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This paper presents an overview of the design and technology of miniature X-ray sources of various types, which can be useful in the portable instruments for diagnosis and precision medical therapy, as well as in industrial applications. Several examples of X-ray sources using the pyroelectric and piezoelectric effects and tubes with thermal and field-emission electron sources have been described. A concept of an X-ray source integrated on one chip, made by the use of microengineering techniques, concludes this paper. In this micro-electro-mechanical system-type construction, a miniature field-emission electron source with carbon nanotube cathode and a recently developed high-vacuum micropump are applied. [2016-0214] [ABSTRACT FROM PUBLISHER]

When the duration of a laser pulse is comparable to the plasma wave period, a large-amplitude plasma wave can be driven by the laser. In the presence of a guiding magnetic field, the large-amplitude plasma wave of finite transverse extent and large phase velocity resonantly accelerates the electrons to a higher energy level. For a small laser spot size, the laser exerts an axial as well as the radial ponderomotive force on the electrons that creates a density depression on the laser axis. This electron-depleted channel also creates a radial electric field (ion space-charge field). The acceleration of electrons in this channel is investigated, where the effect of ion space-charge field is considered, by solving the single particle dynamical equations. This paper shows that the space charge field plays an important role in electron energy gain during acceleration by a plasma wave in a magnetic plasma channel. This paper may be crucial in understanding the dynamics of particle motion and improving the quality of accelerated electron beam in the laser wakefield accelerators. [ABSTRACT FROM AUTHOR]

This paper provides an overview of hyperloop technologies, including a brief discussion of key components of a hyperloop system that determine the electric power requirements as a function of time. At-scale hyperloop systems do not yet exist, so a model was used to generate a set of load profiles for conceptual hyperloop realizations at four locations in the United States: two systems in California and one each in Colorado and Ohio. In all four cases, the modeled hyperloop load profiles included pulses in both active and reactive power. Grid modeling was performed to estimate the grid impacts and for discussing grid integration challenges. The paper discusses how energy storage systems might be used to eliminate the pulsating load characteristics or significantly reduce it to accommodate current grid planning guidelines. [ABSTRACT FROM AUTHOR]

This paper explores a series of challenges presented by Hartmut Rosa's concept of resonance viewed in the context of the normative and political dimensions of critical theory, a tradition in which he explicitly places his work (even as he draws on a wide range of other scholarly fields and domains). First, a tension between the anthropological and sociocultural aspects of his project raises questions about whether the avowed political commitments of the project can be incorporated into its theoretical framework. Second, the variability with which resonance can present, and its fundamentally pathic nature, makes it difficult to imagine how it might serve an emancipatory interest. Beyond this, the critical diagnosis of forms of impaired or deficient resonance introduces methodological questions with moral consequences. Despite these challenges, Rosa's project importantly calls for a renewed relation to the world, one that shares affinities with parallel developments within the humanities. [ABSTRACT FROM AUTHOR]

Graphics processing units (GPUs) have become the target for high-speed and high-throughput computing in the last decade. The device provides excellent capabilities in speeding general-purpose computing in many applications. The main advantage of GPUs is the ability to process heavy parallel requests depending on thousands of parallel processing cores operating concurrently on solving numerical calculations. In this paper, the role of the GPUs in speeding up the encryption process is studied extensively. Advanced Encryption Standard (AES) algorithm is used to encrypt files in both Central Processing Units (CPUs) and GPUs. The encryption process consists of several sub-processes of which each is evaluated by both types of processors. Two different systems models were used in testing operations. Results showed that low-size encryption processes are not affected by the acceleration process and do not require GPU processing. On the other hand, large file size encryption relies heavily on the acceleration process resulting in less processing time. The analysis also showed that the acceleration speed remains constant after reaching the maximum load value. [ABSTRACT FROM AUTHOR]

Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that can simultaneously measure multiple important tissue properties of human body. Although MRF has demonstrated improved scan efficiency as compared to conventional techniques, further acceleration is still desired for translation into routine clinical practice. The purpose of this paper is to accelerate MRF acquisition by developing a new tissue quantification method for MRF that allows accurate quantification with fewer sampling data. Most of the existing approaches use the MRF signal evolution at each individual pixel to estimate tissue properties, without considering the spatial association among neighboring pixels. In this paper, we propose a spatially constrained quantification method that uses the signals at multiple neighboring pixels to better estimate tissue properties at the central pixel. Specifically, we design a unique two-step deep learning model that learns the mapping from the observed signals to the desired properties for tissue quantification, i.e.: 1) with a feature extraction module for reducing the dimension of signals by extracting a low-dimensional feature vector from the high-dimensional signal evolution and 2) a spatially constrained quantification module for exploiting the spatial information from the extracted feature maps to generate the final tissue property map. A corresponding two-step training strategy is developed for network training. The proposed method is tested on highly undersampled MRF data acquired from human brains. Experimental results demonstrate that our method can achieve accurate quantification for T1 and T2 relaxation times by using only 1/4 time points of the original sequence (i.e., four times of acceleration for MRF acquisition). [ABSTRACT FROM AUTHOR]

Radar detection of maneuvering targets with high velocity and acceleration often results in severely deteriorative performance or even failure. Parameter-search approaches are commonly used to overcome such difficulty, but the substantial computational load involved makes them unable to meet the real-time requirements of practical systems. In this paper, to improve the detection performance for maneuvering targets at no expense of computing resource, we derive a coherent detection algorithm for maneuvering targets based on the discrete polynomial-phase transform. The proposed algorithm simultaneously decouples the displacement and velocity of target and reduces the order of the acceleration-induced quadratic phase in the frequency domain of the pulse compressed echoes. As such, the range and Doppler walks are both compensated without any a priori knowledge. In addition, the impact of the cross terms on the detection of auto-terms is investigated in the multiple targets scenario, and the applicable conditions of the proposed algorithm are given. Using numerical simulation and real-data experiments, we demonstrate the advantages of the proposed algorithm over state-of-the-art methods in terms of integration gain and estimation accuracy. [ABSTRACT FROM AUTHOR]

This paper discusses the current state-of-the-art, ongoing fundamental and technical challenges and potential roadmaps for micro-scale vibration energy harvesting and power conversion devices employing micro-/nano-magnetics. Such devices are of paramount importance as powering solution for autonomous and ubiquitous sensor nodes within the emerging “Internet of Things (IoT).” In this paper, we have reviewed the fundamental limitations, technological needs, and breakthroughs in the mentioned areas, including materials, process integration, and device design issues. Particularly, current limitations in both the relevant soft and hard (or permanent) micro-magnets, roadmaps for a complete “Magnetic MEMS” solution for energy harvesting and efficient low-power conversion for “IoT” applications, are discussed. [ABSTRACT FROM AUTHOR]

Vibration and acoustic noise in switched reluctance motor (SRM) drives have been investigated and addressed frequently. However, the focus of most the paper is on vibration of the stator frame due to radial electromagnetic forces acting on the stator teeth. In this paper, a comprehensive vibration analysis for a SRM assembly using finite element (FE) method is conducted, which considers the stator and rotor vibrations due to radial electromagnetic force as well as the effect of mechanical coupling on the vibration between the stator and rotor. First, an experimental modal test was performed to extract modal parameters and to observe the coupling effect. The parameters were then used to adjust and validate the FE model that was used to obtain transfer functions for vibration characterization. Using the frequency domain representation of the radial magnetic force vector and the calculated transfer functions, radial and tangential vibration components have been predicted. [ABSTRACT FROM AUTHOR]

Discontinuous Galerkin time-domain (DGTD) methods using explicit time integration schemes often suffer from unreasonably small time-step size when applied to simulations involving electrically small structures. In this paper, an exponential time integration (ETI) scheme based on Krylov subspace is proposed for DGTD. The proposed scheme is unconditionally stable and exhibits good accuracy for large time-step sizes. When compared with classic ETI schemes, in the proposed scheme, the dense matrix exponentials are absorbed in matrix–vector products, hence the prohibitive memory costs are avoided. Moreover, a preconditioner combining the shift-and-invert technique and restricted additive Schwarz method is also developed to accelerate the proposed scheme. [ABSTRACT FROM AUTHOR]

The driving coil, as a key element of synchronous induction coilgun, endures not only the radial expansionary force because of the magnetic flux compression but also the axial force due to the compressive force and counterforce of the armature. Dielectric breakdown and mechanical structure damage occurs frequently. Meanwhile, the driving coil should have high energy conversion efficiency as a pusher to accelerate the armature. Therefore, it is important to choose the appropriate structure and parameters in order to achieve a high launching performance. In this paper, the factors that influence the system efficiency are analyzed first. Different structure designs of the driving coil with the same inductance are evaluated. The effect of different calibers on the system efficiency is analyzed. The simulation result shows that the structure of the driving coil should be chosen according to the practical launching requirement while the magnetic coupling should be increased. Second, the electromagnetic force applied on the coil is calculated and the stress is analyzed. The thickness and displacement of the containment are calculated on the condition of unyielding. In order to validate the accuracy of the theoretical analysis, an electromagnetic-mechanical coupling finite element model is built. Comparing two calculation results, the error is small. Therefore, the method can be used to guide the design of the driving coil. Finally, a driving coil is fabricated according to the calculation results and experimented through static and dynamic tests. The experimental results show that the driving coil performs well and have high conversion efficiency. It provides a theoretical and experimental basis for the future design of multistage induction coilgun. [ABSTRACT FROM AUTHOR]

The rapid development of Internet-of-Things is yielding a huge volume of time series data, the real-time mining of which becomes a major load for data centers. The computation bottleneck in time series data mining is distance function, which is the fundamental element of many high data mining tasks. Recently various software optimization and hardware acceleration techniques have been proposed to tackle the challenge. However, each of these techniques is only designed or optimized for a specific distance function. To address this problem, in this paper we propose MDA, a high-throughput reconfigurable memristor-based distance accelerator for real-time and energy-efficient data mining with time series in data centers. Common circuit structure is extracted for efficiency, and the circuit can be configured to any specific distance functions. Particularly, we adopt the emerging device memristor for the design of MDA. Comprehensive experiments are presented with public available datasets to evaluate the performance of the proposed MDA. Experimental results show that compared with existing works, MDA has achieved a speedup of $3.5\times $ – $376\times $ on performance and an improvement of 1–3 orders of magnitude on energy efficiency with little accuracy loss. [ABSTRACT FROM AUTHOR]

The recoil force that causes the rearward movement of the gun is generated during firing a railgun as a conventional gun. According to Newton’s third law, it should be equal to the electromagnetic force that accelerates an armature. It continues to act as long as current flows in the rails even when the muzzle arc occurs immediately after the armature exits. The recoil force in a railgun increases being proportional to the square of current as current increases. A recoil system should be installed to absorb the recoil force when it is so large that a carriage cannot withstand the load transmitted directly to it. Design and experiment of the recoil system using friction springs for a railgun are described in this paper. The space and volume to place a spring type of recoil system into the carriage are required relatively small to a hydraulic type and it has a simple structure. The recoil velocity of the railgun can be rapidly down due to the excellent damping characteristics of friction springs during two or three cyclic motions after firing. The load imposed to the carriage can be reduced to over one-tenth of the recoil force with 15 mm of recoil length when about 1560 N · s of firing impulse is applied. [ABSTRACT FROM AUTHOR]

In a railgun, the melting of the armature as a result of great frictional and Joule heating forms a liquid conducting film over the rail–armature contact surfaces. The magnetic field was concentrated in the trailing surface of the armature and liquid film due to the velocity skin effect. Electromagnetic forces in the longitudinal direction acting on the armature and liquid film could cause a self-acceleration in the film. However, the magnetic lateral force in the film squeezes the armature legs against the rails in the transverse direction. Thus, a diverging film, with a minimum thickness at the leading edge, forms at the rail–armature interface due to easier tail deformation than head for traditional C-shaped armature legs. This paper attempts to investigate the effect of self-acceleration in this diverging film on hydrodynamic lubrication and compared with the traditional lubrication model. Total pressure distribution considering uniform and nonuniform film accelerations is investigated, respectively. It is found that the film’s self-acceleration can generate the positive pressure, strengthening the total pressure distribution. Furthermore, conditions for generating positive pressure distribution under different film accelerations are analyzed and discussed. The results show that the film acceleration can decrease the minimum film’s slope that produces a positive pressure distribution. Total pressure distribution can maintain positive at thinner film when the film acceleration is considered. [ABSTRACT FROM AUTHOR]

This paper presents a wavelet-neural network recognition system for personal fitness assistance and elderly daily activity monitoring applications. This discrete wavelet transform radial basis neural network (DWT-RBNN) analyzes vibration induced by human motions, and identifies motion status automatically. The 3-D vibration signals are measured by integrated accelerometer chip, and then DWT extracts vibration features. Local energy of extracted feature is calculated and used by RBNN. A multi-channel RBNN is designed and used for recognition. The computation burden is reduced because of the DWT pre-processing. From experiment results, RBNN shows successful recognition capability. This paper also presents flow diagram to determine engineering parameters for the present and future product developments. [ABSTRACT FROM AUTHOR]

Embedded systems present stringent and often conflicting requirements. On the one side, the need for high performance within a tight energy budget favors inflexible Application Specific Integrated Circuit (ASIC) implementations; on the other side, a short time-to-market demands programmability. Hybrid architectures such as special-purpose customized processors represent an attractive solution, as they are programmable by software, but use dedicated hardware to accelerate parts of the computation. In such a scenario, the capability of automatically identifying the computation parts to be realized in hardware is highly desirable, in order to reduce design time and effort. This paper aims at advancing the state-of-the-art in this field. We recognize that subgraphs of control flow graphs having a single input control point and a single output control point, that we call regions, are good targets for the synthesis of application specific hardware accelerators. We therefore provide a method to identify them and an LLVM-based toolchain (named RegionSeeker) that, analyzing a software application, automatically selects its most profitable regions given an area constraint. Experimental evidence shows that the accelerators identified by RegionSeeker provide a speedup of up to $4.6\boldsymbol {\times }$ and, on average, approximately 30% higher speedup is achieved compared to state-of-the-art identification techniques. [ABSTRACT FROM AUTHOR]

This paper studies the codesign optimization approach to determine how to optimally adapt automatic control of an intelligent electric vehicle to driving styles. A cyber-physical system (CPS)-based framework is proposed for codesign optimization of the plant and controller parameters for an automated electric vehicle, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. Driving style recognition algorithm is developed using unsupervised machine learning and validated via vehicle experiments. Adaptive control algorithms are designed for three driving styles with different protocol selections. Performance exploration method is presented. Parameter optimizations are implemented based on the defined objective functions. Test results show that an automated vehicle with optimized plant and controller can perform its tasks well under aggressive, moderate, and conservative driving styles, further improving the overall performance. The results validate the feasibility and effectiveness of the proposed CPS-based codesign optimization approach. [ABSTRACT FROM AUTHOR]

The multipactor (MP) phenomenon can generate exponentially increasing electron populations in RF vacuum systems, leading to components becoming damaged. This paper uses numerical methods to analyze an RF vacuum window in a coaxial line under various standing wave conditions. Our methods are first benchmarked against the analytic and experimental results for the traveling wave and the numerical results for standing waves that were found in previous work. Second, the effect of standing waves on electron motion in the axial direction is discussed and related to electron trajectories in the presence of an RF window. It is found that standing waves with the magnetic maximum located behind the RF window lead to window collisions that can affect MP depending on the power, frequency, and conductor radii. For a low number of window collisions, MP was highly predictable by earlier work, but as the percentage of collisions occurring on the window surpassed approximately 50%, a novel mode of MP emerged to dominate the phenomenon. [ABSTRACT FROM AUTHOR]

Induction synchrotron (IS) has become the focus of improving the intensity of high energy ion beams in recent years. But because of the pulse voltage of the induction accelerating cell cannot adjust quickly, causing the mismatch of the magnetic deflection field and accelerate electric field, there is a serious beam loss problem in IS. The simulation of beams longitude dynamics proves that increasing the number of accelerating cells can effectively reduce the loss. In this paper, a novel compact induction accelerator module is introduced. Compared with the existing induction accelerator module of KEK, the new design can increase the number of accelerating cells to more than five times in the same installation space and improves the voltage top drop of the acceleration pulse significantly. [ABSTRACT FROM AUTHOR]

It is expected that bilateral control will find broad applications such as mobile robot exploration and operations in extreme environments. However, the transmission of vivid haptic sensation requires a rapid data-transfer rate of haptic data due to the short sampling period and high-frequency communication. The objective of this paper is aimed at the traffic reduction of haptic data by exploiting an impedance field equivalence of a standard bilateral control. The proposed approach theoretically clarifies the equivalence of the standard bilateral control and impedance control in terms of haptic transmission. Based on this equivalence, the same performance of a standard bilateral control can be achieved by only communicating the force information that determines the equilibrium position of the impedance control. The validity of the proposed approach is confirmed through both simulations and experiments. The obtained results show that the proposed approach successfully reduced the amount of communicated haptic data without any disadvantages compared with the standard acceleration-based bilateral system. This paper shows novel interpretation that haptic transmission is realized by controlling the equilibrium force, which contributes reducing data traffic in haptic transmission and understanding motion generation. [ABSTRACT FROM AUTHOR]

This paper investigates the potential use of dielectric laser accelerators (DLAs) for nuclear security applications. For the first time, the LSP code is used to look at this application. LSP is a fast running, parallelized particle-in-cell code that includes space charge effects. The focus of this paper is to ascertain the order of magnitude, amount of charge, that can be driven through the accelerator. From these results, a recommendation on the potential of DLAs for nuclear security applications is given. [ABSTRACT FROM AUTHOR]

To drive the machine tool along a curve, a commercial computer-aid design and computer-aided manufacturing system usually breaks the curve into a set of line segments. This paper provides a systematic way for generating smooth and fast machining velocity planning for contouring line segments in a machine tool. It is especially useful for mass manufacturing. In this paper, the particle swarm optimization algorithm is employed to optimize the design parameters. The algorithm allows for as many motion limits as possible, not only the limits along the path, but those on the axes, as well. It can automatically determine the existence of acceleration, constant speed, and deceleration zones of the S-curve velocity profile. Also, it can determine the optimal corner speed with a given corner error. The computation time of the algorithm is fast so that it allows for online operation. Simulation and experimental results demonstrate that machine tools using the proposed algorithm go fast where possible and slow down where needed, dramatically increasing the productivity. [ABSTRACT FROM AUTHOR]

The constant false alarm rate with convolution and pooling (CP-CFAR) method, which can improve the detection efficiency via GPU parallel acceleration in the airborne synthetic aperture radar (SAR) images, is proposed in this paper. The constant false alarm rate (CFAR) method is one of the most widely used methods for target detection in airborne SAR images. However, since the CFAR is performed on a pixel-by-pixel basis, the time consumption will increase rapidly with the expansion of image scene. Even if the GPU is used for acceleration, the efficiency improvement is still limited, which cannot meet the real-time processing requirements. Therefore, the CP-CFAR method for the target detection of SAR images is proposed in this paper. The convolution layer uses the horizontal and vertical Sobel operators to improve the contrast between targets and background, and the pooling layer can reduce the processing dimension of the images. The convolution and pooling layers are added before the two-parameter CFAR, which can reduce the computational elements but without losing the main feature of the original image. More importantly, compared to the traditional CFAR, the proposed CP-CFAR is more suitable for GPU acceleration, which can improve the detection efficiency significantly. Experiments on the moving and stationary target acquisition and recognition SAR images with a size of 1478 × 1784 show that, compared with the traditional cell-averaging CFAR, two-parameter CFAR and their CPU, multithread CPU, and GPU acceleration modes, the proposed CP-CFAR with GPU acceleration can obtain the best detection performance with the highest acceleration ratio, and the operation time is less than 192 ms. [ABSTRACT FROM AUTHOR]

This paper presents a new radio frequency (RF) excited plasma cathode electron beam (EB) gun design and experimental results at a frequency of 84 MHz. The design offers the following benefits over thermionic cathode triode EB guns: much longer cathode lifetime and as a result improved reliability and reduced maintenance costs; no requirement for a grid electrode, avoiding beam aberration, and rapid beam pulsing. The construction of the diode gun was completed and the results of this paper demonstrate that the EB can be switched on in 200 ns and off within 800 ns. Electrons were extracted from a plasma chamber and then accelerated by an electric field applied in a vacuum chamber at a pressure of 10 ^-5 to 10^-6 mbar, producing a collimated EB. The ionized gas used was air at some 0.5 mbar pressure. The EB gun has been operated at -60~kV accelerating potential and has produced beams of up to 3.2 kW power continuous wave. Modulation of the RF signal was used to control the beam power. Details of the design features of the plasma device are given and evidence of the advantages over conventional EB guns is provided through empirical results. [ABSTRACT FROM AUTHOR]

The concept of digital twin has been introduced for some time, yet one fundamental element of digital twin, digital material, has not been thoroughly studied. To interact with the physical product, the digital twin should always truthfully reflect the responses under various stimuli. In this paper, the deformation and fracture behavior of high impact polystyrene (HIPS) under the influencing factors of strain rate and stress triaxiality are studied to construct the material's digital model. A digital twin of air conditioner product is further built and tested under virtual drop test. Comparing to experimental results, the acceleration curve, crazing induced whitening and the fracture events can all be captured by the digital twin. Our work demonstrates the importance of material characterization as an essential step to construct an accurate digital twin and shows a promising future of digital twin in virtual testing to replace traditional "trial and error" experiments., (© 2022. The Author(s).)

The real-time identification of time-varying cable force is critical for accurately evaluating the fatigue damage of cables and assessing the safety condition of bridges. In the context of unknown wind excitations and only one available accelerometer, this paper proposes a novel cable force identification method based on an improved adaptive extended Kalman filter (IAEKF). Firstly, the governing equation of the stay cable motion, which includes the cable force variation coefficient, is expressed in the modal domain. It is transformed into a state equation by defining an augmented Kalman state vector with the cable force variation coefficient concerned. The cable force variation coefficient is then recursively estimated and closely tracked in real time by the proposed IAEKF. The contribution of this paper is that an updated fading-factor matrix is considered in the IAEKF, and the adaptive noise error covariance matrices are determined via an optimization procedure rather than by experience. The effectiveness of the proposed method is demonstrated by the numerical model of a real-world cable-supported bridge and an experimental scaled steel stay cable. Results indicate that the proposed method can identify the time-varying cable force in real time when the cable acceleration of only one measurement point is available.

Adaptive stochastic gradient descent, which uses unbiased samples of the gradient with stepsizes chosen from the historical information, has been widely used to train neural networks for computer vision and pattern recognition tasks. This paper revisits the theoretical aspects of two classes of adaptive stochastic gradient descent methods, which contain several existing state-of-the-art schemes. We focus on the presentation of novel findings: In the general smooth case, the nonergodic convergence results are given, that is, the expectation of the gradients’ norm rather than the minimum of past iterates is proved to converge; We also studied their performances under Polyak-Łojasiewicz property on the objective function. In this case, the nonergodic convergence rates are given for the expectation of the function values. Our findings show that more substantial restrictions on the steps are needed to guarantee the nonergodic function values’ convergence (rates). [ABSTRACT FROM AUTHOR]

With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impact-increment method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy. [ABSTRACT FROM AUTHOR]

Real-time taxi–passenger matching plays a critical role in modern taxi dispatch systems. Currently, the greedy strategy is widely adopted, which limits the quality of the service (QoS) and the profit of the entire system. There are two crucial tasks in this system: 1) the pairwise prioritization and 2) the matching of taxi–passenger pairs. In this paper, we develop a two-stage taxi–passenger matching system to deal with these two tasks. In the first stage, we design a fuzzy controller to assign a priority score to each taxi–passenger pair in real time. To ensure its performance on providing good QoS and profit, the fuzzy controller is optimized by an offline differential evolution algorithm. New individual representation is designed to optimize the membership functions and fuzzy rule base simultaneously. To accelerate the optimization process, the algorithm is implemented in a parallel way. Then, in the second stage, considering the priority scores as weights in the bipartite graph of taxi and passenger sets, we further apply a polynomial Kuhn–Munkres algorithm to find the maximum weight perfect matching in the bipartite graph. Simulated results validate the effectiveness of the proposed algorithm, which is able to enhance the QoS provided by the taxi system and improve the profit gained by the taxi service company. [ABSTRACT FROM AUTHOR]

Accelerating the inference of CNNs is critical to their deployment in real-world applications. Among all pruning approaches, the methods of implementing a sparsity learning framework have shown effectiveness as they learn and prune the models in an end-to-end data-driven manner. However, these works impose the same sparsity regularization on all filters indiscriminately, which can hardly result in an optimal structure-sparse network. In this paper, we propose a Saliency-Adaptive Sparsity Learning (SASL) approach for further optimization. A novel and effective estimation of each filter, i.e., saliency, is designed, which is measured from two aspects: the importance for prediction performance and the consumed computational resources. During sparsity learning, the regularization strength is adjusted according to the saliency, so our optimized format can better preserve the prediction performance while zeroing out more computation-heavy filters. The calculation for saliency introduces minimum overhead to the training process, which means our SASL is very efficient. During the pruning phase, in order to optimize the proposed data-dependent criterion, a hard sample mining strategy is utilized, which shows higher effectiveness and efficiency. Extensive experiments demonstrate the superior performance of our method. Notably, on ILSVRC-2012 dataset, our approach can reduce 49.7% FLOPs of ResNet-50 with very negligible 0.39% top-1 and 0.05% top-5 accuracy degradation. [ABSTRACT FROM AUTHOR]

With the increasing of the data size and the development of multi-core computers, asynchronous parallel stochastic optimization algorithms such as KroMagnon have gained significant attention. In this paper, we propose a new Sparse approximation and asynchronous parallel Stochastic Variance Reduced Gradient (SSVRG) method for sparse and high-dimensional machine learning problems. Unlike standard SVRG and its asynchronous parallel variant, KroMagnon, the snapshot point of SSVRG is set to the average of all the iterates in the previous epoch, which allows it to take much larger learning rates and also makes it more robust to the choice of learning rates. In particular, we use the sparse approximation of the popular SVRG estimator to perform completely sparse updates at all iterations. Therefore, SSVRG has a much lower per-iteration computational cost than its dense counterpart, SVRG++, and is very friendly to asynchronous parallel implementation. Moreover, we provide the convergence guarantees of SSVRG for both strongly convex and non-strongly convex problems, while existing asynchronous algorithms (e.g., KroMagnon and ASAGA) only have convergence guarantees for strongly convex problems. Finally, we extend SSVRG to non-smooth and asynchronous parallel settings. Numerical experimental results demonstrate that SSVRG converges significantly faster than the state-of-the-art asynchronous parallel methods, e.g., KroMagnon, and is usually more than three orders of magnitude faster than SVRG++. [ABSTRACT FROM AUTHOR]

In this paper, the dynamic balance of a rigid variable speed rotor is tested and analyzed. The vibration acceleration is measured by vibration analyzer instrumentations. The rotor adjustment parameters of counterweight, pitch, and trailing-edge flap are considered. The amplitude and phase of the 1 Ω vibration acceleration are analyzed through an all-phase fast Fourier transform. The experiments are conducted using two rigid rotors with the same geometry. The accelerations of the fuselage in the x ,   y , and z directions are measured. Through a waterfall diagram of the auto-power spectrum, it is found that the imbalance of counterweight, pitch, and trailing-edge flap causes an obvious increase in 1 Ω and 2 Ω acceleration. The hub counterweight mainly causes the lateral and longitudinal vibration in the disc plane, and the aerodynamic factors such as pitch and trailing-edge flap mainly affect the vertical vibration. In order to achieve dynamic balance for variable speed rotors, the counterweight adjustment should be given the highest priority for the vibration in the disc plane, and the pitch and trailing-edge flap adjustment should be given the highest priority for the vertical vibration. The results obtained from this experiment may be helpful toward reasonable designs of variable speed rotor helicopters. [ABSTRACT FROM AUTHOR]

This paper presents verification of frequency-response analysis (FRA) and vibroacoustic-method (VM) test methods complementarity for the assessment of the mechanical condition of a transformer's active part. Experiments performed on real power transformers under field conditions are discussed. The presented results cover three cases of faults which would be difficult to detect or correctly interpret with the application of a single method only. The first case shows the interfering influence of radiators on VM results. In the second case, a loosened winding with unchanged geometry, which cannot be detected by the FRA method, is discussed. The third presented case shows the results of an experiment based on introducing faults into the active part followed by FRA and VM tests. These faults were loosening of the core and loosening of winding with its slight stretching. The first fault could only be detected, as expected by VM results analysis, while the second one was confirmed by both methods; however, FRA assessment quality depends on the method of test data comparison. [ABSTRACT FROM PUBLISHER]

This paper presents new work regimes accompanied by specific conduction models of an SOI nanotransistor with a vacuum cavity. The tunneling mechanisms are separately explored to find out the dominant mechanism. Afterward, the simulations show for the first time two firms on and off states under the gate command. Strong and weak tunneling regimes are emphasized. For the first time, a quasi-saturation region of the ID – V\mathrm {\mathrm {DS}} curves is obtained for V\mathrm {\mathrm {DS}}> 6 V. Different device structures are compared. The best configuration has the swing of 290 mV/decade, threshold voltage of −0.5 V and maximum I\mathrm{\scriptscriptstyle ON}/I\mathrm{\scriptscriptstyle OFF} ratio of 10^\mathrm \mathrm 10 , which is a real gain among the vacuum transistors. Some applications as vacuum diode, switch under the gate command or action as parasitic device are emphasized. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the transient response of Lorentz force at finite magnetic Reynolds numbers Rm on an electrically conducting rectangular bar that is strongly accelerated in the presence of a localized magnetic field. This is done through numerical simulations utilizing a coupled finite-difference boundary element approach. The results show good qualitative agreement with existing experiments with a circular cylinder. The Lorentz force rise time is seen to be a linear function of Rm . The linear dependence of Lorentz force on Rm is found to be valid only for low values of Rm , after which the slope decays leading to an apparent saturation in the Lorentz force at sufficiently large values of Rm . Our results provide important information for the development of Lorentz force flow meters for transient flow applications. [ABSTRACT FROM PUBLISHER]

This paper presents the principle and complete characterization of a single-chip unit formed by microelectromechanical system magnetometers to sense the 3-D magnetic field vector and a Tang resonator. The three sensors, nominally with the same resonance frequency, are operated 200-Hz off-resonance through an ac current whose reference frequency is provided by the resonator embedded in an oscillating circuit. The sensors gain is increased by adopting a current recirculation strategy using metal strips directly deposited on the structural polysilicon. At a driving value of 100 \mu \textA\mathrm{ rms} flowing in series through the three devices, the magnetometers show a sub-185 nT/ $\vphantom {{\sqrt {\mathrm{ Hz}}}^{a}}\sqrt {\mathrm{ Hz}}$ resolution with a selectable bandwidth up to 50 Hz. Over a ±5-mT full-scale range, the sensitivity curves show linearity errors lower than 0.2%, with high cross-axis rejection and immunity to external accelerations. Under temperature changes, the stability of the 200-Hz difference between the magnetometers and the resonator frequency is within 55 ppm/K. Offset is trimmed down to the microtesla range, with an overall measured Allan stability of about 100 nT at 20-s observation time. [2016-0030] [ABSTRACT FROM PUBLISHER]

Automotive collision avoidance (CA) systems help drivers to avoid collisions through autonomous interventions by braking or steering. If the decision to intervene is made too early, the intervention can become a nuisance to the driver, and if the decision is made too late, the safety benefits of the intervention will be reduced. The decision to intervene is commonly based on a threat function. The dimensionality of the input state space for the threat function is, in general, very large, making exhaustive evaluation in real vehicles intractable. This paper presents a method for efficient estimation of a conservative bound on CA system performance, i.e., the worst-case performance. Closed-form expressions are derived for the worst-case performance, in terms of early or unnecessary interventions, with regard to longitudinal or lateral prediction and measurement errors. In addition, we derive closed-form expressions for robust avoidance scenarios, in which no unnecessary intervention will occur. For a system example, numerical results show how decision timing and robustness depend on scenario and system parameters. The method can be used for defining system requirements, system verification, system tuning, or system sensitivity analysis with regard to scenario variations and sensor measurement errors. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for time-varying parameter adaptive throttle and brake control for vehicle speed tracking. A control algorithm has been developed based on a linearized longitudinal vehicle model with characteristic lumped parameters. The lumped parameters are slowly time varying, except when a vehicle experiences gear shift. Combined parameter adaptation and throttle/brake control algorithm have been developed. The performance of the proposed control algorithm has been evaluated via simulations and vehicle tests. Since the proposed control algorithm has been designed using a generic form of the vehicle model, it can be implemented for different classes of vehicles with no information about the vehicle powertrain and the brake system. It has been shown from both simulations and vehicle tests that the vehicle speed tracking performance is robust to external disturbance. [ABSTRACT FROM PUBLISHER]

The paper describes application of unmanned robot applied to automotive test (URAT) to save time, costs, and to improve accuracy of tests. A hierarchical coordinated control method based on fuzzy logic theory is proposed for URAT, to realize the coordinated control and the accurate speed tracking of driving test cycle during all kinds of conditions. The system structure is briefly described in the paper. Similar to a skilled human driver, a control method based on Saridis hierarchical architecture to coordinate multiple robot manipulators systems for the automotive test system is presented. The coordinated movements for throttle mechanical leg, clutch mechanical leg, brake mechanical leg are designed. On top of that, the fuzzy speed controller for URAT is used to accurately track the desired vehicle velocity under different test conditions. Experiments have been conducted by using a Ford FOCUS car. The proposed control method of URAT is experimentally proved and compared with other control methods and with human driver performances. [ABSTRACT FROM PUBLISHER]

Eco-driving at signalized intersections has significant potential for energy saving. In this paper, we focus on eco-departure operations of connected vehicles equipped with an internal combustion engine and a step-gear automatic transmission. A Bolza-type optimal control problem (OCP) is formulated to minimize engine fuel consumption. Due to the discrete gear ratio, this OCP is a nonlinear mixed-integer problem, which is challenging to handle by most existing optimization methods. The Legendre pseudospectral method combining the knotting technique is employed to convert it into a multistage interconnected nonlinear programming problem, which then solves the optimal engine torque and transmission gear position. The fuel-saving benefit of the optimized eco-departing operation is validated by a passenger car with a five-speed transmission. For real-time implementation, a near-optimal departing strategy is proposed to quickly determine the behavior of the engine and transmission. When a string of vehicles are departing from an intersection, the acceleration of the leading vehicle(s) should be considered to control the following vehicles. This issue is also addressed in this paper. [ABSTRACT FROM PUBLISHER]

Accelerated life tests (ALTs) are widely used in industry to assist in product development. Acceleration models are often obtained from physical principles or past experience. But in some applications, particularly for investigating a new material or a new product, their acceleration models cannot be precisely specified. The uncertainty in model specification may cause serious problems in failure time prediction, and reduce the statistical efficiency of an optimal test plan. In this paper, the D and Ds optimal criteria are proposed for designing ALT plans that are good at selecting the best acceleration model among rival models. A generalized linear model (GLM) is developed for modeling ALT data with censoring. This approach simplifies the derivation of the information matrix of a test plan, and allows the experimenter to develop optimal ALT plans under the GLM framework. The proposed optimal design approach is compared with other conventional approaches through examples. The high design efficiency and design flexibility of the proposed approach are demonstrated in the paper. [ABSTRACT FROM PUBLISHER]