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With the proliferation of portable devices, the exponential growth of the global mobile traffic brings great challenges to the traditional communication networks and the traditional wireless communication technologies. In this context, converged networks and cache-based data offloading have drawn more and more attention based on the strong correlation of services. This paper proposes a novel popular services pushing and caching scheme by using converged overlay networks. The most popular services are pushed by terrestrial broadcasting networks. And they are cached in ${n}$ router-nodes with limited cache sizes. Each router-node only interconnects with its neighbor nodes. Users are served through the router’s WiFi link. If the services requested are cached in the routers, the user can be immediately responded; otherwise, the requests can be responded through the link from cellular stations to the router. In the proposed scheme, the cache size of the router, the maximum number of requests each router can serve, and the whole-time delay are limited. Three node-selecting and dynamic programming algorithms are adopted to maximize the equivalent throughput. Analytical and numerical results demonstrate that the proposed scheme is very effective. [ABSTRACT FROM AUTHOR]

For airborne-phased array radar systems, space-time adaptive processing (STAP) is supposed to be a crucial technique for improving target detection performance in the strong clutter background. However, practical application environments are always heterogeneous and have offered a severe challenge to the implementation of STAP. To address this reality, a data-dependent reduced dimension STAP approach based on sparse recovery (SR) is proposed in this paper. To take a full account of the heterogeneous environments, we consider the extremely heterogeneous case in which only one single snapshot is available. There is no doubt that, compared with the clutter covariance matrix (CCM) calculated directly by a single snapshot, the SR technique can provide a more accurate estimate. However, we should come to realize that this estimation is not accurate enough to adaptive processing according to the presented simulation results in lots of literature, and it has been demonstrated that the performance of traditional SR-based STAP degrades dramatically when only a snapshot is available. In the proposed approach, the CCM estimated by SR technique is utilized to design the reduced dimension transformation matrix rather than to calculate adaptive weights as the traditional SR-based STAP. The relatively accurate CCM can provide better support for the design of reduced dimension transformation matrix. From the simulation results, the proposed approach can achieve great performance of clutter suppression and target detection with only a single snapshot compared with several typical STAP algorithms. It is worthwhile pointing out that the proposed approach can also be applied when multiple snapshots are available and the performance improves with increasing number of available snapshots. [ABSTRACT FROM AUTHOR]

For the high-performance microwave component and system design, besides electromagnetic (EM) physics domain, we also need to consider the operation of the real-world multiphysics (MP) environment that contains the effects of other physics domains. EM-centric MP analysis and design optimization become very important. In this article, for the first time, we develop a novel parallel EM-centric multiphysics optimization (MPO) technique. In our proposed technique, the pole/residue-based transfer function is exploited to build an effective and robust surrogate model. A group of modified quadratic mapping functions is formulated to map the relationships between pole/residues of the transfer function and the design variables. Multiple EM-centric MP evaluations are performed in parallel to generate the training samples for establishing the surrogate model. Using our proposed technique, the surrogate model can be valid in a relatively large neighborhood, which makes an effective and large optimization update in each optimization iteration. The trust region algorithm is performed to guarantee the convergence of the proposed MPO algorithm. Our proposed MPO technique takes a small number of iterations to obtain the optimal EM-centric MP response. Two microwave filter examples are used to demonstrate the validity of the proposed technique. [ABSTRACT FROM AUTHOR]

A switched-capacitor interleaved bidirectional dc–dc converter that combines a three-phase interleaved structure with switched-capacitor cells is proposed. The converter features a wide voltage-gain range, low-current ripple on the low-voltage side, low voltage stresses across power switches, an absolute common ground between input and output, and can be easily extended into a topology family. The operating principle and power switch voltage and current stresses are analyzed in detail. An 800 W prototype with a wide voltage-gain range (Uhigh = 400 V, Ulow = 30–100 V) is described, demonstrating a maximum efficiency of 95.8% in the step-up mode and 95.9% in the step-down mode. [ABSTRACT FROM AUTHOR]

High-frequency (HF) ocean radar has the potential to observe sea ice, but this application has not been thoroughly investigated. In this article, we explore sea ice observation with HF radar (HFR) and develop a corresponding signal processing procedure. We derived sea ice radial velocities from raw HFR data and determined angular positions using the MUltiple SIgnal Classification (MUSIC) algorithm. Sea ice velocities were evaluated by comparison with measurements from moored acoustic Doppler current profilers (ADCPs) and a drifting buoy. The root-mean-square (rms) differences between the sea ice velocities obtained by HFR and the ADCPs decreased with increasing radar signal-to-noise ratio (SNR), implying that a high SNR was associated with accurate measurement of sea ice velocity. These results agree with previous validations of HFR ocean current observations. The sea ice pattern mapped by HFR is consistent with the simultaneous C-band microwave radar observations. In particular, the HFR captured the approach of the sea ice edge toward the coast. Sharp attenuation of the HF signal over high concentration sea ice resulted in missing and/or low-SNR data at ranges beyond the front edge of pack ice, in qualitative agreement with model estimates of attenuation. [ABSTRACT FROM AUTHOR]

Spatial modulation is an efficient transmission scheme for RF-chain limited MIMO systems. In this paper, we design a beam-switching based spatial modulation for mmWave MIMO uplink systems. At user side, a power iteration based algorithm is proposed to generate spatial symbols under the constant modulus constraint. With the generated spatial codebook, the optimal transmission mode is determined. At base station side, a round-robin path selection algorithm is proposed to select paths that are separated in angle of arrival. Inter-user interference is then suppressed by constraining the power of the received spatial symbols over selected paths only. Finally, ordered successive interference cancelation is applied to further reduce interference among users. Numerical results show that the proposed beam-switching based spatial modulation is superior to transmission over the strongest propagation path and is able to yield a satisfactory error performance in mmWave MIMO uplink. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel layered physical layer security model, which is the extension of the traditional physical layer security to the domain of multiple-layer information security. It has a hierarchical information security structure that every transmitted message has a security level, while every user has a security clearance. Users can only decode the messages with security levels lower than or equal to their clearance, otherwise they will be deemed as eavesdroppers. Based on the framework of the layered information security and assuming perfect channel state information of all users, an artificial-noise-aided optimal beamforming scheme is proposed to minimize the total transmit power at the base station, while satisfying the minimum secrecy rate requirements of all secret messages. Due to the intrinsical complexity of the formulated nonconvex problem, a safe and convex reformulation based on the first-order Taylor series expansion method is proposed to generate a tractable approximation. A successive convex approximation-based algorithm is then proposed, which solves a series of second-order cone problems with convergence to the stationary point of the original problem. We also consider the imperfect channel state information case, and then propose a worst-case robust design to overcome the influence of channel uncertainties. Semi-definite relaxation method and S-procedure are utilized to get a computationally efficient lower bound of the intractable power minimization problem. Moreover, we investigate the application of the suboptimal zero-forcing-based beamforming scheme in the system to tradeoff the achievable performance and the computational complexity. Simulation results are provided to demonstrate the effectiveness of our proposed schemes. [ABSTRACT FROM AUTHOR]

Siamese networks are prevalent in person re-identification (re-id) tasks to address the similarity and dissimilarity among video frames. It mainly focuses on the inter-video variation between spatio-temporal features extracted from different videos, while the variation between features of the same video has been rarely discussed. In this paper, we introduce the concept of “mean-body” and define an intra-video loss to address the variation between spatio-temporal features of the same video. A novel loss is presented to boost the training of the re-id networks by combining the proposed intra-video loss and the Siamese loss. Specifically, the intra-video loss uses the unique mean-body of each camera viewpoint to make the video sequence more clustered, while the Siamese loss is to make the wrong matching videos more separated. To train the whole network, we update the network and the mean-body in an iterative manner. As a result, the proposed loss is expected to improve the generalization capability of the re-id networks on the testing set. Extensive results demonstrate that the presented approach outperforms the state-of-the-art algorithms on the publicly available data sets, such as PRID2011, iLIDS-VID, and MARS, in terms of re-id accuracy. [ABSTRACT FROM AUTHOR]

Existing indoor semantic recognition schemes are capable of discovering patterns through smartphone sensing; however, there is a lack of a device-free indoor semantic recognition system. In this paper, we propose WiFiMap+, which is a first-ever automatical inference system using WiFi signals to recognize high-level indoor semantics from human activities and environments, where the high-level indoor semantics consist of indoor facilities and environments. To characterize the static indoor environments and dynamical human activities separately with channel state information (CSI), we propose a novel two-stream architecture to generate the spatial streams and the movement streams independently. Compared to the recent research on activity recognition, this two-stream architecture can make the content area of CSI samples extend from human activities to indoor environments. For obtaining accurate indoor environment detection, we propose a CSI-environment model with a spatial stream generation algorithm, which can reduce the effect of human activities on environment detection. For stable activity recognition, we also propose an environment-based testing sample representation method, which can utilize the environment knowledge to overcome the diversity of CSI caused by the environment changes. Finally, we implement WiFiMap+ using commercial WiFi devices and evaluate its performance for seven common semantic detection cases in six-room scenarios. The experimental results show that our proposed WiFiMap+ is robust to the multi-room scenario and can achieve the average accuracy of $\text{92.8}\%$ and the lowest accuracy of about $\text{82}\%$. [ABSTRACT FROM AUTHOR]

Frequency-modulated continuous waveform signals are of great interest in automotive radar, perimeter radar, and wide-area surveillance radar applications. For automotive radars and wide-area surveillance radars, which generally utilize high Doppler frequency resolution for target recognition, the important potential target such as a walking person cannot be viewed as a point-like target due to different velocities of the reflection points of a pedestrian. The echoes of such targets have extended Doppler spectrum, and they appear as horizontal lines in the range-Doppler plane, rather than a single point considered in the traditional cases. However, the existing approaches do not make full use of the Doppler-spread characteristic to enhance the detection performance of pedestrians. In this paper, we will show how this characteristic can be used to enhance the detection performance for Doppler-spread targets. The main goal of this paper is pedestrian detection in wide-surveillance radar applications and the proposed approach can also be applied in automotive radar applications. Motivated by the Hough transform, the energies of most Doppler bins corresponding to the target will be accumulated to enhance the detection performance. The questions of how many and which cells should be accumulated in practical applications are discussed in detail. The proposed approach is based on the ordered statistical-constant false alarm rate but tailored to Doppler-spread targets. The detection performance of this algorithm is derived analytically, and verified via practical wide-area surveillance radar signals. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for video-based person re-identification using multiple convolutional neural networks (CNNs). Unlike the previous work, we intend to extract a compact yet discriminative appearance representation from several frames rather than the whole sequence. Specifically, given a video, the representative frames are selected based on the walking profile of consecutive frames. A multiple CNN architecture incorporated with feature pooling is proposed to learn and compile the features of the selected representative frames into a compact description about the pedestrian for identification. Experiments are conducted on benchmark data sets to demonstrate the superiority of the proposed method over existing person re-identification approaches. [ABSTRACT FROM AUTHOR]

Despite the recent advances on intelligent fault diagnosis of rolling element bearings, existing research works mostly assume training and testing data are drawn from the same distribution. However, due to variation of operating condition, domain shift phenomenon generally exists, which results in significant diagnosis performance deterioration. To address cross-domain problems, latest research works preferably apply domain adaptation techniques on marginal data distributions. However, it is usually assumed that sufficient testing data are available for training, that is not in accordance with most transfer tasks in real industries where only data in machine healthy condition can be collected in advance. This paper proposes a novel cross-domain fault diagnosis method based on deep generative neural networks. By artificially generating fake samples for domain adaptation, the proposed method is able to provide reliable cross-domain diagnosis results when testing data in machine fault conditions are not available for training. The experimental results suggest that the proposed method offers a promising approach for industrial applications. [ABSTRACT FROM AUTHOR]

In distributed generation, grid-connected and islanded modes are essential, but usually they have different control cores to satisfy their respective control targets. Transferring between the cores may therefore lead to prominent disturbances, if the cores are complex and noticeably different in structures. To introduce seamlessness, some techniques have been recommended, but they usually lack unification of control blocks for the front dc–dc converter and rear dc–ac inverter. Moreover, when connected to the grid, some seamless techniques do not control the grid current directly. Hence, its dynamics may be slow, in addition to distortion caused by grid-voltage harmonics. When islanded, most techniques also use two control loops to regulate a drooped voltage across local loads. This double-loop structure works fine, but it has more state variables to change during a transfer of modes, which may not be as seamless. An alternative technique has thus been proposed here, whose purpose is to identify a simple unified control core, which will remain unchanged during the mode transfer. The transfer may then be viewed as a normal change of power reference, instead of an internal change of control structure. Hence, seamless operation may be ensured, as it is tested in simulations and experiments. These tests have additionally shown that the proposed scheme can regulate the grid current directly when connected to the grid, without compromising the droop-voltage regulation when islanded. [ABSTRACT FROM AUTHOR]

Polypropylene has great potential as a thermoplastic insulation material for high voltage direct current (HVDC) cable. However, its mechanical properties restrict its application, particularly at low temperature. In this paper, isotactic polypropylene (iPP) with the β-nucleating agent WBG was prepared by the melt blending method. The crystallinity, β-crystal proportion and crystalline morphology were analyzed by wide-angle X-ray diffraction, differential scanning calorimetry, scanning electron microscopy and polarized optical microscopy. The results showed that the crystallinity and β-crystal proportion increased as the WBG concentration increased. Three types of β-crystal morphology, namely β-spherulite, flower-like agglomerate and β-quasi-spherulite, were sequentially obtained with increasing WBG concentration. The mechanical properties, space charge distribution, thermally stimulated discharge current and DC electrical breakdown strength were investigated. Compared with pure iPP, the Izod impact strength and DC breakdown strength of iPP/0.1%WBG were improved by 238 and 16%, respectively, and the fracture energy and brittleness temperature of iPP/0.3%WBG were improved by 420 and 80%, respectively. In addition, the space charge accumulation was suppressed in the range of 0.1–0.5 wt% WBG. Chain coupling between the β-crystals and the amorphous phase, particularly in the flower-like agglomerates, was considered to play an important role in improving the mechanical and electrical performance. [ABSTRACT FROM AUTHOR]

Conventional insulated gate bipolar transistor (IGBT) current sensing and protection techniques usually employ discrete sensors, such as lossy shunt resistors, and may involve accessing the high-voltage collector load of the IGBT. This would normally present difficulties for integration. This paper presents an IGBT gate driver IC with a collector current sensing circuit and an on-chip CPU for local data processing. This IC is prototyped using a TSMC 0.18 μm 40 V BCD Gen-2 process. The collector current sensing technique is based on the unique Miller plateau relationship between the gate current and collector current ($I_{C}$ and $I_{G}$) for a particular gate resistance ($R_{G}$). It allows a cycle-by-cycle measurement of IC during both turn-on and turn-off transients without any extra discrete components. The temperature variation is compensated internally by the on-chip CPU using polynomial curve fitting. This technique only monitors the low-voltage signal at the gate terminal, without the need to handle any high-voltage signal on the collector/load side. Measurements using a double pulse test setup show an accuracy of ±0.5 A over the current ranges of 1–30 A for turn-on and 1–50 A for turn-off from 25 to 75 °C. [ABSTRACT FROM AUTHOR]

Location-based social media have been extensively utilized in the concept of “social sensing” to exploit dynamic information about human activities, yet joint uses of social sensing and remote sensing images are underdeveloped at present. In this paper, the close relationship between the number of Twitter users and brightness of nighttime lights (NTL) over the contiguous United States is calculated and geotagged tweets are then used to upsample a stable light image for 2013. An associated outcome of the upsampling process is the solution of two major problems existing in the NTL image, pixel saturation, and blooming effects. Compared with the original stable light image, digital number (DN) values of the upsampled stable light image have larger correlation coefficients with gridded population (0.47 versus 0.09) and DN values of the new generation NTL image product (0.56 versus 0.52), i.e., the Visible Infrared Imaging Radiometer Suite day/night band image composite. In addition, total personal incomes of states are disaggregated to each pixel in proportion to the DN value of the pixel in the NTL images and then aggregate by counties. Personal incomes distributed by the upsampled NTL image are closer to the official demographic data than those distributed by the original stable light image. All of these results explore the potential of geotagged tweets to improve the quality of NTL images for more accurately estimating or mapping socioeconomic factors. [ABSTRACT FROM AUTHOR]

Avalanche transistors have been widely used in nanosecond pulse generators because of high switching speed, low jitter, small size, low intrinsic inductance, and high-frequency operation. Marx circuits based on cascaded switches are often used to increase the voltage amplitude. In this paper, some current-limiting resistors in traditional Marx circuits were replaced by diodes to speed up the charging speed, to reduce the energy loss, and to increase the repetitive frequency. The influence of capacitance and the current limiting resistor on the output voltage amplitude and frequency were analyzed. The minimum on-resistance of a single BJT was calculated to be about 2.5 Ω, and the equivalent internal resistance of the Marx circuit based on cascaded switches reduced the output voltage amplitude over the load, so multiple Marx circuits in parallel were used to increase the output voltage amplitude. By changing the number of Marx modules in parallel, the influence of the equivalent internal resistance of the circuit on the output pulse was studied. By changing the load resistance, it verified that the Marx circuit in parallel had a better boosting effect over low-resistance loads. The experiments show that nanosecond pulses with a rise time of 3.4 ns, an amplitude of 2.5 kV and a repetitive frequency of 15 kHz were obtained over a 50 Ω resistor load with four Marx circuits in parallel. [ABSTRACT FROM AUTHOR]

Cognitive radio ad hoc network (CRAHN) has been considered an efficiently spectrum-aware communication paradigm in wireless networks because of its intrinsic properties of cognition and self-organization. In practice, because primary and secondary ad hoc networks are usually associated with two different types of wireless networks, the synchronization between primary users and secondary users is hardly guaranteed. The multi-channel asynchronous CRAHNs referred to as multi-channel non-time-slotted CRAHNs impose many challenging problems that severely degrade system performance. In this article, we review these challenging issues in multi-channel non-time-slotted CRAHNs, including reactivation- failure, frequently unexpected hand-offs, nonreal- time spectrum aggregation, inefficient power allocation, and frequent re-routing problems. Then, we develop a full-duplex based framework to resolve these issues. Future research directions are discussed to improve system performance of multi-channel non-time-slotted CRAHNs. [ABSTRACT FROM AUTHOR]

In this paper, a balanced phase shifter using coupled line with loaded transmission line is proposed, which is the first balanced passive phase shifter providing both differential-mode (DM) phase shift and common-mode (CM) suppression simultaneously. Furthermore, the proposed design can provide (30°–90°) phase-shift range with characteristic of the wide bandwidth. Compared with single-ended phase shifters, the proposed design can be directly utilized in differential system without additional baluns. Compared with the state-of-arts balanced passive phase shifters, the proposed one shows the advantages of the CM suppression, wider bandwidth, wider alternative phase-shift range, and simpler structure. Three DM transmission poles can be obtained to support the wide bandwidth. Complete theoretical analysis and discussion are given to guide the design. To verify the theoretic prediction, three prototypes are designed with the operation bandwidth for 30° ± 2.5° (60° ± 4.2° and 90° ± 5.5°) of 68% (70% and 73%), with the minimum insertion of 0.2 dB (0.15 dB and 0.27 dB), with the CM suppression better than 10 dB, and with the minimum return loss of 17.8 dB (18.5 dB and 15.1 dB), respectively. [ABSTRACT FROM AUTHOR]

In this work, we conduct comprehensive comparisons between four variants of independent component analysis (ICA) methods and three variants of sparse dictionary learning (SDL) methods, both at the subject-level, by using synthesized fMRI data with ground-truth. Our results showed that ICA methods perform very well and slightly better than SDL methods when functional networks’ spatial overlaps are minor, but ICA methods have difficulty in differentiating functional networks with moderate or significant spatial overlaps. In contrast, the SDL algorithms perform consistently well no matter how functional networks spatially overlap, and importantly, SDL methods are significantly better than ICA methods when spatial overlaps between networks are moderate or severe. This work offers empirical better understanding of ICA and SDL algorithms in inferring functional networks from fMRI data and provides new guidelines and caveats when constructing and interpreting functional networks in the era of fMRI-based connectomics. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for an electric-drive-reconstructed onboard charger (EDROC) for electric vehicles incorporating a symmetrical nine-phase permanent magnet machine. To implement three-phase power factor correction and propulsion battery voltage/current regulation, an exclusive utilization of the nine-phase propulsion system is developed. First, a paralleled three-phase pulsewidth-modulated voltage source rectifier is reutilized from six inverter legs and is directly connected to the three-phase utility grid through six-phase out of the machine stator windings. Second, a three-phase buck-type converter is reconstructed by the remaining three-phase inverter legs and machine windings. Third, to realize zero electromagnetic torque production during the three-phase charging mode, the rotor parking position is applied in the decoupling transformation matrix. Moreover, control schemes for a charging mode including current balancing and interleaving strategy are elaborated. To evaluate the steady-state and dynamic behavior of the proposed EDROC system under different operation scenarios, 3.3-kW laboratory prototype based tests have been conducted. [ABSTRACT FROM AUTHOR]

Communication at millimeter wave frequencies will be one of the essential new technologies in 5G. Acquiring an accurate channel estimate is the key to facilitate advanced millimeter wave hybrid multiple-input multiple-output (MIMO) precoding techniques. Millimeter wave MIMO channel estimation, however, suffers from a considerably increased channel use overhead. This happens due to the limited number of radio frequency (RF) chains that prevent the digital baseband from directly accessing the signal at each antenna. To address this issue, recent research has focused on adaptive closed-loop and two-way channel estimation techniques. In this paper, unlike the prior approaches, we study a non-adaptive, hence rather simple, open-loop millimeter wave MIMO channel estimation technique. We present a random phase rotation design of channel subspace sampling signals and show that they obey the restricted isometry property (RIP) with high probability. We then formulate the channel estimation as a low-rank subspace decomposition problem and, based on the RIP, show that the proposed framework reveals resilience to a low signal-to-noise ratio. It is revealed that the required number of channel uses ensuring a bounded estimation error is linearly proportional to the degrees of freedom of the channel, whereas it converges to a constant value if the number of RF chains can grow proportionally to the channel dimension while keeping the channel rank fixed. In particular, we show that the tighter the RIP characterization the lower the channel estimation error is. We also devise an iterative technique that effectively finds a suboptimal, but stationary, solution to the formulated problem. The proposed technique is shown to have improved channel estimation accuracy with a substantially low channel use overhead as compared to that of previous closed-loop and two-way adaptation techniques. [ABSTRACT FROM AUTHOR]

With the development of electric vehicles (EVs), the reliability and security of the motor drive system have been in high demand in recent years. EVs can still work reliably even when the motor drive system encounters some failures. Therefore, fault-tolerant motors have become the focus of research all over the world. The hybrid excitation axial field flux-switching permanent magnet machine (HEAFFSPMM) is a novel stator excitation brushless PM machine. It combines the advantages of AFFSPMM and hybrid excitation PM machine. Based on a 600 W prototype of three-phase 12/10 stator/rotor pole AFFSPMM, these parameters of HEAFFSPMM are optimized by 3-D finite element method in order to obtain the high self-inductance and low ratio of mutual and self-inductances, including the number of rotor poles, the split ratio, the width of permanent magnet, and the width of stator middle teeth. Then, the fault-tolerant control method of the space vector pulse width modulation based on minimum copper loss is proposed in this paper with the combination of adjusting the field current. The control methods of the HEAFFSPMM are simulated and investigated at healthy and one-phase open-circuit operation. Finally, the experiments are done to validate the proposed fault-tolerant control method. The results indicate that the HEAFFSPMM has good fault tolerance under the proposed control method. [ABSTRACT FROM AUTHOR]

Timing analysis of real-time tasks under preemptive scheduling must take cache-related preemption delay (CRPD) into account. Typically, a task may be preempted more than once during the execution in each period. To bound the total CRPD of ${k}$ preemptions, existing CRPD analysis techniques estimate the CRPD at each program point, and use the sum of the ${k}$ -largest CRPD among all program points as the total CRPD upper bound. In this paper, we disclose that the above-mentioned approach, although works well for instruction caches, leads to significant overestimation when dealing with data caches. This is because on data caches, the CRPD of preemptions at different program points may have correlations, and the total CRPD of multiple preemptions is in general smaller than the simple sum of the worst-case CRPD of each preemption. To address this problem, we propose a new technique to efficiently explore the correlation among the CRPD of different preemptions, and thus more precisely calculate the total CRPD. Experiments with benchmark programs show that the proposed technique leads to substantially tighter total CRPD estimation with multiple preemptions comparing with the state-of-the-art. [ABSTRACT FROM AUTHOR]

Wearable devices are designed to have a small size and be lightweight. Consequently, the battery life is constrained and becomes a crucial limitation. In this paper, we use both data compression and wireless transmission speed control to minimize the energy consumption of wearable devices for data transmission, subject to a deadline constraint. We consider both an off-line setting where future channel gains are known ahead of time and a stochastic setting where channel gains change stochastically according to a Markov process. For the first case, we present an efficient $(1+\epsilon)$ approximation algorithm for an arbitrarily small $\epsilon$ , while in the latter case we give a stochastic algorithm to minimize the total expected energy use. We also conduct experimental studies on the proposed algorithms and show that the stochastic algorithm, despite not knowing future channel gains, closely approximates the performance of the nearly optimal off-line solution with less than 0.1% difference in energy consumption on an average. We also compared the stochastic algorithm with several other practical algorithms and showed that our algorithm achieves significant improvements in the overall energy use. [ABSTRACT FROM AUTHOR]

This paper presents an end-to-end learning architecture for video-based person re-identification by integrating convolutional neural networks (CNNs) and bidirectional recurrent neural networks (BRNNs). Given a video with consecutive frames, features of each frame are extracted with CNN and then are fed into the BRNN to get a final spatio-temporal representation about the video. Specifically, CNN acts as a Spatial Feature Extractor, while BRNN is expected to capture the temporal cues of sequential frames in both forward and backward directions, simultaneously. The whole network is trained end-to-end with a joint identification and verification manner. Experimental results on benchmark data sets show that the proposed model can effectively learn spatio-temporal features relevant for re-identification and outperforms existing video-based person re-identification methods. [ABSTRACT FROM AUTHOR]

This paper proposes a novel technique to develop a low-cost electromagnetic (EM) centric multiphysics parametric model for microwave components. In the proposed method, we use space mapping techniques to combine the computational efficiency of EM single physics (EM only) simulation with the accuracy of the multiphysics simulation. The EM responses with respect to different values of geometrical parameters in nondeformed structures without considering other physics domains are regarded as coarse model. The coarse model is developed using the parametric modeling methods such as artificial neural networks or neuro-transfer function techniques. The EM responses with geometrical and nongeometrical design parameters as variables in the practical deformed structures due to thermal and structural mechanical stress factors are regarded as fine model. The fine model represents the behavior of EM centric multiphysics responses. The proposed model includes the EM domain coarse model and two mapping neural networks to map the EM domain (single physics) to the multiphysics domain. Our proposed technique can achieve good accuracy for multiphysics parametric modeling with fewer multiphysics training data and less computational cost. After the modeling process, the proposed model can be used to provide accurate and fast prediction of EM centric multiphysics responses of microwave components with respect to the changes of design parameters within the training ranges. The proposed technique is illustrated by a tunable four-pole waveguide filter example at 10.5–11.5 GHz and an iris coupled microwave cavity filter example at 690–720 MHz. [ABSTRACT FROM AUTHOR]

Objective image quality metrics (IQMs) potentially benefit from the addition of visual saliency. However, challenges to optimizing the performance of saliency-based IQMs remain. A previous eye-tracking study has shown that gaze is concentrated in fewer places in images with highly salient features than in images lacking salient features. From this, it can be inferred that the former are more likely to benefit from adding a saliency term to an IQM. To understand whether these ideas still hold when using computational saliency instead of eye-tracking data, we first conducted a statistical evaluation using 15 state-of-the-art saliency models and 10 well-known IQMs. We then used the results to devise an algorithm, which adaptively incorporates saliency in IQMs for natural scenes, based on saliency dispersion. Experimental results demonstrate that this can give significant improvements. [ABSTRACT FROM AUTHOR]

This paper proposed a simple strategy for parameters identification of switched reluctance motor (SRM) direct instantaneous torque control. This strategy without rotor locking includes measuring and calculating steps. In the measuring step, flux linkage curves with current at three critical positions are obtained. At the intermediate position, flux linkage curve is measured under current chopper control (CCC). At the aligned and unaligned position, flux linkage curves are measured when the winding is given a voltage pulse. In the calculating step, the whole flux-linkage characteristics with current and position can be calculated based on the measured critical curves. Then torque curves are calculated for direct instantaneous torque control. Meanwhile, the i-Ψ loci curves during CCC operation are analyzed for identifying adjusting advance angle. In this way, the entire flux linkage characteristics and adjusting advance angle parameters under different operating area are obtained. This strategy is applied to a 7.5 kW 12/8 SRM for direct instantaneous torque control (DITC). Experiments have been carried out to verify the effectiveness and accuracy of the proposed method. [ABSTRACT FROM PUBLISHER]

Cloud gaming is a promising approach to provide high-quality gaming services to mobile devices. However, existing cloud gaming systems fail to fully exploit hardware resources due to coarse-grained resource scheduling based on virtual machine migration. In this article, we propose a novel cloud gaming design, referred to as FGCG, with fine-grained scheduling to maximize resource utilization on a heterogeneous CPU-GPU cluster. Specifically, we decompose game workloads into small and independent render tasks that can be freely dispatched to different machines. Trace-driven simulation results show that FGCG can significantly improve resource utilization compared to existing cloud gaming systems. [ABSTRACT FROM AUTHOR]

This paper studies stability analysis of dc microgrids with uncertain constant power loads (CPLs). It is well known that CPLs have negative impedance effects, which may cause instability in a dc microgrid. Existing works often study the stability around a given equilibrium based on some nominal values of CPLs. However, in real applications, the equilibrium of a dc microgrid depends on the loading condition that often changes over time. Different from many previous results, this paper develops a framework that can analyze the DC microgrid stability for a given range of CPLs. The problem is formulated as a robust stability problem of a polytopic uncertain linear system. By exploiting the structure of the problem, we derive a set of sufficient conditions that can be efficiently checked by solving convex optimization problems to guarantee locally robust stability. The effectiveness and nonconservativeness of the proposed framework are demonstrated using simulation examples. [ABSTRACT FROM PUBLISHER]

Due to the nonlinear response of digital phase-shifting profilometry (PSP), phase errors are inevitable in the retrieved 3-D profiles and result in negative impacts on the measurement accuracy of the PSP system. A novel method is presented in this paper to reduce the impact. Instead of compensating phase errors in the retrieved 3-D profile, specific harmonics are superimposed upon the initial fringe pattern actively to adjust the amplitudes of the harmonics in the captured fringe image with the intention to suppress the phase error, and all nonlinear response of the PSP system can be compensated in theory. Furthermore, it does not consume additional time in the 3-D profile reconstruction process. Experimental results are shown to demonstrate the validity of the method. [ABSTRACT FROM PUBLISHER]

A cross-shaped composite with frequency selective surfaces is applied in the design of a broadband polarizer. The structure is multilayer, and the unit cell of each layer consists of a composite cross and a metal strip. The design takes advantage of both the similar amplitude and the stable phase difference of nearly 90° of the two orthogonal components of transmitted waves. The bandwidth of the polarizer reaches 74%, from 5.15 to 11.20 GHz, which is able to generate circular-polarization waves from incident linear waves. A sample polarizer is fabricated and tested. According to the measurement results, the polarizer operates from 5.75 to 11.20 GHz at normal incidence. In addition, its working frequency band can still cover the range of 5.80 to 11.00 GHz when the incident angle increases to 20°. [ABSTRACT FROM PUBLISHER]

Image quality assessment potentially benefits from the addition of visual attention. However, incorporating aspects of visual attention in image quality models by means of a perceptually optimized strategy is largely unexplored. Fundamental challenges, such as how visual attention is affected by the concurrence of visual signals and their distortions; whether visual attention affected by distortion or that driven by the original scene only should be included in an image quality model; and how to select visual attention models for the image quality application context, remain. To shed light on the above unsolved issues, designing and performing eye-tracking experiments are essential. Collecting eye-tracking data for the purpose of image quality study is so far confronted with a bias due to the involvement of stimulus repetition. In this paper, we propose a new experimental methodology to eliminate such inherent bias. This allows obtaining reliable eye-tracking data with a large degree of stimulus variability. In fact, we first conducted 5760 eye movement trials that included 160 human observers freely viewing 288 images of varying quality. We then made use of the resulting eye-tracking data to provide insights into the optimal use of visual attention in image quality research. The new eye-tracking data are made publicly available to the research community. [ABSTRACT FROM PUBLISHER]

The design, fabrication, assembly, and characterization of a miniature adjustable-focus camera module driven by MEMS-thermal actuators are presented. The camera module consists of one solid tunable lens for optical power variation, two identical MEMS-thermal actuators integrated with displacement amplifiers for lens element driving, a CMOS image sensor for recording, and necessary CNC fabricated components for supporting and housing. Fully 3D-multiphysics simulations with valid material properties are performed to explore the design and, hence, optimize the performance of the system. In this paper, the fabricated MEMS-devices are clearly demonstrated, and followed by the detailed characterization of the camera module. Static characterizations of the system, including the temperature distribution on actuators, electric resistance change with temperature increase, displacement-voltage curve of actuator, and the focal length tuning capability, are tested. Dynamic response speed and imaging performance of the camera module are also covered. Results show that the designed MEMS actuator is able to provide a maximum output displacement of 135 \mu \textm when a 10 V driving voltage is applied. Driven by the thermal actuator, the solid tunable lens presents a repeatable focal length tuning from 9.2 to 7.9 mm with precise focus control. The adjustable-focus capability of the miniature camera module is experimentally demonstrated by clearly focusing targets placed at different object distances. [2016-0072] [ABSTRACT FROM PUBLISHER]

Acoustic and electrical characteristics of biological tissue are important factors in magnetoacoustic tomography with magnetic induction (MAT-MI). Acoustic inhomogeneity significantly affects the propagations of sound waves. Differences in sound speed lead to distortions of the sound sources in the reconstruction process. The objective of this study is to develop a novel algorithm to reconstruct the sound source distribution in an acoustically inhomogeneous medium. The proposed algorithm is developed on the basis of the finite-difference time-domain method and time-reversal acoustic theory; it combines the relationship among symmetrical transducers with the back-projection algorithm. An acoustically inhomogeneous model with different regions of variable sound speeds is established to validate the proposed algorithm. From the data collected by a rotated focused transducer, first, the sound speed distribution is reconstructed, and then, the sound sources of the model are reconstructed. The reconstructed sound sources are obviously distorted when the speed differences are not considered. In contrast, the proposed algorithm yields reconstructed sound sources that are consistent with the model in terms of shape and size. Thus, the proposed algorithm is capable of accurately reconstructing the acoustic sources distribution in an acoustically inhomogeneous medium. This method provides a solution reducing the influence of acoustic inhomogeneity in MAT-MI. The distributions of sound speed can be obtained during the process of reconstructing the sound source. Consequently, the imaging of the acoustic speed and the electrical conductivity of biological tissues can be implemented simultaneously in MAT-MI. [ABSTRACT FROM PUBLISHER]

Personalized review-based rating prediction, a newly emerged research problem, aims at inferring users’ ratings over their unrated items using existing reviews and corresponding ratings. While some researchers proposed to learn topic factor from review text to obtain interpretability for rating prediction, they often overlooked the fact that the learned topic factors are limited to review text and cannot fully reveal the complicated relations between reviews and ratings. Moreover, topic modeling based solutions for this problem usually utilize Gibbs sampling algorithms to learn topics and word distributions, resulting in non-negligible computational overload. To address the above challenges, we propose an integrated topic and latent factor model (ITLFM), which combines topic and latent factors in a linear way to make them complement each other for better accuracies in rating prediction tasks. In addition, ITLFM models review text through an additive topic model to reveal user's and item's topic factors simultaneously. To ensure high learning efficiency, we design a hybrid stochastic learning algorithm for ITLFM. We evaluate ITLFM on several standard benchmarks and compare with representative approaches. The experimental results demonstrate that the proposed ITLFM method is computationally efficient and accurate, as well as scalable for large scale applications. [ABSTRACT FROM PUBLISHER]

The high mobility germanium (Ge) channel is considered as a strong candidate for replacing Si in pMOSFETs in the near future. It has been reported that the conventional power-law degradation kinetics of Si devices is inapplicable to Ge. In this paper, further investigation is carried out on defect energy distribution, which clearly shows that this is because the defects in GeO2/Ge and SiON/Si devices have different physical properties. The three main differences are: 1) energy alternating defects (EAD) exist in Ge devices but are insignificant in Si; 2) the distribution of as-grown hole traps has a tail in the Ge bandgap but not in Si, which plays an important role in the degradation kinetics and device lifetime prediction; and 3) EAD generation in Ge devices requires the injected charge carriers to overcome a second energy barrier, but not in Si. Taking the above differences into account, the power-law kinetics of EAD generation can be successfully restored by following a new procedure, which can assist in the Ge process/device optimization. [ABSTRACT FROM PUBLISHER]

Direction finding for multiple targets is one of the most important tasks in MIMO radar applications. The existing algorithms such as MUSIC and ESPRIT for direction finding can only achieve the localization of multiple targets with unchanged location parameters due to their batch mode. In this paper, we show that the multiple targets localization and tracking in a bistatic MIMO radar system can be solved by adaptive asymmetric joint diagonalization, where the fluctuation of target radar cross section (RCS) is regarded as a source of time diversity for matched data, and the algebraic structure of the matched data themselves rather than their statistics is exploited. The resulting algorithm can achieve not only the localization but also tracking of multiple targets since it estimates the target location parameters in a recursive mode. The identifiability of the proposed algorithm is analyzed and the Cramér–Rao lower bound is also derived as performance benchmark. Simulation results show that the proposed algorithm has comparable localization accuracy to batch algorithms. Moreover, it exhibits good tracking capability for multiple targets with varying location parameters. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) technology as a convenient and reliable charging method, its electromagnetic field (EMF) radiation, and its compliance with human electromagnetic exposure limits have recently been studied. Different from the current research, which validates the EMF radiation level of a predesigned WPT system, this paper presents the loosely coupled transformer design method to minimize the EMF in the concerned area. The energy storage in the primary and secondary coils is studied for all popular compensation topologies in recently reported research. The coil of the loosely coupled transformer is designed with the S-S compensation topology as an example. The EMF radiation level is optimized to below the International Commission on Non-Ionizing Radiation Protection guideline in the concerned area. A 3.3-kW WPT system for electric vehicle wireless charging with an LCC-LCC compensation topology is designed with detailed process and experiment results, verifying that the EMF radiation is controlled as designed. The numerical analysis of human exposure is performed with the finite-element method, and the results show compliance as expected. [ABSTRACT FROM PUBLISHER]

Wireless power transfer (WPT) is an emerging technology that can realize electric power transmission over certain distances without physical contact, offering significant benefits to modern automation systems, medical applications, consumer electronics, etc. This paper provides a comprehensive review of existing compensation topologies for the loosely coupled transformer. Compensation topologies are reviewed and evaluated based on their basic and advanced functions. Individual passive resonant networks used to achieve constant (load-independent) voltage or current output are analyzed and summarized. Popular WPT compensation topologies are given as application examples, which can be regarded as the combination of multiple blocks of resonant networks. Analyses of the input zero phase angle and soft switching are conducted as well. This paper also discusses the compensation requirements for achieving the maximum efficiency according to different WPT application areas. [ABSTRACT FROM PUBLISHER]

UV imager has promising application prospect in the detection of corona discharge because of its advantages, such as high sensitivity, intuitive and non-contact discharge detection. In order to make better use of ultraviolet imager to detect corona of the high voltage electrical equipment, experiments are carried out to observe insulator corona discharge using the DayCor® Superb UV imager in this paper. During the experiments, voltages are applied on a FXBW-35/70 insulator, and corona discharge was detected through the ultraviolet imager. The relationship between the detected photon number, the instrument gain and the distance are studied. Then through extracting the discharge facular area from UV image using Matlab package, the differences of photon number and facular area in quantifying the corona discharge intensity are compared and analyzed. Research shows that the photon number increases first and then decrease with the rise of UV gain. Differently, the facular area increases monotonically with the rise of gain. There will be no multi-valued problem when the facular area is used to quantify the discharge. Both the photon number and facular area decrease with the increase of detecting distance, but the fluctuation of the facular area-distance curve is smaller than the photon number — distance curve. Using the facular area to quantify the corona discharge can be more accurate. The study results of this paper provide references for better assessing the electric equipment corona discharge intensity by ultraviolet imager. [ABSTRACT FROM PUBLISHER]

Fabless semiconductor industry and government agencies have raised serious concerns about tampering with inserting hardware Trojans (HTs) in an integrated circuit supply chain in recent years. In this paper, a low hardware overhead acceleration method of the detection of HTs based on the insertion of 2-to-1 MUXs as test points is proposed. In the proposed method, the fact that one logical gate has a significant impact on the transition probability of the logical gates in its logical fan-out cone is utilized to optimize the number of the inserted MUXs. The nets which have smaller transition probability than the user-specified threshold and minimal logical depth from the primary inputs are selected as the candidate nets. As for each candidate net, only its input net with smallest signal probability is required to be inserted the MUXs-based test points. The procedure repeats until the minimal transition probability of the entire circuit is not smaller than the threshold value. In order to further optimize the number of required insertions and reduce the overhead, the weighted random pattern technique is also applied. Experiment results on ISCAS’89 benchmark circuits show that our proposed method can achieve remarkable improvement of transition probability with on average 9.50% power, 2.37% delay, and 10.26% area penalty. [ABSTRACT FROM AUTHOR]

With the advent of cloud computing, it has become increasingly popular for data owners to outsource their data to public cloud servers while allowing data users to retrieve this data. For privacy concerns, secure searches over encrypted cloud data has motivated several research works under the single owner model. However, most cloud servers in practice do not just serve one owner; instead, they support multiple owners to share the benefits brought by cloud computing. In this paper, we propose schemes to deal with privacy preserving ranked multi-keyword search in a multi-owner model (PRMSM). To enable cloud servers to perform secure search without knowing the actual data of both keywords and trapdoors, we systematically construct a novel secure search protocol. To rank the search results and preserve the privacy of relevance scores between keywords and files, we propose a novel additive order and privacy preserving function family. To prevent the attackers from eavesdropping secret keys and pretending to be legal data users submitting searches, we propose a novel dynamic secret key generation protocol and a new data user authentication protocol. Furthermore, PRMSM supports efficient data user revocation. Extensive experiments on real-world datasets confirm the efficacy and efficiency of PRMSM. [ABSTRACT FROM AUTHOR]

In the age of Web 2.0, community user contributed questions and answers provide an important alternative for knowledge acquisition through web search. Question retrieval in current community-based question answering (CQA) services do not, in general, work well for long and complex queries, such as the questions. The main reasons are the verboseness in natural language queries and the word mismatch between the queries and the candidate questions in the CQA archive during retrieval. To address these two problems, existing solutions try to refine the search queries by distinguishing the key concepts in the queries and expanding the queries with relevant content. However, using the existing query refinement approaches can only identify the key and non-key concepts, while the differences between the key concepts are overlooked. Moreover, the existing query expansion approaches, not only overlook the weights of key concepts in the queries, but also fail to consider concept level expansion for them. In this paper, we explore a key concept identification approach for query refinement and a pivot language translation based approach to explore key concept paraphrasing. We further propose a new question retrieval model which can seamlessly integrate the key concepts and their paraphrases. The experimental results demonstrate that the integrated retrieval model significantly outperforms the state-of-the-art models in question retrieval. [ABSTRACT FROM PUBLISHER]

This paper focuses on the coordination of a population of thermostatically controlled loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the device bidding and market clearing strategies to motivate self-interested users to realize efficient energy allocation subject to a peak energy constraint. This coordination problem is formulated as a mechanism design problem, and we propose a mechanism to implement the social choice function in dominant strategy equilibrium. The proposed mechanism consists of a novel bidding and clearing strategy that incorporates the internal dynamics of TCLs in the market mechanism design, and we show it can realize the team optimal solution. This paper is divided into two parts. Part I presents a mathematical formulation of the problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations. [ABSTRACT FROM AUTHOR]