with dynamic knowledge domain inference concept. The ongoing operational shift leads to unacceptable states variation, which may result in power oscillations, and if the controllers are not suitably designed, the system may be interactive and oscillations can aggravate. The study reports a new concept of updating control parameters, which is linked with operational shift, initially in an offline mode in building respective knowledge domain that fits into the framework of changing situations, to ensure states regulation. The proposed concept also provides flexibility to update the knowledge domain over and above offline data with newer dataset combining the nearest data clusters to derive an averaged data (controller parameter) within predefined boundary to change the controller functioning. The knowledge retrieval, as operational shift proceeds, has been mapped utilizing dynamical inference concept. The control so derived, effectively ensures the best damping well within time for the large network reliability and security. The structure of the controller so obtained is termed as the intelligent controller. In the present investigation, parameters of the respective controllers are stored in their respective knowledge domain on the modular basis. Firefly Algorithm (FA) with integral time multiplied by absolute error has been used as the objective function to be minimized. FA is then used to develop knowledge domain structure by way of deriving optimal controller parameters for corresponding operational shift to ensure oscillation damping with minimum settling time as well as overshoot/undershoot. The study is performed on six area sample power system. The proposed concept demonstrates an intelligent control concept for quick oscillation damping as the operating condition changes. Unified power flow controller has been used as an ancillary device as power system stabilizer approaches to the onset of unaccepta-
Abstract: Sensations elicited by electrical stimulation of touch are multidimensional, varying in perceived intensity and quality in response to changes in stimulus current or waveform timing. This paper manipulated both current and frequency, while volunteer participants estimated the dissimilarity of all non-identical pairs of 16 stimulus conditions. Multidimensional scaling analysis revealed that a model having two perceptual dimensions was adequate in representing the electrotactile (electrocutaneous) sensations. The two dimensions were identified as perceptual frequency and intensity, and were strongly correlated with the two stimulus variables, frequency and current, although not in a 1:1 correspondence. Perception of frequency differences increased monotonically with stimulus intensity, which is consistent with other human sensory systems, such as hearing and vision. Our results are consistent with previously-reported research using a different methodology and cutaneous locus. Congruence across different methods and laboratories suggests similar underlying perceptual mechanisms.
Autors: Kurt A. Kaczmarek;Mitchell E. Tyler;Uchechukwu O. Okpara;Steven J. Haase;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Abstract: A time-varying phase shift associated with each phase matching point of homogeneous weakly coupled multicore fibers is proposed to describe the stochastic time evolution of the intercore crosstalk (ICXT) observed experimentally. This model for the stochastic ICXT time evolution represents a generalization of current ICXT theoretical models and potentiates the development of new time-adaptive ICXT mitigation techniques. The model is first proposed considering a single polarization scheme, and is then generalized to a dual polarization scheme and to account for the polarization coupling between cores. Comparison between spectrograms of the crosstalk transfer function (XTTF) amplitude evaluated using the single polarization model and measured experimentally shows excellent agreement for short (few minutes) decorrelation times. For large decorrelation times (above 1 h), some differences in the behavior of the time evolution of the XTTF amplitude are observed. Nevertheless, excellent match between the mean and variance of the XTTF amplitude evaluated from the model and from analytical expressions proposed in the literature is observed for short and large decorrelation times. It is also shown that the decorrelation time of the short-term average crosstalk remains unchanged when the dual polarization scheme is considered. Similar spectrograms of the XTTF obtained with the single and dual polarization ICXT models are also shown.
Autors: Tiago M. Ferreira Alves;Adolfo V. T. Cartaxo;
Abstract: It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.
Abstract: A systematic and quantitative comparison of electrical detection systems in scanning microwave microscopy is reported. Scanning microwave microscopy (SMM) is capable of investigating nanoscale electrical properties with high accuracy over a broad frequency range of 1–20 GHz. However, due to the passive matching network only discrete frequencies can be used every 1 GHz with varying signal-to-noise ratio (SNR). Here we study in detail the impedance matching mechanism using an interferometric network where a two-port measurement is implemented with a reduction of the trace noise due to signal subtraction. The interferometer setup shows superior performance resulting in a 2–8 fold increased SNR with respect to the standard shunt solution, in addition to stable broadband performance over the full frequency range. We perform a comparison of the electrical sensitivity obtained using a direct connection from the network analyser to probe, the typically implemented shunt-resonator impedance matching network, and the proposed interferometer setup. The interferometer SMM allows us also for calibrated impedance measurements, which we demonstrate on Tobacco mosaic viruses with 18-nm diameter, with a capacitance resolution of 0.67 attoFarads at 10 ms acquisition time per pixel.
Abstract: The first results of internal solitary wave (ISW) observations over the ice-free Laptev Sea derived from 354 ENVISAT Advanced Synthetic Aperture Radar (ASAR) images acquired in May–October 2011 are reported. Analysis of the data reveals the key regions of ISW distribution that are primarily found over the outer shelf/slope regions poleward the M2 critical latitude. Most of the ISWs are observed in regions where enhanced tide-induced vertical mixing and heat fluxes have been previously reported. This suggests that spaceborne SAR observations may serve as a tool to infer local mixing hot spots over the ice-free Arctic Ocean.
Autors: Igor E. Kozlov;Evgenia V. Zubkova;Vladimir N. Kudryavtsev;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Abstract: In some situations, only a limited number of measurements under a limited number of conditions may be available for analysis. This paper describes an approach for creating additional interpolated measurements in which both measurement noise as well as signal have appropriate values. This is important, for example, when evaluating the behavior of advanced readback channels where quantities, such as sector failure rate (SFR), change very abruptly from 0% to 100% in response to relatively small parameter changes. This means that a smooth interpolation of SFR between coarse measurement points is little help in determining the actual boundary of good performance. If, instead, interpolated waveforms are fed into the channel, the boundary of the region of good performance can be clearly identified. This paper formulates a solution for the general problem of noisy measurement (waveform) interpolation and then applies this approach specifically to the situation, where a series of spin-stand waveforms were captured at various reader positions and with various written track squeeze positions (i.e., a set of “747s”). Using this approach, realistic waveforms can now be created and the SFR evaluated at any arbitrary intermediate reader and writer positions.
Abstract: The Bio-Section of this issue of the IEEE Journal of Solid-State Circuits (JSSC) includes some of the highlights of the outstanding papers from the 2017 International Solid-State Circuits Conference (ISSCC), which was held in San Francisco, CA, USA, in February 2017.
Abstract: Device-quality crystallographically oriented epitaxial (100)Ge and (110)Ge were grown on GaAs substrates using a large bandgap AlAs buffer. Electrical characteristics of p-type metal–oxide–semiconductor (pMOS) capacitors, fabricated from the aforementioned material stacks, are presented for the first time. High-resolution cross-sectional transmission electron microscopy analysis demonstrated atomically abrupt heterointerfaces between Al2O3/Ge as well as Ge/AlAs for both (100) and (110) orientations. Various process conditions were implemented during MOS capacitor fabrication to study their impact on the Al2O3/Ge interface. The fabricated pMOS devices demonstrated excellent electrical characteristics with efficient modulation of the Fermi level from midgap to the conduction band edge, corresponding to a minimum value of cmev−1 on (100)Ge, indicative of a high-quality oxide/Ge heterointerface, and an effective electrical passivation of the Ge surface. Postdeposition annealing under O2 was found to be less effective at reducing oxide trap density ( as compared to forming gas or O2 postmetallization anneals (PMA), indicating that metal-induced bandgap states at the gate metal/dielectric interface have a notable impact on Ge pMOS . On the other hand, a tradeoff must be made between and the eq-
ivalent oxide thickness when performing PMA under O2 or forming gas ambient.
Autors: Peter D. Nguyen;Michael B. Clavel;Jheng-Sin Liu;Mantu K. Hudait;
Appeared in: IEEE Transactions on Electron Devices
Abstract: Altered firing properties and increased pathological oscillations in the basal ganglia have been proven to be hallmarks of Parkinson’s disease (PD). Increasing evidence suggests that abnormal synchronous oscillations and suppression in the cortex may also play a critical role in the pathogenic process and treatment of PD. In this paper, a new closed-loop network including the cortex and basal ganglia using the Izhikevich models is proposed to investigate the synchrony and pathological oscillations in motor circuits and their modulation by deep brain stimulation (DBS). Results show that more coherent dynamics in the cortex may cause stronger effects on the synchrony and pathological oscillations of the subthalamic nucleus (STN). The pathological beta oscillations of the STN can both be efficiently suppressed with DBS applied directly to the STN or to cortical neurons, respectively, but the underlying mechanisms by which DBS suppresses the beta oscillations are different. This research helps to understand the dynamics of pathological oscillations in PD-related motor regions and supports the therapeutic potential of stimulation of cortical neurons.
Autors: Meili Lu;Xile Wei;Kenneth A. Loparo;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Abstract: In this paper, a new shaded-pole main exciter (ME) with additional short-circuited coils for aircraft three-stage starter–generator (SG) is proposed and investigated. The basic structure, winding configurations, operating principle, and start system structure of the presented shaded-pole ME are illustrated in detail. The comparative study between the original ME and the shaded-pole ME with respect to the starting mode performances is conducted by 2-D finite-element method (FEM). A prototype SG with original ME has been developed, and the experimental results are essentially consistent with the simulation results by the FEM utilized in the predictions in this paper. Simulation data and waveforms verify that the proposed shaded-pole ME is a good candidate for aircraft machines to satisfy the dual function of starter and generator.
Abstract: The sheet beam relativistic extended interaction oscillator (REIO) is a very important high-power millimeter-wave source for many actual and potential applications. A Ka-band sheet beam REIO is designed by means of particle-in-cell (PIC) simulation. In the design, we adopt a sheet electron beam with dimensions of 45 mm mm to reduce the space charge effect and the extended interaction cavities to increase the power capacity. The results of the PIC simulation demonstrate the device can generate an output power of 404 MW at 30 GHz with an efficiency of 20%. In addition, we develop the experiment on a short-pulse accelerator. In the experiment, the oscillator generates a millimeter-wave power of 125 MW with a beam current of 4 kA, a beam voltage of 500 kV, and guiding magnetic field of 1 T. The frequency of the output millimeter wave is 30.6 GHz and the pulsewidth is 16 ns. The experiment proves that millimeter wave of over 100 MW can be generated with the sheet beam REIO.
Abstract: From a new stator-flux perspective, a comparative study between the series and parallel hybrid excitation machine (PHEM) is conducted and it is revealed that in PHEMs there still exist distinct stator-flux harmonic components during high-speed flux weakening operation, which could be further utilized to improve the torque capability at high-speed range. Inspired by this idea, an auxiliary winding is creatively introduced into PHEMs to recycle and utilize the magnetic field energy generated during the field regulation. A new design case is presented in this paper, in which two sets of armature windings with different pole pair numbers are arranged to realize the function of flux weakening operation and energy recycling, respectively. The feasibility of this new hybrid solution is evaluated by using the finite-element analysis. Furthermore, a prototype is manufactured and relevant experiments are performed. The experimental results agree well with the theoretical analysis and simulation results, which verify that the recycled energy can be effectively used to boost the output torque and power of PHEMs in the high-speed region.
Abstract: Electrical current measurement by a giant magnetoimpedance (GMI) sensor may require the sensitive element (amorphous wire) to be aligned with the magnetic field produced by the conductor (toroidal configuration), which involves a bending stress. In this paper, a first study is made to investigate the impact of bending stress on a GMI sensor. For practical GMI sensor implementation, the offset and intrinsic sensitivity are crucial parameters. This is why these quantities have been evaluated in both diagonal and off-diagonal configurations. A Co-rich amorphous wire (from Unitika Ltd.) of diameter and 15 cm length was used. The off-diagonal voltage was measured through a pick-up coil. The wire was bent over a cylinder with a radius of 2.5 cm. The excitation frequency was 800 kHz. In the diagonal configuration, the sensitivity at a given bias field was decreased by 50% in the bent position compared to the straight position. The offset also decreased by 25%. In the off-diagonal configuration, the sensitivity around zero decreased by about 28%. The offset stayed quasi-null during the test. These results showed that the off-diagonal configuration seems to be best suited for an application as a current sensor that involves bending. The reversibility and repeatability of the bending effect have been evaluated under ten successive bending stresses. It was shown that the effect is quite reversible and repetitive.
Abstract: Applicability of copper–carbon nanotube (Cu-CNT) composites as on-chip global VLSI interconnects is investigated comprehensively. Electrical modeling of Cu-CNT composite interconnects is carried out by virtue of effective complex conductivity. The performances, including time delay and step response, are characterized based on the equivalent circuit model. Finally, the crosstalk effect between coupled Cu-CNT composite interconnects is analyzed.
Abstract: The degradation mechanism of Ti/Pt/Au ohmic contacts to p-GaAs was identified experimentally under high direct-current density stress in detail. A revised measuring structure was designed based on the circular transfer length method (CTLM), in which the high current density of A/cm2 was applied vertically, while the contact resistance was measured horizontally between two contact electrodes. According to revised CTLM, the specific contact resistance was measured during stress. The results indicated that specific contact resistance showed an exponential dependence on the aging time. The depth profiling results obtained from the Auger electron spectroscopy showed that Pt penetrated into the Au layer during stress. Furthermore, some voids were observed at the Au/Pt interface, and intermixing began to form within metal layer during stress. These results demonstrated that the degradation of Ti/Pt/Au ohmic contacts to p-GaAs was attributed mainly to the electromigration and Joule heating along the current direction under high current density.
Abstract: The recent development of some high-power THz vacuum electronic devices calls for the application of space filters such as frequency-selective surfaces (FSSs) and polarization dividers. This paper presents the comparative study of two types of FSSs for a THz gyromultiplier output system, one with high-pass characteristic while the other one with low-pass functionality. Both FSSs are designed, fabricated, and experimentally tested between 200 and 1600 GHz to verify their capability of separating the dual-frequency output from the gyromultiplier. The high-power operation capability of the FSSs is also characterized by taking both the corona discharge and volumetric breakdown into consideration at the frequencies of interest. Based on the comparative study of the performance, the fabrication challenge and the high-power capability between the two FSSs, a generalized conclusion is given regarding the choice of the FSSs for high-power THz application.
Abstract: Space-division multiplexing in multimode fibers is a very promising approach to overcome the shortcoming of capacity in long-haul optical transmission systems. In this paper, we present an analysis of different mode representations in multimode fibers. We resume the properties and the interrelations of linearly polarized and vectorial modes. We take a look at the coupled nonlinear Schrödinger equation and Manakov equations for strongly coupled mode groups. The nonlinear coupling coefficient of the Manakov equation is investigated for both mode bases, in order to verify if the approximated linearly polarized modes are a valid representation for the analysis of nonlinearities in space-division multiplexed systems. Even though the effective mode areas differ considerably between LP- and vector modes, the simulated coupling coefficient shows a good agreement between both models. The results indicate that the mode basis does not affect the nonlinear parameter. For the analysis the field distributions of the modes are numerically calculated with a vector finite difference modesolver. Finally the simulated results are verified analytically.
Abstract: The self-heating effects (SHEs) in gate-all-around (GAA) MOSFETs with vertically stacked silicon nanowire (SiNW) channels are investigated. Direct observations using thermal images, electrical proof measurements, and supportive numerical simulations are carried out to verify the SHEs. This paper examines the location of hot spots as well as heat dissipation paths (heat sink) depending on the device geometry, and the electrical degradation produced by the SHEs. It also includes the estimation of the surface temperature of the GAA MOSFET and the average temperature across the bulk channel. Design parameters for improved management of the heat dissipation in a device are suggested. This investigation can contribute to improve the device performance and reliability of a 3-D stacked structure.
Autors: Jun-Young Park;Byung-Hyun Lee;Ki Soo Chang;Dong Uk Kim;Chanbae Jeong;Choong-Ki Kim;Hagyoul Bae;Yang-Kyu Choi;
Appeared in: IEEE Transactions on Electron Devices
Abstract: This letter describes a method of correcting ionospheric frequency modulation for a high-frequency hybrid sky-surface wave radar mounted on a shipborne platform. In the proposed method, azimuth-dependent sea clutter signals are first decomposed into monocomponent signals based on distinguishable differences in their directions of incidence. Afterward, based on the decomposed monocomponent signals, the statistical mean of the time derivatives of the signal phases, weighted by the signal amplitudes, is used to estimate the ionospheric frequency modulation. Finally, the estimated result is applied to the received data to compensate for the ionospheric contamination. Numerical results on simulated data demonstrate the effectiveness of the proposed algorithm.
Autors: Yongpeng Zhu;Yinsheng Wei;Lei Yu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Abstract: Recently, novel magnetic materials have been developed for high-efficiency and high power density electric motors. In addition, next-generation semiconductor devices, like silicon carbide (SiC) or gallium nitride (GaN), have been introduced for power converters due to their high-frequency operation. Therefore, high-frequency operation of new magnetic materials is possible when they are driven by GaN or SiC inverters. Nevertheless, iron loss characterization of magnetic materials when they are excited by high-frequency signals have not been conducted yet. This paper introduces the iron losses characterization of a magnetic material at high carrier frequency excitation using a GANFET inverter. This characterization was carried out by the experimental evaluation of iron losses at carrier frequencies from 5 to 500 kHz at different deadtimes. As a result of the measurements, iron losses seem to have a trend to increase at high carrier frequencies and large deadtimes. In addition, filtering is introduced and it seems to be an effective technique for reducing iron losses.
Abstract: In this paper, the investigation is focused on the iron loss prediction for electrical machines fed by low switching frequency inverter. An improved iron loss model is developed after reviewing various existing iron loss models considering pulse-width modulation (PWM) influence. In order to validate the improved iron loss model, iron loss tests are carried out on an electrical machine. The predicted iron loss results match well with the measured results, which shows that the improved iron loss model is able to predict iron loss in electrical machine fed by an inverter. The comparison between the predicted iron losses with and without considering the PWM influence shows that the iron loss can be significantly increased due to the influence of PWM, especially when the switching frequency is low.
Abstract: In this paper, the temperature dependencies of iron loss under different flux densities, frequencies, and dc bias flux densities are systematically investigated. The temperature dependence of the hysteresis loss varies significantly with the dc bias flux density while that of the eddy current loss is independent of the dc bias flux density. Based on these different characteristics of the hysteresis and the eddy current iron losses, an improved iron loss model is developed. The temperature dependence of iron loss under dc bias condition can be considered by utilizing the improved iron loss model. The developed iron loss model is validated by both tests on laminations and an electrical machine.
Abstract: This paper presents the results of experimental trials carried out on a permanent magnet synchronous motor (PMSM) that uses a stator core made of a nanocrystalline magnetic material (FINEMET). It is demonstrated that the manufactured stator can reduce the PMSM total iron loss by 64% to 75% compared with an equivalent motor using a stator made of conventional non-oriented silicon steel. The experimental results are confirmed by 2-D finite-element analysis.
Autors: Nicolas Denis;Masaki Inoue;Keisuke Fujisaki;Hiromitsu Itabashi;Tomoaki Yano;
Abstract: This paper puts forward the design and analysis of an ironless permanent magnet machine for a micro wind power application. The proposed methodology includes comprehensive geometric, magnetic, and electrical dimensioning followed by detailed 2-D finite-element modeling of a synchronous generator. The configuration investigated in this paper shows the generators rotor fixed in the tip of the blades and illustrates the advantages of a large diameter for a microgeneration application.
Autors: Valdirene Verdum;Roberto P. Homrich;Aly F. Flores Filho;David G. Dorrell;
Abstract: The Russians launched the first artificial Earth satellite, Sputnik 1, into an elliptical low-Earth orbit (LEO) in October 1957. Through its four external antennas, Sputnik 1 broadcast radio beacons at 20.005 and 40.01 MHz to study the density of the atmosphere and the radio-wave propagation through the ionosphere. This historic event represents the advent of the satellite age. Since then, satellites have become an integral part of global navigation, Earth observation, broadcasting, and communication systems. The latter complements conventional wired and wireless terrestrial communication and provides an effective platform to relay radio signals between two arbitrary points on or near the Earth. Satellite communication offers end users a high level of flexibility. Irrespective of the geological coordinate, the user can benefit from a broad spectrum for various applications, from two-way voice and data communication to video conferencing.
Abstract: Inside, it's brightly lit and filled with humming machinery, a mammoth futuristic manufactory. Robot arms grab components from bins and place each part with precision, while conveyor belts move the assembled pieces smoothly down production lines. Finished products enter testing stations for quality checks before being packed for shipping. It has been called a gigafactory, and it does indeed produce vast quantities of advanced batteries. But this gigafactory is in China, not Nevada. It doesn't make batteries for cars, and it's not part of the Elon Musk empire.
Abstract: An indisputable fact cannot be rebutted. It is supported by theory and experience. Over the past 25 years, wind and solar generation has undergone dramatic growth, resulting in a variety of experiences that model the integration of wind and solar into the planning and operation of modern electric power systems. In this article, we bring together examples from Europe, North America, and Australia to identify five indisputable facts about planning and operating modern power systems. Taken together, we hope these experiences can help build consensus among the engineering and public policy communities about the current state of wind and solar integration and also facilitate conversations about evolving future challenges.
Abstract: Because of the explosion in data growth, the requirement for high-density storage systems has increased. Bit-patterned media recording (BPMR) is a candidate for the next-generation magnetic recording systems, and its many advantages facilitate the achievement of recording densities of 1 Tb/in2 and beyond. In BPMR, each information bit is represented by a magnetic island; however, due to the small spacings between the along- and across-track islands that are for the achievement of a high areal density, severe extents of the inter-symbol interference and inter-track interference appear. These error factors degrade the system performance of the recording system. In this paper, an iterative channel detection scheme with a low-density parity check (LDPC) product code for which the extrinsic information between the soft output Viterbi algorithm and the LDPC product code is used for the BPMR is proposed. For the improvement of the BPMR performance, the modified extrinsic information data are exploited.
Abstract: In compressive sensing (CS) of images or videos, a block-based sensing or recovery scheme can facilitate low-cost sampling or recovery in memory and computation. However, its recovery with small block size and small subrate suffers greatly from its lack of information of the measurement data essential to recover a unique solution among many candidates. This study, based on prior knowledge of the signal to be sensed, namely, the relative magnitude difference of signal entries, designs a weighting process to limit the solution space of the recovered signal and combines it with much simplified Landweber iterations to deliver a complete recovery algorithm, called iterative weighted recovery (IWR). We theoretically verify the performance of the proposed IWR, including error bound, convergence rate, and stopping criterion. Application of the proposed IWR to block-based CS of images or videos confirms the quality improvement of the recovered images or videos and reduction of recovery time.
Autors: Khanh Quoc Dinh;Byeungwoo Jeon;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Abstract: In this paper, we develop wireless-powered device-to-device (D2D) communications underlaying a time-division duplex cellular network, where D2D users (DUs) coexist with cellular users (CUs) and harvest energy from a base station during the downlink time for sustaining communications during the uplink time. Two spectrum access modes, coexistence and hybrid, are considered for the DUs. Our goal is to maximize the sum rate of the DUs by jointly designing beamforming and time allocation as well as DU transmit power, while maintaining the quality-of-service for the CUs. In a single DU scenario, the joint design problems in the downlink and uplink are decoupled and solved in sequence. By doing so, the optimal downlink beamforming is found via a semi-definite relaxation (SDR) approach. From a DU power control perspective, a scheme is proposed for obtaining the optimal solution of the remaining uplink design in the coexistence and hybrid modes. For a scenario with multiple DUs, a converted SDR problem is considered to attain the optimal solution of the original problem when the uplink receive beamforming is appropriately predetermined to null out the DU interference. We present simulation results to quantify the impact of various network parameters on the performance of the proposed schemes.
Autors: Meng-Lin Ku;Jyun-Wei Lai;
Appeared in: IEEE Transactions on Wireless Communications
Abstract: Impulsive noise is one key factor that limits the performance of underwater acoustic (UA) communications. In this paper, two pilot-subcarrier based algorithms are proposed to improve the performance of channel estimation and impulsive noise mitigation for UA orthogonal frequency-division multiplexing (OFDM) systems. The first algorithm jointly estimates the channel and the impulsive noise based on the least-squares principle. The second algorithm is developed with the aim to reduce the computational complexity, where the expectation-maximization principle is applied to estimate the channel and the impulsive noise iteratively. We compare the proposed algorithms by simulations and apply them to process the data collected during an experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that both proposed algorithms have better performance than existing methods in mitigating impulsive noise in UA OFDM systems.
Abstract: Combined with a quickest detection algorithm for error propagation prevention in joint channel decoding and state estimation, a decoding procedure based on Pearl’s belief propagation is proposed to exploit the redundancy of system states in time domain for cyber-physical systems. By applying the proposed scheme to a linear model of electric generator dynamic system, numerical simulations have demonstrated that a better performance of state estimation will be obtained by the joint channel decoding and state estimation, and the error propagation can be successfully eliminated by the error propagation detection algorithm during the state estimation process.
Autors: Shuping Gong;Liang Li;Ju Bin Song;Husheng Li;
Appeared in: IEEE Transactions on Wireless Communications
Abstract: A multiuser secure broadcast system is considered, where there are one multiantenna base station (BS), multiple single-antenna legitimate users, one multiantenna friendly jammer (FJ), and one multiantenna eavesdropper (Eve). We jointly design the optimal precoding matrix at the BS and the jamming covariance matrix at the FJ by minimizing the total transmit power of the BS and FJ under the signal-to-interference-plus-noise ratio constraints at the users and Eve. To solve this challenging problem, when the FJ has more antennas than the users and Eve, we first find the optimal structure of the jamming covariance matrix and, then, convert the problem into its equivalent convex form. Also, we propose an iterative algorithm to jointly design the precoding and jamming covariance matrices in all scenarios. The solution obtained by this algorithm is shown to be asymptotically optimal when the FJ has more antennas than the users and Eve. Numerical results show that the proposed schemes considerably outperform the existing schemes.
Abstract: Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients.
Abstract: In this paper, we consider the energy-bandwidth allocation for a network of multiple users, where the transmitters each powered by both an energy harvester and conventional grid, access the network orthogonally on the assigned frequency band. We assume that the energy harvesting state and channel gain of each transmitter can be predicted for time slots a priori. The different transmitters can cooperate by donating energy to each other. The tradeoff among the weighted sum throughput, the use of grid energy, and the amount of energy cooperation is studied through an optimization objective, which is a linear combination of these quantities. This leads to an optimization problem with O() constraints, where is the total number of transmitter–receiver pairs, and the optimization is over seven sets of variables that denote energy and bandwidth allocation, grid energy utilization, and energy cooperation. To solve the problem efficiently, an iterative algorithm is proposed by using the Proximal Jacobian alternating direction method of multipliers (ADMM). The optimization subproblems corresponding to Proximal Jacobian ADMM steps are solved in the closed form. We show that this algorithm converges to the optimal solution with an overall complexity of O(). Numerical results show that the proposed algorithms can make efficient use of the harvested energy, grid energy, energy cooperation, and the available bandwidth.
Autors: Vaneet Aggarwal;Mark R. Bell;Anis Elgabli;Xiaodong Wang;Shan Zhong;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: This paper investigates a joint source-channel secrecy problem for the Shannon cipher broadcast system. We suppose list secrecy is applied, i.e., a wiretapper is allowed to produce a list of reconstruction sequences and the secrecy is measured by the minimum distortion over the entire list. For discrete communication cases, we propose a permutation-based uncoded scheme, which cascades a random permutation with a symbol-by-symbol mapping. Using this scheme, we derive an inner bound for the admissible region of secret key rate, list rate, wiretapper distortion, and distortions of legitimate users. For the converse part, we easily obtain an outer bound for the admissible region from an existing result. Comparing the outer bound with the inner bound shows that the proposed scheme is optimal under certain conditions. Besides, we extend the proposed scheme to the scalar and vector Gaussian communication scenarios, and characterize the corresponding performance as well. For these two cases, we also propose another uncoded scheme, orthogonal-transform-based scheme, which achieves the same performance as the permutation-based scheme. Interestingly, by introducing the random permutation or the random orthogonal transform into the traditional uncoded scheme, the proposed uncoded schemes, on one hand, provide a certain level of secrecy, and on the other hand, do not lose any performance in terms of the distortions for legitimate users.
Autors: Lei Yu;Houqiang Li;Weiping Li;
Appeared in: IEEE Transactions on Information Theory
Abstract: In this correspondence, a downlink cooperative nonorthogonal multiple access transmission scheme is considered in the multicarrier scenario, where the user equipment (UE) with strong channel conditions acts as a relay to help the UE with weak channel conditions. A joint optimization of subcarrier pairing and power allocation is formulated as a mixed-integer nonconvex problem, with the objective to minimize the transmit power of the base station and the relay (strong UE) under the quality of service requirements of both UEs. We first explore the inherent property of power allocation for a single subcarrier pair. Then, in light of the property, we employ the Lagrange dual method and the Hungarian algorithm, in an asymptotically optimal manner, to solve the joint subcarrier pairing and power allocation problem. Numerical results show that our proposed algorithm outperforms other schemes with or without cooperation.
Autors: Xunan Li;Chong Li;Ye Jin;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: In this paper, we consider the problems of minimizing sum power and maximizing sum rate for multicell networks with load coupling, where coupling relation occurs among cells due to intercell interference. This coupling relation is characterized by the signal-to-interference-plus-noise ratio (SINR) coupling model with cell load vector and cell power vector as the variables. Due to the nonlinear SINR coupling model, the optimization problems for multicell networks with load coupling is nonconvex. To solve these nonconvex problems, we first consider the optimization problems for single-cell networks. Through variable transformations, the optimization problems can be equivalently transformed into convex problems. By solving the Karush–Kuhn–Tucker, the optimal solutions to power minimization and rate maximization problems can be obtained in closed form. Based on the theoretical findings of optimization problems for single-cell networks, we develop a distributed time allocation and power control algorithm with low complexity for the sum power minimization in multicell networks. This algorithm is proved to be convergent and globally optimal by using the properties of standard interference function. For sum rate optimization in multicell networks, we also provide a distributed algorithm that yields suboptimal solution. Besides, the convergence for this distributed algorithm is proved. Numerical results illustrate the theoretical findings, showing the superiority of our solutions compared to the conventional solution of allocating uniform power for users in the same cell.
Abstract: In this paper, we focus on heterogeneous features learning for RGB-D activity recognition. We find that features from different channels (RGB, depth) could share some similar hidden structures, and then propose a joint learning model to simultaneously explore the shared and feature-specific components as an instance of heterogeneous multi-task learning. The proposed model formed in a unified framework is capable of: 1) jointly mining a set of subspaces with the same dimensionality to exploit latent shared features across different feature channels, 2) meanwhile, quantifying the shared and feature-specific components of features in the subspaces, and 3) transferring feature-specific intermediate transforms (i-transforms) for learning fusion of heterogeneous features across datasets. To efficiently train the joint model, a three-step iterative optimization algorithm is proposed, followed by a simple inference model. Extensive experimental results on four activity datasets have demonstrated the efficacy of the proposed method. A new RGB-D activity dataset focusing on human-object interaction is further contributed, which presents more challenges for RGB-D activity benchmarking.
Abstract: Thermal sensor noise has a great impact on the efficiency and effectiveness of a dynamic thermal management (DTM) strategy. To address the problem of forecasting temperature based on noisy thermal sensors, we first propose a Kalman-based runtime thermal prediction scheme. To obtain accurate temperature predictions, a multivariate linear power model and a physically-based state space thermal model for 3-D network-on-chip are also proposed. Simulation results show that it reduces the standard deviations of the prediction error by 46%–53% compared with the auto-regressive based one under sensor noise with . Conventional reactive DTM techniques suffer from significant performance degradation due to their pessimistic reaction, thus, based on the proposed prediction scheme, we further propose a proactive DTM strategy that primarily consists of a thermal-aware routing algorithm and a proactive throttling scheme: 1) to take into account both thermal and congestion issues, we propose a proactive congestion and thermal aware routing algorithm. Simulation results demonstrate that it can achieve better throughput as well as approach better thermal balance. Specifically, under uniform traffic, the proposed scheme reduces the maximum chip temperature by about 3.9 °C and achieves 78.3% higher throughput compared with the competing thermal optimization approach based on dynamic programming network and 2) when the temperature exceeds the threshold, existing coarse-grained reactive throttling schemes cool down the overheated nodes at the penalty of significant performance loss. In this paper, a proactive quota-based throttling scheme is proposed. Simulation results show that it improves the throughput up to 11.1% compared with the reactive throttling schemes.
Autors: Yuxiang Fu;Li Li;Kun Wang;Chuan Zhang;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Abstract: The critical dimension (CD) is highly influenced by the reactive ion etching (RIE) of silicon in the CMOS technology. The CD has to be well-controlled since it is one of the most important features related to process stability and product quality. However, the RIE process involves a lot of parameters which are highly confounded and entangled and thus it is very difficult to analyze the process. To study and extract the influences of these parameters in terms of CD variation, screening experiments are carried out to obtain the necessary factors to develop a CD-related model. An elaborated model, based on the selected parameters, is then built up via applying the design of experiments and response surface optimization. This model is validated to be capable of characterizing the process as well as predicting the CD.
Autors: Maria Rizquez;Agnès Roussy;Jakey Blue;Laurent Bucelle;Jacques Pinaton;Julien Pasquet;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Abstract: This paper proposes a novel kinetic velocity model (KVM) for the drift-diffusion (DD) transport approach to describe ballistic effects. It also presents a simulation study of the ballistic effect in short-channel InGaAs and silicon FETs. Monte Carlo and subband Boltzmann transport equation results as well as DD simulations using the simple gate length-dependent ballistic mobility proposed in the literature and the KVM model are compared and discussed. Basic concepts, such as the Matthiessen rule and Fermi-Dirac statistics, are analyzed with a view on ballistic transport in devices in the linear and saturation regimes.
Abstract: The modern aircraft has evolved to become an important part of our society. Its design is multidisciplinary in nature and is characterized by complex analyses of mutually interdependent disciplines and large search spaces. Machine learning has, historically, played a significant role in aircraft design, primarily by approximating expensive physics-based numerical simulations. In this work, we summarize the current role of machine learning in this application domain, and highlight the opportunity of incorporating recent advances in the field to further its impact. Specifically, regression models (or surrogate models) that represent a major portion of the current efforts are generally built from scratch assuming a zero prior knowledge state, only relying on data from the ongoing target problem of interest. However, due to the incremental nature of design processes, there likely exists relevant knowledge from various related sources that can potentially be leveraged. As such, we present three relatively advanced machine learning technologies that facilitate automatic knowledge transfer in order to improve design performance. Subsequently, we demonstrate the efficacy of one of these technologies, i.e. transfer learning, on two use cases of aircraft engine design yielding noteworthy results. Our aim is to unveil this new application as a well-suited arena for the salient features of knowledge transfer in machine learning to come to the fore, thereby encouraging future research efforts.
Autors: Alan Tan Wei Min;Ramon Sagarna;Abhishek Gupta;Yew-Soon Ong;Chi Keong Goh;
Appeared in: IEEE Computational Intelligence Magazine
Abstract: Recovering dynamic 3D structures from 2D image observations is highly under-constrained because of projection and missing data, motivating the use of strong priors to constrain shape deformation. In this paper, we empirically show that the spatiotemporal covariance of natural deformations is dominated by a Kronecker pattern. We demonstrate that this pattern arises as the limit of a spatiotemporal autoregressive process, and derive a Kronecker Markov Random Field as a prior distribution over dynamic structures. This distribution unifies shape and trajectory models of prior art and has the individual models as its marginals. The key assumption of the Kronecker MRF is that the spatiotemporal covariance is separable into the product of a temporal and a shape covariance, and can therefore be modeled using the matrix normal distribution. Analysis on motion capture data validates that this distribution is an accurate approximation with significantly fewer free parameters. Using the trace-norm, we present a convex method to estimate missing data from a single sequence when the marginal shape distribution is unknown. The Kronecker-Markov distribution, fit to a single sequence, outperforms state-of-the-art methods at inferring missing 3D data, and additionally provides covariance estimates of the uncertainty.
Autors: Tomas Simon;Jack Valmadre;Iain Matthews;Yaser Sheikh;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Abstract: A highly sensitive hybrid plasmonic slot-waveguide (HPSW) biosensor based on silicon-on-insulator is proposed and analyzed for DNA hybridization detection. The reported design is based on increasing the light interaction with the sensing region by using slot waveguide with plasmonic material. Due to the high index contrast and plasmonic effect, an ultrahigh optical confinement is achieved in the low-index regions, which enables the detection of the smallest change in the analyte refractive index with high sensitivity. The normalized power confinement, power density, and effective index of the supported modes by the HPSW are analyzed to achieve high-power confinement through the suggested biosensor and hence high sensitivity can be obtained. The HPSW is also incorporated with straight slotted resonator to calculate the sensitivity of the proposed design. The simulation results are calculated using full vectorial finite element method. The reported biosensor has high sensitivity of 1890.4 nm/RIU (refractive index unit), which is the highest in the literature to the best of our knowledge with a detection limit of 2.65 × 10 –6 RIU.
Autors: Mohamed Farhat O. Hameed;Ahmed Samy Saadeldin;Essam M. A. Elkaramany;Salah S. A. Obayya;
Abstract: Accurate inversion of land surface temperature (LST) from remote sensing data is an essential and challenging topic for earth observation applications. This paper successfully retrieves the LST from FY-3C/VIRR data with split-window method. With the simulated data, the algorithm coefficients are acquired with root mean square errors lower than 1.0 K for all subranges when view zenith angle (VZA) < 30° and the water vapor content (WVC) < 4.25 g/cm2 , as well as those in which the VZA < 30° and the LST < 307.5 K. In addition, a detailed sensitivity analysis is carried out. The analysis result indicates that the total LST uncertainty caused by the standard error of the algorithm, the uncertainties of land surface emissivity and WVC, and the instrument noise would be 1.22 K and 0.94 K for dry and wet atmosphere, respectively. Furthermore, LST retrieval method is applied to the visible and infrared radiometer measurements over the study area covering the geographical latitude of 31.671°N to 44.211°N and longitude of 10.739°W to 1.898°E, and the derived LST is cross-validated with Terra/MODIS LST product. The preliminary validation result shows that the split-window method determines the LST within 2.0 K for vegetation and soil areas.
Abstract: Monitoring chlorophyll-a concentration (Chl-a) in inland waters, particularly hypertrophic lake waters in megacities, is a critically important environmental issue. To enable long-term Chl-a monitoring using Landsat series sensors, development of a Chl-a estimation algorithm for the new Landsat sensor is requisite. This study aims to identify the most accurate algorithm for Chl-a estimation in hypertrophic waters using Landsat 8 images and in situ Chl-a data from West Lake and nine other hypertrophic lakes in Hanoi (Vietnam's capital). The best estimation was obtained by the ratio of two reflectances at 562 and 483 nm, corresponding to the ratio of the OLI band 3 versus band 2, termed the GrB2 algorithm. The GrB2 values using the reflectances of water samples and the Landsat images were correlated with the Chl-a by an exponential function (r2 = 0.64 to 0.82), and the estimated Chl-a were verified by the smallness of standard error (smaller than 10%) and degree of conformity with recent fish-kill phenomena that commonly occur in those lakes in summer and early spring. Because the availability of GrB2 is limited to waters with low levels of inorganic suspended matter, its extension to waters with much higher levels requires further investigation.
Abstract: Given a timed automaton modeling an implementation and a timed automaton as a specification, the problem of language inclusion checking is to decide whether the language of is a subset of that of . It is known to be undecidable. The problem gets more complicated if non-Zenoness is taken into consideration. A run is Zeno if it permits infinitely many actions within finite time. Otherwise it is non-Zeno. Zeno runs might present in both and . It is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as counterexamples of language inclusion checking. In this work, we propose a zone-based semi-algorithm for language inclusion checking with non-Zenoness. It is further improved with simulation reduction based on LU-simulation. Though our approach is not guaranteed to terminate, we show that it does in many cases through empirical study. Our approach has been incorporated into the PAT model checker, and applied to multiple systems to show its usefulness.
Abstract: We investigated the magnetic properties of NiFe2O4(NFO) epitaxial films grown on MgAl2O4(MAO) substrates by the reactive radio frequency magnetron sputtering method. The films were found to be coherently distorted to at least 61 nm thickness because of the lattice mismatch between MAO and NFO. The NFO(001) films exhibited large negative uniaxial anisotropy that can be quantitatively explained by the magneto-elastic theory despite the lattice distortion being as much as 3%. We also discovered magnetic anomalies in both the saturation magnetization and anisotropy of the thinnest film, which may because of the reconstruction of the electronic structures at NFO interfaces.
Abstract: Test quality is critical to eliminate test escapes and to achieve high-reliability large-scale integrated (LSI) devices. This paper proposes a new concept called “physical test coverage” to verify test coverage based on the physical layout of LSI circuits. The physical test coverage is calculated as the ratio between the critical area of all wires in a device and that of wires undetected by LSI tests. From the critical area of undetected wires and the defect density of a manufacturing line, the risk of test escapes can be predicted. To effectively develop LSI tests that can minimize the number of test patterns, undetected wires are prioritized by the critical area related to each wire. Even when the conventional “logical” test coverage is high enough to satisfy the coverage criterion, some LSI devices investigated in this paper showed low physical test coverage depending on the physical layout of the LSI circuit. The concept of physical coverage was applied in the test development of some LSI products, and the test quality was substantially improved, such that 90% of test escapes of a device were eliminated.
Abstract: This paper starts from a review on the progress in fabrication of piezoelectric ceramic coatings by thermal spray method. For our experimental work, two types of lead-free piezoelectric ceramic coatings, including potassium-sodium niobate-based and bismuth sodium titanate-based, are fabricated by thermal spray process, and their structure, morphology, and piezoelectric properties are characterized. Our obtained lead-free ceramic coatings exhibit single phase of perovskite structure, relatively dense morphology, and competitive piezoelectric coefficients. The mechanism of forming the piezoelectric perovskite crystalline phase by thermal spray involving melting-recrystallization process is analyzed in comparison to that of ceramic synthesis through solid-state reaction. Suppression of volatile loss and decomposition at high temperature due to the extremely high melting and cooling rate in the thermal spray process, and the impact on the resulting structure are discussed. Significant advantages of the thermal spray method over alternative processing methods for forming piezoelectric ceramic coatings are summarized. The combination of environmentally friendly lead-free compositions and the scalable thermal spray processing method will promote more applications of piezoelectric ceramic coatings for producing distributive sensors and transducers, and forming advanced smart structures and systems.
Autors: Kui Yao;Shuting Chen;Kun Guo;Chee Kiang Ivan Tan;Meysam Sharifzadeh Mirshekarloo;Francis Eng Hock Tay;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Abstract: A continuous–discontinuous Gakerkin time domain method (CDGTD) with vector basis functions is proposed to analyze the wideband response of plasmonic structures with the Drude dispersive model. Compared to the conventional time domain approaches, such as FDTD and PSTD, the unstructured mesh can provide a better geometrical approximation of curved surfaces and fine features. An EB scheme Riemann solver is employed to calculate the flux between adjacent subdomains. The relationship between the electric field and the polarization currents is modeled by a first order auxiliary differential equation (ADE). A leap-frog scheme is proposed to update Maxwell's equations, the ADEs of the Drude medium and the perfectly matched layer (PML) in an efficient manner. This new approach is validated by virtue of simulating the ultra-wideband behavior of a gold nanoloop antenna with and without a substrate as well as the reflectivity of a dual-band infrared absorber. Its advantage in computational cost is demonstrated via comparison to a commercial software package. In this light, the CDGTD method represents a more efficient forward modeling tool, which has been successfully employed here to perform a parametric study of a dual-band infrared absorber.
Autors: Qiang Ren;Yusheng Bian;Lei Kang;Pingjuan L. Werner;Douglas H. Werner;
Abstract: This paper deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised classification as a basis for automatic map generation. Recently, deep convolutional neural networks (CNNs) have shown impressive performance and have quickly become the de-facto standard for semantic segmentation, with the added benefit that task-specific feature design is no longer necessary. However, a major downside of deep learning methods is that they are extremely data hungry, thus aggravating the perennial bottleneck of supervised classification, to obtain enough annotated training data. On the other hand, it has been observed that they are rather robust against noise in the training labels. This opens up the intriguing possibility to avoid annotating huge amounts of training data, and instead train the classifier from existing legacy data or crowd-sourced maps that can exhibit high levels of noise. The question addressed in this paper is: can training with large-scale publicly available labels replace a substantial part of the manual labeling effort and still achieve sufficient performance? Such data will inevitably contain a significant portion of errors, but in return virtually unlimited quantities of it are available in larger parts of the world. We adapt a state-of-the-art CNN architecture for semantic segmentation of buildings and roads in aerial images, and compare its performance when using different training data sets, ranging from manually labeled pixel-accurate ground truth of the same city to automatic training data derived from OpenStreetMap data from distant locations. We report our results that indicate that satisfying performance can be obtained with significantly less manual annotation effort, by exploiting noisy large-scale training data.
Abstract: Modeling how contextual factors relate to a software system’s configuration space is usually a manual, error-prone task that depends highly on expert knowledge. Machine-learning techniques can automatically predict the acceptable software configurations for a given context. Such an approach executes and observes a sample of software configurations within a sample of contexts. It then learns what factors of each context will likely discard or activate some of the software’s features. This lets developers and product managers automatically extract the rules that specialize highly configurable systems for specific contexts.
Autors: Paul Temple;Mathieu Acher;Jean-Marc Jézéquel;Olivier Barais;
Abstract: Due to the efficiency and effectiveness of hashing technologies, they have become increasingly popular in large-scale image semantic retrieval. However, existing hash methods suppose that the data distributions satisfy the manifold assumption that semantic similar samples tend to lie on a low-dimensional manifold, which will be weakened due to the large intraclass variation. Moreover, these methods learn hash functions by relaxing the discrete constraints on binary codes to real value, which will introduce large quantization loss. To tackle the above problems, this paper proposes a novel unsupervised hashing algorithm to learn efficient binary codes from high-level feature representations. More specifically, we explore nonnegative matrix factorization for learning high-level visual features. Ultimately, binary codes are generated by performing binary quantization in the high-level feature representations space, which will map images with similar (visually or semantically) high-level feature representations to similar binary codes. To solve the corresponding optimization problem involving nonnegative and discrete variables, we develop an efficient optimization algorithm to reduce quantization loss with guaranteed convergence in theory. Extensive experiments show that our proposed method outperforms the state-of-the-art hashing methods on several multilabel real-world image datasets.
Autors: Lei Ma;Hongliang Li;Fanman Meng;Qingbo Wu;King Ngi Ngan;
Abstract: Query auto-completion (QAC) is widely used by modern search engines to assist users by predicting their intended queries. Most QAC approaches rely on deterministic batch learning algorithms trained from past query log data. However, query popularities keep changing all the time and QAC operates in a real-time scenario where users interact with the search engine continually. So, ideally, QAC must be timely and adaptive enough to reflect time-sensitive changes in an online fashion. Second, due to the vertical position bias, a query suggestion with a higher rank tends to attract more clicks regardless of user’s original intention. Hence, in the long run, it is important to place some lower ranked yet potentially more relevant queries to higher positions to collect more valuable user feedbacks. In order to tackle these issues, we propose to formulate QAC as a ranked Multi-Armed Bandits (MAB) problem which enjoys theoretical soundness. To utilize prior knowledge from query logs, we propose to use Bayesian inference and Thompson Sampling to solve this MAB problem. Extensive experiments on large scale datasets show that our QAC algorithm has the capacity to adaptively learn temporal trends, and outperforms existing QAC algorithms in ranking qualities.
Abstract: Accurately classifying roadway surface disruptions (RSDs) plays a crucial role to enhance quality transportation and road safety. To this end, smartphones are becoming an ad hoc tool to collect road data, while the user is at the steering wheel. In this paper, for the first time, sensed data are represented with a novel technique inspired in the bag of words representation. New results suggest that segments of accelerometer readings play a key role to characterize different classes of events, boosting classification performance. A novel data collection process was conducted in real-life environments, where the smartphones were freely placed at five user-surveyed locations, within a fleet of cars and trucks. To the best of our knowledge, this is the largest and most heterogenous data set for RSDs, and we make it publicly available. We approach the problem of identifying RSDs as one of supervised learning, where we contrast representative classifiers, most of them not previously reported. We exhaustively evaluated the performance of all classifiers in six data sets, most of them resembling actual data sets used in similar projects. We found that in all cases, the best classifier outperforms the best results reported so far. The proposed methodology was extensively evaluated through a sensitivity analysis to determine the relevance of the parameters. Experimental results reveal that the representation technique boosts considerably the classification performance when compared with the state of the art solutions, reducing in one order of magnitude the false-positives/negatives rate and surpassing the classification accuracy for about 10% in a multiclass data set.
Autors: Luis C. González;Ricardo Moreno;Hugo Jair Escalante;Fernando Martínez;Manuel Ricardo Carlos;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Abstract: Jamming is a typical attack by exploiting the nature of wireless communication. Lots of researchers are working on improving energy-efficiency of jamming attack from the attacker’s view. Whereas, in the low-duty-cycle wireless sensor networks where nodes stay asleep most of time, the design of jamming attack becomes even more challenging especially when considering the stochastic transmission pattern arising from both the clock drift and other uncertainties. In this paper, we propose LearJam, a novel learning-based jamming attack strategy against low-duty-cycle networks, which features the two-phase design consisting of the learning phase and attacking phase. Then in order to degrade the network throughput to the maximal degree, LearJam jointly optimizes these two phases subject to the energy constraint. Moreover, such process of optimization is operated iteratively to accommodate the requirement of practical implementation. Conversely, we also discuss how the state-of-the-art mechanisms can defend against LearJam, which will aid the researchers to improve the security of low-duty-cycle networks. Extensive simulations show that our design achieves significantly higher number of successful attacks and reduces the network’s throughput considerably, especially in a sparse low-duty-cycle network, compared with some typical jamming strategies.
Autors: Zequ Yang;Peng Cheng;Jiming Chen;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Abstract: Line resistance reduction in interconnects was achieved through Cu microstructure modulation. The modulation was performed via both raising annealing temperature and reducing the post-patterning dielectric aspect ratio and resulted in a bamboo-like Cu microstructure. Compared with the conventional polycrystalline, the modulated Cu microstructure also presents a lower resistivity increase rate with area scaling. A TaN stress control layer deposited on over-plated Cu surface was demonstrated to be critical for maintaining the Cu interconnect integrity after the high-temperature anneal.
Abstract: Motivated by recent work on stochastic gradient descent methods, we develop two stochastic variants of greedy algorithms for possibly non-convex optimization problems with sparsity constraints. We prove linear convergence1 in expectation to the solution within a specified tolerance. This generalized framework is specialized to the problems of sparse signal recovery in compressed sensing and low-rank matrix recovery, giving methods with provable convergence guarantees that often outperform their deterministic counterparts. We also analyze the settings, where gradients and projections can only be computed approximately, and prove the methods are robust to these approximations. We include many numerical experiments, which align with the theoretical analysis and demonstrate these improvements in several different settings.
Linear convergence is sometimes called exponential convergence.
Autors: Nam Nguyen;Deanna Needell;Tina Woolf;
Appeared in: IEEE Transactions on Information Theory
Abstract: In this paper, we characterize the linear degrees of freedom (DoF) of a cellular network in which the base station (BS) operates in a full-duplex (FD) mode and the users operate in a half-duplex mode. We assume that the BS and the users are equipped with reconfigurable antennas which can be switched between their preset modes. We consider two practical scenarios for different assumptions on channel state information at the transmit sides (CSIT), referred to as no CSIT and partial CSIT models. To derive the inner-bounds for two scenarios, we propose a new achievable scheme which enables interference alignment between uplink and downlink interference signals at each user via preset mode switching of reconfigurable antennas. The key concept of our scheme is to align the interference signals of uplink transmission at the downlink users, through the identical preset mode pattern over the multiple of downlink transmission periods and silence periods of the BS. We also develop an outer-bound on the linear sum DoF of the cellular network for the no CSIT model, which matches up with the inner-bound. Moreover, we also provide a natural variant of the proposed scheme when considering residual self-interference at the FD BS, which can alleviate the shortcoming of the existing self-interference cancellation techniques.
Autors: Heecheol Yang;Wonjae Shin;Jungwoo Lee;
Appeared in: IEEE Transactions on Wireless Communications
Abstract: Equipment productivity in semiconductor manufacturing has become a major topic due to high equipment prices. It is easier and more precise to calculate productivity based on the running logs; however, engineers may often be assigned to estimate the productivity of the equipment in the design phase to predict project benefits so that investment decisions can be made. In such situations, no running log is available to calculate equipment productivity. If the architecture of the equipment and the wafer flow are simple, equipment productivity still can be evaluated using algebra-based solutions. Unfortunately, with rapidly shrinking IC dimensions equipment architecture becomes more and more complicated so a linear platform is typically used. In a linear platform, multiple mainframes are used to install more chambers. In each main-frame, there may be multiple robots to enable efficient wafer transmission. It is very difficult to estimate the productivity of a linear platform using simple algebra-based solutions; however, accurate productivity estimation of a linear platform is critical due to its higher price. To address this problem, a novel estimative methodology is proposed in this paper. This method analyzes the potential wait time of a chamber and then identifies the productivity bottleneck of the platform. The proposed methodology is designed for calculating wafers per hour for the linear platform. The accuracy of the proposed methodology is then verified by a simulation model. By applying this methodology to estimate the productivity for a semiconductor manufacturing line incorrect equipment investment can be reduced, therefore enhancing market competitiveness.
Autors: Kai-Ting Yang;Li-Jen Ko;Hsiang-Yin Shen;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Abstract: In this paper, an amplify-and-forward two-way relay (TWR) precoding is designed with no source node (SN) processing in order to maximize sum rate and concurrently reduce the network latency and signaling overhead. For the arbitrary pre-/postprocessing at the SNs that have antennas, it is rigorously shown that an -by- optimal TWR precoder matrix is symmetric when the noise power of the TWR node is relatively small compared with that of the SNs and/or each of the channel matrices is spatially orthogonal. Using the symmetric structure of the TWR precoding matrix, a constrained nonlinear-multivariable optimization problem is formulated that can be solved with polynomial time complexity. Furthermore, a closed-form optimal TWR precoding matrix is designed for a TWR system with . When compared with an optimal joint SN and RN precoding method, it is verified that the proposed precoding method provides a good tradeoff between the system complexity and sum rate performance.
Autors: Jingon Joung;Jihoon Choi;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: A linear programming (LP)-based framework is presented for obtaining converses for finite blocklength lossy joint source-channel coding problems. The framework applies for any loss criterion, generalizes certain previously known converses, and also extends to multi-terminal settings. The finite blocklength problem is posed equivalently as a nonconvex optimization problem and using a lift-and-project-like method, a close but tractable LP relaxation of this problem is derived. Lower bounds on the original problem are obtained by the construction of feasible points for the dual of the LP relaxation. A particular application of this approach leads to new converses, which recover and improve on the converses of Kostina and Verdú for finite blocklength lossy joint source-channel coding and lossy source coding. For finite blocklength channel coding, the LP relaxation recovers the converse of Polyanskiy, Poor and Verdú and leads to a new improvement on the converse of Wolfowitz, showing thereby that our LP relaxation is asymptotically tight with increasing blocklengths for channel coding, lossless source coding, and joint source-channel coding with the excess distortion probability as the loss criterion. Using a duality-based argument, a new converse is derived for finite blocklength joint source-channel coding for a class of source-channel pairs. Employing this converse, the LP relaxation is also shown to be tight for all blocklengths for the minimization of the expected average symbolwise Hamming distortion of a -ary uniform source over a -ary symmetric memoryless channel for any . The optimization formulation and the lift-and-project method are extended to networked settings and demonstrated -
y obtaining an improvement on a converse of Zhou et al. for the successive refinement problem for successively refinable source-distortion measure triplets.
Autors: Sharu Theresa Jose;Ankur A. Kulkarni;
Appeared in: IEEE Transactions on Information Theory
Abstract: In a previous paper, we discussed wireless strain sensors, based upon the effect, employing a number of different field-annealed amorphous ribbons as resonators and transducers. In this paper, we present results for a polycrystalline (Fe0.8Al0.2)98B2 alloy as the transducer and either Metglas 2826MB3 or Beijing Yeke 1K501 as the resonator. Frequency variation curves and tensile stress tests were performed on the sensors. The FeAlB–amorphous alloys ensemble resulted in a linear behavior through a larger deformation amplitude than previously obtained. Gauge factors of up to 190 were obtained over a deformation amplitude of at least 300 ppm. The results are discussed in the light of the magnetization behavior of the materials involved.
Autors: Eduardo S. Bastos;Alessandro Dalponte;Frank P. Missell;Guilherme O. Fulop;Mateus B. de Souza Dias;Cristina Bormio-Nunes;
Abstract: An optically enhanced Fabry–Perot etalon was demonstrated to accurately measure the refractive index of sugar solutions. The etalon consisted of two silver/SiO2-coated glass substrates separated by a spacer. The semi-transparent silver films of ~15-nm thickness greatly enhanced the interference of light. The SiO2 layer coated on the silver created a hydrophilic surface in addition to protecting the silver from oxidation. The hydrophilic behavior of the SiO2 films together with a capillary action allowed the tested liquids to easily flow into and wet the cavity between the two pieces of glass. Optical spectrophotometer was used to measure the transmission spectra of the etalon with and without a sugar solution. The refractive indices of sugar solutions with different brix concentrations were subsequently determined from the interference peak positions. The results showed a linear response of the refractive index to the brix concentration with a ratio of refractive index per brix%, making the etalons promising for analyzing specific chemicals in liquids.
Abstract: Source and mask optimization (SMO) is an important lithographic resolution enhancement technology. Recently, some research indicate that the lithography performance is sensitive to the errors of an actual lithography system, such as thermal aberration, thick mask effects, and mask uncertainties. Most of the errors would result in uncertain wavefront aberration, so the reduction of aberration sensitivity means the improvement of lithography stability. In this paper, we propose a low aberration sensitivity SMO (LASSMO) method to improve robustness of lithography performance against uncertain aberration. To reduce the aberration sensitivity, we build the LASSMO model via innovating new cost function including sensitivity penalty terms. Aiming at spherical aberration and coma, this method is demonstrated using two target patterns with critical dimensions of 45 nm. Taking into account the statistic characteristics of uncertain aberration, we use the normalized stochastic gradient descent algorithm to establish an iterative optimization framework. The simulation results show the benefit of LASSMO method in both high pattern fidelity and the low sensitivity of lithography imaging to aberration.
Abstract: You've never heard of Littelfuse? Do you drive a car or truck? Do you watch TV or use a laptop computer or a mobile device? Do you use a washing machine or dryer for clothes, or do you adjust the temperature in your home? Assuming your answer is ?yes? to any or all of these questions, then you have and continue to use Littelfuse products on a daily basis.
Abstract: This paper shows the generation of a local oscillator (LO) signal for cellular transceivers by means of a phase-locked loop and a phase interpolator (PI) digital-to-time converter (DTC). The PI-DTC allows arbitrary frequency shifts over a wide range. We derive a closed-form description of the spurs in the spectrum of the LO signal caused by quantization and nonlinear effects for the PI-DTC. Furthermore, we show the existence of a new class of spurs generated due to noise processes in the PI. Measurement and simulation results are in good agreement with our closed-form solution.
Autors: Peter Preyler;Christoph Preissl;Stefan Tertinek;Tobias Buckel;Andreas Springer;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Abstract: In this letter, we study the mobile user recruitment problem for mobile crowdsensing systems. Instead of minimizing the overall sensing cost or user utility, this letter aims to optimize the load balancing of the mobile users, which is particularly important for the resource-constrained individual user. We refer to such a problem as the load balanced mobile user recruitment (LB-MUR) problem. Specifically, we first formulate the LB-MUR problem as a mixed integer linear programming (LP) and prove that it is NP-hard. Then an efficient polynomial-time suboptimal algorithm is proposed, which is based on LP relaxation. Furthermore, we derive the approximation ratio of the proposed algorithm. Finally, we evaluate the effectiveness of the proposed scheme through simulations.
Abstract: This letter proposes a novel multiview feature extraction method for supervised polarimetric synthetic aperture radar (PolSAR) image classification. PolSAR images can be characterized by multiview feature sets, such as polarimetric features and textural features. Canonical correlation analysis (CCA) is a well-known dimensionality reduction (DR) method to extract valuable information from multiview feature sets. However, it cannot exploit the discriminative information, which influences its performance of classification. Local discriminant embedding (LDE) is a supervised DR method, which can preserve the discriminative information and the local structure of the data well. However, it is a single-view learning method, which does not consider the relation between multiple view feature sets. Therefore, we propose local discriminant CCA by incorporating the idea of LDE into CCA. Specific to PolSAR images, a symmetric version of revised Wishart distance is used to construct the between-class and within-class neighboring graphs. Then, by maximizing the correlation of neighboring samples from the same class and minimizing the correlation of neighboring samples from different classes, we find two projection matrices to achieve feature extraction. Experimental results on the real PolSAR data sets demonstrate the effectiveness of the proposed method.
Abstract: Linear discriminant analysis (LDA) is a popular technique for supervised dimensionality reduction, but with less concern about a local data structure. This makes LDA inapplicable to many real-world situations, such as hyperspectral image (HSI) classification. In this letter, we propose a novel dimensionality reduction algorithm, locality adaptive discriminant analysis (LADA) for HSI classification. The proposed algorithm aims to learn a representative subspace of data, and focuses on the data points with close relationship in spectral and spatial domains. An intuitive motivation is that data points of the same class have similar spectral feature and the data points among spatial neighborhood are usually associated with the same class. Compared with traditional LDA and its variants, LADA is able to adaptively exploit the local manifold structure of data. Experiments carried out on several real hyperspectral data sets demonstrate the effectiveness of the proposed method.
Autors: Qi Wang;Zhaotie Meng;Xuelong Li;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Abstract: Most existing fingerprints-based indoor localization approaches are based on some single fingerprint, such as received signal strength (RSS), channel impulse response, and signal subspace. However, the localization accuracy obtained by the single fingerprint approach is rather susceptible to the changing environment, multipath, and non-line-of-sight propagation. In this paper, we propose a novel localization framework by Fusing A Group Of fingerprinTs (FAGOT) via multiple antennas for the indoor environment. We first build a GrOup Of Fingerprints (GOOF), which includes five different fingerprints, namely, RSS, covariance matrix, signal subspace, fractional low-order moment, and fourth-order cumulant, which are obtained by different transformations of the received signals from multiple antennas in the offline stage. Then, we design a parallel GOOF multiple classifiers based on AdaBoost (GOOF-AdaBoost) to train each of these fingerprints in parallel as five strong multiple classifiers. In the online stage, we input the corresponding transformations of the real measurements into these strong classifiers to obtain independent decisions. Finally, we propose an efficient combination fusion algorithm, namely, MUltiple Classifiers mUltiple Samples (MUCUS) fusion algorithm to improve the accuracy of localization by combining the predictions of multiple classifiers with different samples. As compared with the single fingerprint approaches, our proposed approach can improve the accuracy and robustness of localization significantly. We demonstrate the feasibility and performance of the proposed algorithm through extensive simulations as well as via real experimental data using a Universal Software Radio Peripheral platform with four antennas.
Autors: Xiansheng Guo;Nirwan Ansari;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: Power dissipation during scan testing of a system-on-chip can be significantly higher than that during functional mode, causing reliability and yield concerns. This paper proposes a logic cluster controllability (LoCCo)-based scan chain stitching methodology to achieve low-power testing. The scan chain stitching is made power aware by placing flip-flops with higher test combination requirements at the beginning of scan chains, while flip-flops with lower test combination requirements are put toward the end of scan chains. The test combination requirements are estimated through a simple logic cluster and flip-flop controllability identification algorithm. This method helps in consolidating care bits toward the beginning of scan chains. Hence, a significantly lower shift-in transition is achieved in the test patterns. The results from ITC’99 and industrial designs in 28FDSOI and 40-nm CMOS technologies show a total shift-in transition reduction of up to 23.1% and average shift power reduction of up to 21.6% using the proposed method. The use of LoCCo methodology posed a negligible routing congestion overhead in the layout compared to the conventional method. LoCCo is also used as a base to apply other vector reordering low-power methods and gain reduced computation time with almost similar power reduction as achieved by Bonhomme et al. independently.
Abstract: Energy and battery lifetime constraints are critical challenges to IC designs. Stacked power-domain implementation, which connects voltage domains in series, can effectively improve power delivery efficiency and thus improve battery lifetime. However, such an approach requires balanced currents between different domains across multiple operating scenarios. Furthermore, level shifter insertion, along with placement constraints imposed by power domain regions, can incur significant power and area penalties. To the best of our knowledge, no existing work performs subblock-level partitioning optimization for stacked-domain designs. In this paper, we present an optimization framework for stacked-domain designs. Based on an initial placement solution, we apply a flow-based partitioning that is aware of multiple operating scenarios, cell placement, and timing-critical paths to partition cells into two power domains with balanced cross-domain current and minimized number of inserted level shifters. We further propose heuristics to define regions for each power domain so as to minimize placement perturbation, as well as a dynamic programming-based method to minimize the area cost of power domain generation. In an updated floor plan, we perform matching-based optimization to insert level shifters with minimized wirelength penalty. Overall, our method achieves an excellent current balance across stacked domains with less than 10% discrepancy, which results in up to more than battery lifetime improvements.
Autors: Kristof Blutman;Hamed Fatemi;Ajay Kapoor;Andrew B. Kahng;Jiajia Li;José Pineda de Gyvez;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Abstract: This paper investigates the loss and temperature field distributions of a consequent-pole hybrid excited vernier machine (CPHEVM) with dc field windings embedded between the modulating poles. The time-stepping finite-element method is utilized to analyze the losses in consideration of rotating magnetic flux excitation. A 3-D coupled fluid heat transfer model totally packaged in a large air region is established based on the finite volume method to obtain precise temperature rise distribution. A 12-slot/70-pole CPHEVM, which has high torque density and good flux-weakening capability, is taken as an example to reveal the variation patterns of loss and temperature rise under different dc excitations.
Abstract: This paper describes a highly efficient method for lossless compression of volumetric sets of medical images, such as CTs or MRIs. The proposed method, referred to as 3-D-MRP, is based on the principle of minimum rate predictors (MRPs), which is one of the state-of-the-art lossless compression technologies presented in the data compression literature. The main features of the proposed method include the use of 3-D predictors, 3-D-block octree partitioning and classification, volume-based optimization, and support for 16-b-depth images. Experimental results demonstrate the efficiency of the 3-D-MRP algorithm for the compression of volumetric sets of medical images, achieving gains above 15% and 12% for 8- and 16-bit-depth contents, respectively, when compared with JPEG-LS, JPEG2000, CALIC, and HEVC, as well as other proposals based on the MRP algorithm.
Autors: Luís F. R. Lucas;Nuno M. M. Rodrigues;Luis A. da Silva Cruz;Sérgio M. M. de Faria;