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To retrieve the information from the serious distorted received signal is the key challenge of communication signal processing. The chaotic baseband communication promises theoretically to eliminate the inter-symbol interference (ISI), however, it needs complicated calculation, if it is not impossible. In this paper, a genetic algorithm support vector machine (GA-SVM) based symbol detection method is proposed for chaotic baseband wireless communication system (CBWCS), by this way, treating the problem from a different viewpoint, the symbol decoding process is converted to be a binary classification through GA-SVM model. A trained GA-SVM model is used to decode the symbols directly at the receiver, so as to improve the bit error rate (BER) performance of the CBWCS and simplify the symbol detection process by removing the channel identification and the threshold calculation process as compared to that using the calculated threshold to decode symbol in the traditional methods. The simulation results show that the proposed method has better BER performance in both the static and time-varying wireless channels. The experimental results, based on the wireless open-access research platform, indicate that the BER of the proposed GA-SVM based symbol detection approach is superior to the other counterparts under a practical wireless multipath channel., 31 pages, 16 figures

Chaos has been successfully applied in many fields to improve the performance of engineering systems, such as communication, vibration compact, and mixing. Generating chaos from originally non-chaotic systems is a relevant topic because of potential applications. In this work, the impulse control is shown to generate chaos from non-chaotic system. Using non-chaotic Chen system as an example, we prove by analytical and numerical methods that chaos is indeed generated. The features of the chaos generated by impulse control are analysed using Lyapunov exponents, bifurcation diagram, power spectrum, Poincare mapping and Kaplan-Yorke dimension. Furthermore, we demonstrate the chaotic attractor generation by impulse control using a circuit experiment. The last but not minor point is that the existence of topological horseshoe is given by rigorous computer-aided proof.

The power electronic converters are typical nonlinear systems. The conventional linearized modeling methods cannot accurately describe the working process of the converter. The control strategies based on the linearized model can only achieve good performance near the working point. By considering the switching nonlinear system nature of the converters, the main contributions of this article are as follows: a current error switching model is developed for the three-phase voltage source rectifiers (VSRs) under unbalanced grid for the first time; and an improved stability analysis theorem is proved for the switching control of the three-phase VSRs under unbalanced grid condition. These contributions are used to design a simple current switching controller for VSRs. The main advantages of the proposed modeling and control strategy are as follows. The switching model of the converter is built without any approximation. It accurately describes the physical working principle of the three-phase VSR under unbalanced grid condition. The proposed current switching controller has a very simple control structure. The switching states of the converter are directly produced according to the switching rule. There are no control parameters, no complicated rotation transformation, and no voltage vector modulation in the proposed switching controller. The proposed switching controller is not sensitive to the circuit parameters. The robustness of the control system is improved without any extra compensators or observers. Simulation and experiment verifies the correctness, the effectiveness, and the superiority of the proposed theory and methodology.

Anaerobic digestion is promising for waste activated sludge (WAS) degradation. However, conventional processes were generally stuck with limited hydrolysis and poor pathogen destruction. Hyperthermophilic digestion at 70 °C has drawn attention in overcoming those issues at a relatively low energy requirement and operating difficulties. In order to illuminate its operation characteristics, a single-stage hyperthermophilic digester was controlled at 70 °C and operated continuously to degrade WAS. 88.7 mL/g VSadded of methane yield could be achieved in the hyperthermophilic system, fourfold higher than that in the mesophilic system. Kinetic analysis revealed that hyperthermophilic digestion was advantageous in converting the non-degradable fraction. Consequently, hydrolysis under the hyperthermophilic condition was able to be significantly improved. Above 10 d was necessary for the hyperthermophilic system to gain such a high methane production. In the case of stability, the organic loading of higher than 10.2 g VS/L/d resulted in increasing limitation from methanogenesis and accumulation of propionic, butyric and valeric acids. In addition to the dominant acetoclastic genus Methanothrix for methane production in the hyperthermophilic system, two hydrogenotrophic methanogens Methanospirillum and Methanothermobacter reached 18.84% and 8.31%, respectively. The genus Coprothermobacter, affiliated with the phylum Firmicutes, made more contribution to protein hydrolysis in the hyperthermophilic digester.

Tungsten(VI) oxide (WO3) with excellent charge transport properties and intrinsic thermal and chemical robustness is a promising anode interface material instead of PEDOT:PSS in organic solar cells (OSCs). Herein, a solution-processed, ultraviolet-irradiation-derived WO3 film as anode interface layer (AIL) is developed based on tungsten(VI) chloride (WCl6) as precursor. The WO3 film is derived from the solution-processed precursor film with simple ultraviolet-irradiation treatment, and the preparation process without high-temperature annealing is very compatible with large-scale production and flexible substrate. The composition of the WO3 film is analyzed by X-ray photoelectron spectroscopy. ITO modified by the WO3 film, namely ITO/WO3, exhibits similarly high optical transmittance as that of bare ITO. The work function of ITO/WO3 measured by ultraviolet photoelectron spectroscopy is obviously lower than that of bare ITO, which can facilitate effective holes extraction. In addition, the WO3 film possesses relatively smooth and hydrophobic surface, beneficial to form excellent interface contact with active layer. Moreover, non-fullerene OSCs based on the WO3 film as AIL are studied with typical and relatively low-cost PBDB-T:ITIC as active layer. The optimal efficiency (8.70%) of the device based on ITO/WO3 is dramatically higher than that (3.32%) of the device based on bare ITO, and comparable to that (8.80%) of the device based on ITO/PEDOT:PSS. Therefore, the solution-processed, ultraviolet-irradiation-derived WO3 film as AIL should have great potential to realize high-performance non-fullerene OSCs, which can also inspire a novel and promising route to prepare other transition metal oxide films in optoelectronic devices.

A Triaxial creep experiment was performed with Chengdu clay. The results demonstrate that the deformation of clay includes instantaneous elastic strain, attenuated creep deformation, steady creep deformation, and accelerated creep deformation. In view of the nonlinear properties of creep, an improved nonlinear viscous element describing attenuating creep and an improved fractional order viscous element describing accelerating creep are established, and a one-dimensional nonlinear fractional order five-element creep model is developed with the two improved elements. The model can theoretically describe the entire process of creep. The nonlinear fractional order five-element model and the traditional five-element model were employed to verify the creep test. Compared with the traditional five-element creep model, the nonlinear fractional order creep model more faithfully reproduces the experimental data and more accurately describes the deformation trend in each stage, especially the accelerated creep stage.

This letter studies the impact of network-coded multiple access (NCMA) on the outage performance of full-duplex cooperative non-orthogonal multiple access (NOMA). In particular, we propose a network-coded cooperative NOMA (NC-CNOMA) strategy, under which user devices utilize physical-layer network coding (PNC) to demodulate signals with greater probability. The exact analytical expression of the outage probability is derived to evaluate the performance of the proposed scheme. The provided simulation results validate our analysis and the proposed NC-CNOMA scheme outperforms the conventional cooperative NOMA with regard to outage performance.

In this paper, we study a downlink non-orthogonal multiple access (NOMA) transmission system, where a novel network-coded interference cancellation (NCIC) scheme is proposed to promote the outage performance. In order to further improve the outage performance, an adaptive NCIC (A-NCIC) scheme is also studied, which dynamically switches between successive interference cancellation (SIC) and the proposed NCIC schemes according to the power allocation factors and target data rates. The expressions of the outage probability are derived to evaluate the performance of the proposed scheme. The simulation results demonstrate the remarkable performance of the proposed NCIC scheme over the conventional SIC-based NOMA on the outage probability.

Crane operations might be very dangerous in rough sea conditions due to unexpected payload swing induced by ship excitations. In this paper, a novel Cable-Driven Inverted Tetrahedron Mechanism (CDITM) is presented to suppress the payload swing for sake of the workers’ safety. The CDITM retrofitting on an offshore crane is simplified as a constrained pendulum with a moving base, and its equations of motion are obtained by Newton Euler Method. Next, three-dimensional dynamic analysis is performed using Matlab/Simulink, and the influence law of ship excitations, tagline tension, crane pose and CDITM configuration on the payload swing are investigated. Finally, through comparative experimental verification, it is found that the simulation tendencies of in-plane swing follows the experiment curves quite well, and the variations between the simulation and experiment results are acceptable. Thus the dynamic modeling and analysis of CDITM are verified. The theoretical and experimental results are fundamental and valuable for the engineering application of CDITM in the offshore industries.

In the Boost converter, the equivalent series resistance (ESR) of the output capacitor, may cause output voltage ( v o ) jumps, that are not modeled commonly in the literature. These jump discontinuities in v o , lead to performance issues in switching surface (SS) controllers. In this paper, these ESR effects are modeled using switched systems with state jumps, called jump-flow switched (JFS) systems. Furthermore, it is shown that approximating the capacitor voltage ( v c ), with v o , can cause undesired limit cycles, oscillations, chattering or instability issues. To resolve these issues, a non-jumping normal switched system is defined for JFS systems, that is equivalent to the internal continuous dynamics. Simulation and experimental results show the fast and robust responses of the controller board with Boost converter.

Most existing endmember extraction techniques require prior knowledge about the number of endmembers in a hyperspectral image. The number of endmembers is normally estimated by a separate procedure, whose accuracy has a large influence on the endmember extraction performance. In order to bridge the two seemingly independent but, in fact, highly correlated procedures, we develop a new endmember estimation strategy that simultaneously counts and extracts endmembers. We consider a hyperspectral image as a hyperspectral pixel set and define the subset of pixels that are most different from one another as the divergent subset (DS) of the hyperspectral pixel set. The DS is characterized by the condition that any additional pixel would increase the likeness within the DS and, thus, reduce its divergent degree. We use the DS as the endmember set, with the number of endmembers being the subset cardinality. To render a practical computation scheme for identifying the DS, we reformulate it in terms of a quadratic optimization problem with a numerical solution. In addition to operating as an endmember estimation algorithm by itself, the DS method can also co-operate with existing endmember extraction techniques by transforming them into a novel and more effective schemes. Experimental results validate the effectiveness of the DS methodology in simultaneously counting and extracting endmembers not only as an individual algorithm but also as a foundation algorithm for improving existing methods. Our full code is released for public evaluation. 1 1 https://github.com/xuanwentao/DivergentSubset

Hydrogen energy and polymer electrolyte membrane (PEM) fuel cells become concerned issues in recent years. Nevertheless, the construction of hydrogen refueling infrastructure and hydrogen storage and transportation constrains the commercial development of fuel cells. In this review, sources, production, storage, transportation, and purification methods of hydrogen are extensively reviewed and compared. The advantages of utilizing industrial by-product hydrogen and steam reforming gas in PEM fuel cell systems are analyzed. Using industrial wasted hydrogen can significantly reduce the cost of hydrogen. Also, it is indicated that the onboard hydrogen generation by steam methanol reforming can solve the difficulties of efficient storage and transportation of gaseous hydrogen, which means that methanol has great potential to be a convenient carrier of hydrogen. The effects of impurities contained in the reformate gas are generally introduced. After the methanol steam reforming and pretreatment purification processes, the reformate gas can be fed to PEM fuel cells. Thus, a fuel cell system integrated with onboard hydrogen production and impure hydrogen treatment subsystems is introduced, and key technologies therein for pretreatment purification and in-situ poisoning mitigation methods are reviewed. Finally, suggestions are proposed for further studies.

Anode materials based on transition metal sulfides suffer from poor electrochemical reversibility, which limits their cycling stability. Herein, we synthesize hollow I-Cu2MoS4 nanocubes composed of ultrathin nanosheets using a solvothermal method with Cu2O nanocubes as sacrificial templates. The presence of a surfactant is a key factor that prevents the structural collapse of the hollow cubic structure of Cu2MoS4 and the formation of nanoplates. An ether-based electrolyte shows better compatibility with the Cu2MoS4 electrode than a carbonate-based electrolyte, which is reflected in high reversible capacity, superior rate performance, and remarkably improved cycling performance. Ex-situ XRD analysis demonstrates a highly reversible electrochemical reaction in the ether-based electrolyte, which enhances the cycling stability.

Fast and accurate remote sensing image retrieval from large data archives has been an important research topic in the remote sensing research literature. Recently, hashing-based remote sensing image retrieval has attracted extreme attention because of its efficient search capabilities. Especially, deep remote sensing image hashing algorithms have been developed based on convolutional neural networks (CNNs) and have shown effective retrieval performance. However, implementing a deep hashing network tends to be highly expensive in terms of storage space and computing resources to be suitable for on-orbit remote sensing image retrieval, which usually operates on resource-limited devices such as satellites and unmanned aerial vehicles (UAVs). To address this limitation, we propose to hash a deep network that in turn hashes remote sensing images. Specifically, we develop a quantized deep learning to hash (QDLH) framework for large-scale remote sensing image retrieval. The weights and activation functions in the QDLH framework are binarized to low-bit representations, which require comparatively much less storage space and computing resources. The QDLH results in a lightweight deep neural network for effective remote sensing image hashing. We conduct extensive experiments on two public remote sensing image data sets by incorporating several state-of-the-art network architectures into our QDLH methodology for remote sensing image hashing. The experimental results demonstrate that the proposed QDLH is effective in saving hardware resources in terms of both storage and computation. Moreover, superior remote sensing image retrieval performance is also achieved by our QDLH, compared with state-of-the-art deep remote sensing image hashing methods.

An M-ary Differential Chaos Shift Keying modulation using Chaotic Shape-forming Filter (CSF-M-DCSK) is proposed here to transmit two sub-streams with different system performances. The chaotic shape-forming filter is used to generate the chaotic carrier which is modulated according to the DCSK concept. The modulated chaotic signal is demodulated by a coherent matched filter receiver and the maximum likelihood decision rule is used to get the best noise performance. Compared to DCSK and its enhanced versions, the new modulation scheme offers not only better noise and multipath performances but also a higher data rate. The hardware implementation of the proposed method is as simple as that of a conventional communication system. Analytical expressions have been derived for the CSF-M-DCSK Bit Error Rate (BER) and its performance has been evaluated in AWGN and multipath channels by simulations. The new CSF-M-DCSK system has been implemented and successfully tested on a Wireless open-Access Research Platform (WARP). Results of simulations and measurements performed in real application scenarios have proven the feasibility and superiority of CSF-M-DCSK over its competitors.

In this paper, a simple extended Kalman Filter (EKF) controller for direct torque control (DTC) of a six-phase induction machine in all speed ranges is proposed. The aim of this paper is to decrease the execution time of EKF modeling of a six-phase induction motor. The proposed method is fast and can operate online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find parameters used for controlling the motor. In low speed, not only the motor speed measurement but also the DTC of machine is difficult. The EKF model can estimate speed, flux, load torque, and stator resistance in low speed; thus, optimization can be performed in all loads and speed range. The proposed method increases the accuracy of DTC of the six-phase induction machine and decreases the computation cost of the system using the simplified algorithm. The simulation and experimental results verify the effectiveness and the robustness of the proposed method against parameter variations.

Ambient backscatter which utiliees the ambient radio-frequency signals to enable transmissions between battery-less devices has attracted considerable attention in academia and industry. This study addresses the questions of full-duplex (FD) and self-interference cancellation (SIC) for ambient backscatter which adopts dual-antenna structure to achieve persistent information transmission and energy harvesting. The authors construct the physical-layer network coding (PNC) mapping principle of on–off keying in the dual-antenna structure and propose the PNC-based FD algorithm to eliminate the self-interference in the information domain. Furthermore, the bit-error-ratio and throughput performances are analysed under conventional half-duplex mode and the proposed FD mode, respectively. In order to facilitate system complexity and reduce power consumption, they design a hardware prototype to achieve SIC which consists of low-power passive analogue components. Numerical results are provided to confirm the theoretical studies. Circuit simulations demonstrate that the circuit is commendably consistent with the design concept.

We develop a hierarchical generative adversarial network (HGAN) for generating future typhoon cloud remote sensing images, which enables a visual means to typhoon cloud prediction. The HGAN consists of a global generator and a local discriminator. The global generator aims at producing the future typhoon cloud images as realistic as possible and accordingly reveals the structure and future location of the typhoon clouds. It is constructed in terms of a hierarchical architecture with multiple subnetworks, which capture the overall typhoon variations and favor generating clear future typhoon cloud images. The local discriminator tries its best to distinguish generated typhoon cloud images from ground-truth ones, based on the local patches. The local procedure encourages the discriminator to focus on characterizing the moving typhoon clouds rather than the still background. The global generator and the local discriminator are trained in an adversarial fashion with respect to historical typhoon cloud image sequences. The trained HGAN is capable of producing reliable visual predictions that are not only enabled by the global generator and but also examined by the local discriminator. Experiments validate the effectiveness of the HGAN for typhoon cloud prediction.

Two-dimensional metal dichalcogenides show a promising potential in energy storage due to their high specific capacity. Different from the bulk SnS prepared by conventional solvothermal method, our strategy to prepare the three-dimensional (3D) hierarchical SnS@N-doped carbon (SnS@NC) microspheres assembled from ultrathin nanosheets is realized by the polymer-assisted solvothermal method. The key factor of SnS@NC microspheres is the use of polyvinylpyrrolidone, which not only acts as surfactant to obtain the hierarchical spherical structure but also is used as heteroatom sources to realize the N-doped carbon layer coating. Compared with the bulk SnS, the enhanced electrochemical performance of SnS@NC electrode can be attributed to its 3D hierarchical structure and composition advantages, including enhanced Li+ diffusion kinetics, faster charge transfer, enough void space to accommodate the volume variation, higher electronic conductivity, and more active sites.

The dynamic failure of carbon/epoxy sandwich plates with polyvinyl chloride foam core subjected to foam projectile impact is experimentally analyzed in this research. The effects of intensity of impact impulse, cores density, core thickness on the impact resistance of the composite sandwich plates in terms of deflection of rear sheets are also assessed. The 3D- digital image correlation technique is applied to measure the dynamic deformation of the sandwich plates. The results show that the carbon/epoxy sandwich plates exhibit more excellent impact resistance than aluminum sandwich plates with polyvinyl chloride cores at the similar area mass. The carbon/epoxy sandwich plates experience an obvious spring back, and only a slight plastic deflection can be observed after test. The failure modes of the sandwich plates include plastic deformation, fiber breakage, delamination, matrix crack, debonding, and compression of cores. The damage of plates become more serious with core density and core thickness decreasing, and impact impulse increasing, respectively.

This study presents a new higher-order refined analysis model for static and free vibration analysis of a sandwich plate with soft functionally graded material core. The governing equations are derived from equilibrium differential equations of motions. The accuracy and convergence of the present model and numerical solution are validated versus available results. Variable length width ratios, thickness ratios between skins and core and span-to-thickness of sandwich plates have been studied. Obtained results show that suggested model can achieve greater accuracy for sandwich plates with soft functionally graded material core, as compared to existing functionally graded sandwich plate analysis models and models based on finite element method. Finally, parametric study has been carried out to investigate influence of volume fraction distribution, thickness to side ratio and material properties on the plate bending and free vibration.

Photocatalytic water splitting taking the advantage of using solar energy directly is one of the most effective strategies for hydrogen evolution. The development of facile methods for synthesizing highly efficient and stable photocatalysts for hydrogen production still remains a great challenge. Herein, a metal-organic framework (MOF)-templated strategy was designed for the synthesis of solid solutions of (Zn0.95Cu0.05)1-xCdxS that exhibit outstanding photocatalytic hydrogen production reaction activity. More importantly, efficient light capturing ability and photogenerated charges separation were accomplished via fine-tuning the composition of the photocatalysts by adjusting the concentrations of doping metals in the template MOFs. Under visible light (λ > 420 nm), an optimized nanocatalyst, (Zn0.95Cu0.05)0.6Cd0.4S, exhibited a higher durability and satisfied photocatalytic hydrogen evolution rate of 4150.1 μmol g-1 h-1 of water splitting.

In the satellite-based application, low signal-to-noise ratio (SNR) is a considerable obstacle for automatic dependent surveillance-broadcast (ADS-B), leading to some erroneous bit declarations. In this case, the confidence level of each bit should be declared legitimately to make full use of error correction. In this study, the authors focus on methods to optimise the confidence declaration for ADS-B signals with coherent demodulation scheme. A novel optimal-threshold labelling method is firstly proposed for known and unknown amplitudes. They also present a dynamic-threshold labelling method, in which a specific threshold is unnecessary. Detailed theoretical analyses are carried out for the proposed methods and are verified by simulations. Finally, they make a comparison between different confidence level labelling methods in terms of reception performance and complexity. A conclusion is set forth that the methods have a high probability of correct reception at low SNRs.

Small-aperture compact high-frequency surface wave radar (HFSWR) suffers from low azimuth accuracy for target detection due to its wide beamwidth. Multitarget tracking (MTT) algorithms, when applied to the raw target detection data of HFSWR, fail to effectively filter the target azimuths, and thus, resulting in inaccurate target tracks and courses. In this article, a vessel azimuth and course joint re-estimation method by exploring Doppler velocity and the information accumulated from consecutive observations is presented. It begins with applying an MTT algorithm to a measured target states data sequence acquired by HFSWR to establish initial target tracks, from which the measured range, azimuth, and radial velocity data sequences are obtained. Then, the azimuth trend is extracted from the obtained azimuth data sequence as roughly corrected azimuth estimates, with which the target locations are roughly corrected. Subsequently, target speeds and initial courses are estimated based on the roughly corrected location data sequence, followed by a data selection procedure based on proposed control parameter rules to select the qualified data for calculating the projected angles in terms of speed and direction, separately. Eventually, the target azimuth data sequence is further refined using a linear azimuth error model, whose parameters are obtained by minimizing the difference between the projected angles using a constrained optimization method. Experimental results from field data demonstrate that the proposed method can estimate the target azimuths with significantly improved accuracy. The deviations of the corrected target locations are considerably reduced, and the accuracy of course estimation is enhanced.

Thorium is much more abundant than uranium in nature and has become one of the important potential energy sources in the future. It is because that a thorium-232(232Th) nucleus has the ability to produce a uranium-233(233U) nucleus by absorbing a neutron. The aim of this paper is to investigate the extraction and separation of thorium ions and uranyl ions from aqueous solution with N,N’-dimethyl-N,N’-dioctyl-4-oxaheptanediamide (DMDOHA) into ionic liquids of 1-methyl-3-butylimid-azolium bis(trifluoromethanesulfonyl)imide ([C4mim][NTf2]). The results show that the extractant DMDOHA has a good affinity toward thorium ions than uranyl ions in the present system, the maximum value of separation factor SFTh(IV)/U(VI) is 21.9 at pH 2.24. The extraction process of thorium ions and uranyl ions was confirmed to proceed by cation-exchange extraction mechanism. The DMDOHA extractant formed a major 3:1 complex with thorium ion and a major 2:1 complex with uranyl ion based on the relationship between log[DMDOHA] with logD.

To improve the accuracy and efficiency of measuring fracturing proppant sphericity and roundness, a measurement scheme is designed by combining fuzzy connectedness and shape similarity. Firstly, in the proppant images collected by the microscope, according to the color characteristics of the test placement plane's hole and proppant, the region of each proppant and that of the hole without proppant are marked separately. Secondly, based on the feature of holes without proppant, the statistical method of labeling connected components is used to only reserve all the proppant regions. Thirdly, select a part of the region of each proppant as the seed region to calculate the fuzzy connectedness map between seed regions and other regions. Fourthly, select the appropriate connectedness threshold for each proppant based on histogram of fuzzy connectedness map of each proppant region to obtain the accurate region of each proppant. Finally, the shape similarity measurement method based on Hu moment is used to determine the sphericity and roundness of each proppant by measuring the similarity between the region of each proppant and that of 20 particles in the standard template. The experimental results show that the proposed scheme is consistent with manual measurement flow, and can avoid the human labor, meanwhile, the accuracy of measurement is basically consistent with the results of manual measurement.

Orthogonal matching pursuit (OMP) is an efficient method for decomposing a seismic trace with regard to an atom dictionary. The original OMP optimizes one unique single objective in terms of successively maximizing the inner product between an atom and its corresponding residual at different approximating levels. Though the inner product effectively measures signal similarity at a global time scale, it tends to neglect localizing an atom whose peak position plays a key role in seismic reconstruction. To address this limitation, we propose a peak colocalized orthogonal matching pursuit (PCOMP) strategy that optimizes two objectives, i.e., signal correlation and peak colocalization, both of which are defined based on signal residuals and atoms. Compared with the original OMP, the PCOMP extends a much larger search space in favor of more accurate seismic reconstruction. In this scenario, the genetic algorithm (GA) used for solving the original OMP is not suitable for the PCOMP. Therefore, we propose to solve the two objective optimization problem by exploiting an improved nondominated sorting genetic algorithm (NSGA-II) algorithm, which not only increases the diversity of searching for optimization and but also reduces the reconstruction error over the GA. Furthermore, the constrained atom positions obtained from the peak colocalization objective enable efficient convergence. Experiments for seismic data validate the advantages of the proposed PCOMP.

This paper proposes a simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges. The proposed method is fast and can be operated online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find the parameters to ensure optimal efficiency operation. Not only is the motor speed measurement difficult at low speeds but it is also difficult to calculate the machine efficiency at the same speeds. Thus, the EKF model can estimate speed, load, and motor efficiency at low speed ranges so that optimization can be done in all loads and speed ranges. Unlike the conventional LMC method, the proposed method is independent of parameter variations. Because of the independency of this method against the parameter variations, it works similarly to the search based efficiency control methods. Two DSP boards including estimator and controller are used to achieve high accuracy and speed in estimating and controlling machines. The simulation and experimental results verify the robustness of the sensorless method against parameter variations.

Beetle antennae search (BAS) is a newly developed meta-heuristic algorithm which is effectively used for optimizing objective functions of complex forms or even unknown forms. The common practice for implementing meta-heuristic algorithms including the BAS largely relies on programming in a high-level language and executing the code on a computer platform. However, the high-level implementation of the BAS algorithm hinders it from being used in an embedding system, where real-time operations are normally required. To address this limitation, we present an approach to implementing the BAS algorithm on a field-programmable gate array (FPGA). Specifically, we program the BAS function in the Verilog hardware description language (HDL), which provides a tractable vehicle for implementing the BAS algorithm at the gate level on the FPGA chip. We simulate our Verilog HDL based BAS module with the Modelsim platform. Simulation results validate the feasibility of our proposed Verilog HDL implementation of the BAS. Additionally, we implement the BAS model on the Zynq XC7Z010 platform, with $132.5~\mu $ s latency for model implementation.

With the development of control theory and the pneumatic element, the application of pneumatic systems has attracted more attention because of the performance to price ratio improvement. Despite of these, there are still challenge to deal with the nonlinearity of the system, the uncertainty of the parameters, the input saturation and the unknown control direction in the tracking control of pneumatic system. In this paper, the nonlinearity and model uncertainty are treated with adaptive radial basis function neural network (RBFNN), meanwhile, the unknown control direction and input saturation are dealt with the Nussbaum function and Gauss error function, respectively. The stability of the designed controller is proved by Lyapunov theory. Finally, the experimental and comparison results show the effectiveness and superiority of the proposed method.

In this letter, a new frequency selective surface is proposed, which is mainly applied to 5G communication. The equivalent circuit method is used to provide assistance for structural design. This structure can generate dual-frequency passbands and achieve double resonant frequencies 28.1 and 39.5 GHz. It acquires large enough bandwidths to cover 27.5–28.35 and 38.6–40 GHz, which are bands of 5G communication. In addition, this structure is a multi-layer structure composed of one metallic layer and two dielectric layers, and its unit size is 0.56λ × 0.56λ, where λ is the wavelength corresponding to the first resonant frequency. Simulated results show that this structure has excellent filtering properties with respect to polarization stability as well as angular stability. Finally, the prototype of this structure is fabricated. The measured results and simulated results have consistent filtering characteristics within the tolerance of error.

Model identification is divided into two parts: structure identification and parameter identification, and the parameter identification is actually an optimization process. For improving the optimization performance, in this paper, we firstly present a novel conjugate gradient descent method with a modified Armijo-type line search technique to train a Takagi-Sugeno fuzzy neural network model. Numerical simulations are implemented to demonstrate the efficiency of the proposed algorithm. According to the experimental comparisons that are evaluated over 15 classification and 3 regression problems, the advantages of the given method are superior to its another two counterparts. To complement the simulation results and help in establishing a robust fuzzy neural network model, we strictly prove two deterministic convergent behaviors of the presented algorithm, i.e., weak and strong convergence results. They indicate the gradient of the target function with respect to network weights converges to zero and the parameter sequence approaches a fixed optimal point, respectively.

Protein kinases, the main regulators of a vast map of cellular processes, are the most attractive targets in drug discovery. Despite a few successful examples of protein kinase inhibitors, the drug discovery strategy of downregulating protein kinase activity has been quite limited and often fails even in animal models. Here, we utilize protein kinase A (PKA) activity to design PKA-triggered supramolecular assemblies with anticancer activities. Grafting a suitable peptide to PNIPAM raises the critical temperature of the LCST polymer above body temperature. Interestingly, the corresponding phosphorylated polymer has a critical temperature below body temperature, making this peptide-appended PNIPAM a suitable polymer for the PKA-triggered supramolecular assembly process. PKA-triggered assembly occurs selectively in PKA-upregulated MCF-7 cells, which disturbs the cytoskeleton and sensitizes cancer cells against doxorubicin. The chemosensitization is also observed in vivo to identify effective tumor inhibitors with satisfactory biocompatibility. Overall, this phosphorylation-induced (in principle, PKA-catalyzed) supramolecular assembly opens up a promising chemotherapy strategy for combating kinase-upregulated cancer., A nonapeptide grafted LCST polymer undergoes enzymatic phosphorylation to assemble, which selectively disrupts PKA overexpressing cancer cells via kinetics targeting.

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

Offshore cranes are widely used for lifting operations at sea. However, due to the ship motions and crane operations, the payload swing is unavoidable, hence putting the operators in danger. Thus, this article proposes a novel triple-tagline system which has three taglines forming a triangle structure in the space and can suppress the payload swing in arbitrary directions. The kinematic and dynamic models are built in a systematic manner, which establish the theoretical basis of position synchronization and tension setting of the taglines. Then, dynamic analysis is carried out to explore the effect of the taglines’ tension on payload swing suppression, but it is unexpected to find that the taglines cannot suppress the dynamic payload swing if they always hold the static equilibrium condition. Furthermore, inspired by the air damping phenomenon, a damp-based tagline tension setting method is proposed to guarantee the resultant force of the taglines would always keep the tendency to damp the payload swing. At last, a tension/position hybrid control strategy is presented to prevent the interference of the taglines to crane operations. The validity of the proposed method and strategy are verified by experimental results.

The physical and chemical properties of metal nanomaterials are closely tied to their size and shape. A well-controlled synthesis protocol is needed to control over particle morphologies. Although the shape and size of metal nanostructures have been controlled by various pathways, such as soft templates and seed-mediated protocol method, most of the methods are involved with complicated multi-step synthesis. In this work, the morphology of palladium nanostructures, including nanorods, nanoparticles, and nanocubes, were well controlled by a simple one-step/one-pot polyol method in the presence of poly(vinylpyrrolidone) and KBr. A detailed study of the relationship between the morphology and controlling factors, such as reaction temperature, the concentration of metal precursor, PVP, reducing agent, and potassium bromide is presented. Well-controlled morphologies of Pd nanorods, nanospheres, and nanocubes are obtained via tuning these reaction parameters. The results from this work provide a basis for optimizing palladium nanocrystals growth through the simple one-pot/one-step polyol method.

Gas flow has fractional order dynamics; therefore, it is reasonable to assume that the pneumatic systems with a proportional valve to regulate gas flow have fractional order dynamics as well. There is a hypothesis that the fractional order control has better control performance for this inherent fractional order system, although the model used for fractional controller design is integer order. To test this hypothesis, a fractional order sliding mode controller is proposed to control the pneumatic position servo system, which is based on the exponential reaching law. In this method, the fractional order derivative is introduced into the sliding mode surface. The stability of the controller is proven using Lyapunov theorem. Since the pressure sensor is not required, the control system configuration is simple and inexpensive. The experimental results presented indicate the proposed method has better control performance than the fractional order proportional integral derivative (FPID) controller and some conventional integral order control methods. Points to be noticed here are that the fractional order sliding mode control is superior to the integral order sliding mode counterpart, and the FPID is superior to the corresponding integral order PID, both with optimal parameters. Among all the methods compared, the proposed method achieves the highest tracking accuracy. Moreover, the proposed controller has less chattering in the manipulated variable, the energy consumption of the controller is therefore substantially reduced.

The cathodic pressure drop is an effective indicator for detecting the water state in flow channels and gas diffusion layer of the proton exchange membrane fuel cell. Reducing current density is supposed to be the easiest way to cure the fuel cell from flooding. However, the relationship among pressure drop, current density and flooding has not been investigated, which is meaningful for preventing flooding, especially for the stationary power plant featuring constant condition and long-time operation. In this paper, the evolution of pressure drop, voltage, impedance, and water amount in terms of the resistance at different parts inside the fuel cell were analyzed quantitatively using a new equivalent circuit model, which could describe the water state more appropriately under large water amount. For one thing, when the flooding risk was diagnosed at different current densities, the cathodic resistance of catalyst layer was almost 238 mΩ·cm2, and the mass transfer resistance of the cathodic channels and gas diffusion layer was between 220 and 234 mΩ·cm2. It implied that pressure drop could be used to detect flooding. For another, the pressure drop could not return to the control line, but the more the current density decreased, the closer it approached to this line, which was verified by the impedance at different layers. In real application, the appropriate strategy of lowering current and diagnosis based on pressure drop could be selected for avoiding flooding in advance.

Short peptide cages have great potential applications in drug encapsulation and release because of excellent biocompatibility, biodegradability and multi-functionality originated from their abundant sequences. However, constructing short peptide cages are still a challenge, which is caused by the rapid kinetic and unlimited self-assembly behavior of short peptide in a macroscopical media. Herein, we developed smart procedures to produce short peptide cages, in which porous CaCO3 microparticles were used as enzyme (thermolysin) carriers and applied as catalyzers to promote the condensation reaction of Fmoc-Y and L-NH2 in confined space of water/n-hexane emulsion which limited the self-assembly behavior of Fmoc-YL-NH2 and allowed the peptide to just self-assemble on CaCO3 surface. Intact short peptide cages would be produced after the removing the templates.

To predict the anti-penetration performance of protective structures, the ballistic performance of sandwich plates with steel face-sheet and aluminum foam core, the quasi-static compressive experiments of four different aluminum foam are performed and analyzed. The failure mechanism, mechanical parameters, and modified constitutive model are obtained. The virtual tests using numerical simulation were carried out in different penetration velocities based on quasi-static experimental constitutive parameters. Influence of projectile shape, face-sheet thickness, core thickness, and core densities on the residual velocity and plastic deformation of sandwich plates are discussed, while typical penetration failure modes and deformation mechanism are presented and analyzed. The failure modes of sandwich plates are different for hemisphere- and blunted-nosed projectile and the projectile shape influence is significant for ballistic performance when the penetration velocity approaches ballistic limit. The ballistic limit increases with increase of face-sheet or core thickness, core density and which shows an approximate linear relationship.

We present a cofactor-based endmember extraction strategy for estimating green algae area in geostationary ocean color imager multispectral images. Our strategy improves the efficiency of the widely used N-FINDR endmember extraction method from two aspects. First, our strategy exploits the cofactor matrix for searching the largest simplex volume, which just computes matrix inverse and determinant for a small number of times (or even once). This is more efficient than the enumeration of determinants for all pixels in N-FINDR. Second, our strategy empirically obtains optimal endmembers through a few recursive iterations of cofactor matrix updates, contrasting a large number of repetitive volume maximizations with random initializations in N-FINDR. Experimental evaluation in terms of green algae area estimation validates that our strategy achieves the same accuracy as N-FINDR with much more efficiency.

The magnetic Fe3O4/BiOBr composites with different molar ratios were prepared by a new two-step method. The effect of different Fe3O4 contents on composites’ properties was detected through XRD, SEM, TEM, HR-TEM, XPS, Uv–vis DRS, PL and BET. When the molar ratio of Fe3O4 nanospheres and BiOBr nanosheets is 0.5:1, the two are combined regularly to form 3D flower-like hierarchical heterostructure. This phenomenon is firstly found and can provide a reference for synthesizing other regularly combined magnetic heterostructure catalysts. The degradation activity for Rhodamine B (RhB) is much stronger than that of the previous studies under visible-light irradiation. 3D flower-like Fe3O4/BiOBr (0.5:1) heterostructure possesses great advantages including excellent magnetic separation, remarkable reutilization and stability. Through active species detection and liquid chromatography mass spectrometry (LC-MS) analysis, the degradation mechanisms of RhB are summarized (a) RhB photosensitization and (b) RhB moleculs attacked by radicals and a new possible degradation path was to be presented. This study offers a new method to prepare a regularly combined magnetic Fe3O4/BiOBr photocatalytic material and demonstrates its wonderful application for degradation of organic contaminants in aquatic environment.

The desalination and purification of sea or brackish water by utilizing solar energy are considered to be the most feasible solutions to overcome the problems of water shortage and pollution. In this study, a bifunctional Cu2-xSe-decorated hierarchical TiO2 nanotube mesh (CTNM) was designed and synthesized successfully for both solar water evaporation and photodegradation. Cu2-xSe enhances solar light absorption and solar water evaporation performance as a low-cost absorber because of its localized surface plasmon resonance (LSPR) effect. Meanwhile, the formation of the p-Cu2-xSe/n-TiO2 heterojunction improves the photodegradation performance by increasing separation and transport of photogenerated charge carriers. Hence, CTNM has a relatively high solar water evaporation conversion efficiency of 83.06% and also can photodegrade 95% of methyl orange after 3 h under 2.5 kW m−2 simulated solar irradiation, which demonstrate the extremely high utilization ratio of solar energy of CTNM.

Integrating nano-sized WS2 with conductive network has been extensively investigated for lithium-ion batteries (LIBs) and demonstrated to be effective. Herein, a 3D flexible graphene foam@carbon nanotubes@WS2 (GF@CNTs@WS2) hybrid has been prepared for LIBs anode applications. The components of GF, CNTs and WS2 in the hybrid foam can offer numerous open channels for the easy access of electrolyte, enhanced flexibility and conductivity, and active sites for electrochemical reactions, respectively. When evaluated as an anode material for LIBs, the GF@CNTs@WS2 electrode delivers a specific capacity of 931 mAh g−1 at a current density of 0.1 A g−1, high reversible capacity of 525 mAh g−1 after 500 cycles at 0.2 A g−1. Moreover, we believe this structural design can open up a route for electrodes design in advanced flexible energy-storage devices.

Magnetic element is the basic component of matrix in high gradient magnetic separation (HGMS), and its configurative parameters such as size have marked effects on the capture efficiency of the matrix. Therefore, the geometric design of the element should be matched with the properties of the material to be separated, to optimize the HGMS performance. In this work, the capture of independent magnetic particles on a cylindrical element in pulsating HGMS process was theoretically described, and their size matching ratios (magnetic element to particle) under the maximum capture probability and critical capture conditions were specifically discussed. These theoretically calculated size ratios were much larger than that (2.69) in the literatures available, but generally consistent with those obtained from pulsating HGMS applications. The theoretical analysis were basically validated by the actual capture of ilmenite and hematite particles on cylindrical elements, using an experimental magnetic capture method. According to the new theoretical model, the size matching ratio is not fixed at the value of 2.69. It depends on the properties of the material to be separated such as volume magnetic susceptibility and the operating parameters of a HGMS process such as magnetic induction and flow velocity through the magnetic element. This theoretical description provides a new fundamental understanding in the size matching between magnetic element and particle, and would contribute to the solution of size matching issue in the real capture situation considering the interactions between magnetic particles, and therefore to the optimal design and operations of matrix in HGMS applications.

Pyran is fused into the planar donor moiety to enhance the extinction coefficient and reduce the bandgap, thus two acceptors PTTIC and PTBT-R are designed and synthesized. Compared to the IDT-based acceptor, these pyran-bridged acceptors show higher the highest occupied molecular orbital level and wider absorption coverage. Devices fabricated with poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b′]dithiophene)-co-(1,3-di(5-thiophene-2-yl)-5,7-bis(2-ethylhexyl)-benzo[1,2-c:4,5-c′]dithiophene-4,8-dione)] (PBDB-T):PTTIC as the active layer give a power conversion efficiency (PCE) of 7.35%.

Learning to hash is a popular technique for fast similarity search on a large-scale image database. However, many hashing methods do not achieve satisfactory results because of the quantization loss in the straightforward binary code generation procedure. In order to address this problem, we propose a novel hash code reconstruction framework for existing unsupervised hashing methods. In our proposed approach, the hash codes are generated through reconstructing the original images with relaxed hamming vector representation, such that the final learned codes will be more approximate to characterize the intrinsic image structure. Moreover, our proposed hash code reconstruction algorithm is very efficient for computing, which can be generalized to various hashing methods. Extensive experiments are conducted on four public image datasets by incorporating our proposed scheme with different hashing methods, and the comparison results have shown that significant performance improvements can be achieved with minor additional time cost for fast similarity search task.

Metal-air fuel cells are regarded as potential alternatives of power supply due to their high specific energy. However, the excessive accumulation of reaction products leads to performance degradation, low energy density, and short service life, hampering more widespread application. This study focuses on enormously increasing the fuel cell system energy density by electrolyte isolation and management. Filters are used to isolate metal oxide (including ZnO, MgO, and Al2O3) from supersaturated electrolyte solutions in fuel cells. The filtration efficiency is close to 100%. The flow field is optimized to suppress the anode passivation. In zinc-air fuel cells (ZAFCs), the ratio of discharge capacity to electrolyte volume (electrolyte capacity) is up to 1025 Ah L−1, and the discharging voltage still remains stable. The zinc-air fuel cell system (ZAFCS) exhibits high energy density, high stability, and low cost, rendering this type of metal-air fuel cell a promising energy storage in electric vehicles.

Water failures, which can be diagnosed with alternating-current impedance, is harmful to output properties and durability of the proton exchange membrane fuel cell. In this paper, an impedance-based measuring method of the zero-phase ohmic resistance is presented, which adjusts the measuring frequency to confine the impedance point within the ±3° sampling limitation area so as to guarantee the accuracy of 0.01 mΩ. The zero-phase ohmic resistance is sensitive to the membrane dehydration, and it decreases in the flooding process due to the gradual liquid water accumulation in the catalyst layer. The fluctuation of the zero-phase ohmic resistance increases in the flooding process, owing to the water state variation resulting from increasingly frequent water removal. A semi-empirical equivalent circuit model is used to analyze the change of mass transfer in the flooding process, and it is found that the diffusion resistance and the dissolution resistance of the reactant increase sharply. The fixed-low-frequency resistance is applicable in the flooding diagnosis, whose sensitivity changes with the chosen frequency. The highest sensitivity is corresponding to the peak value of the impedance magnitude. This paper provides adequate information about the water fault diagnosis, making sense to the fault-avoidance and the durability-promotion of the fuel cell.

The extraction behavior and mechanism of uranium(VI) from aqueous solution with the multidentate ligand N,N,N″′,N″′-tetraoctyl-N″,N″-ethidene diglycolamide (TOE-BisDGA) as extractant were investigated. The extraction percentages of uranium(VI) were found to increase with increasing aqueous nitric acid solution. The extraction process was deduced to proceed by neutral extraction mechanism or ion association extraction mechanism, and the TOE-BisDGA extractant formed a major 1:1 complex with uranium(VI) in xylene system. The possible molecular structure of extracted pieces were presumed to be [UO2(NO3)2(TOE-BisDGA)] or [UO2(TOE-BisDGA)](NO3)2 or [UO2(NO3)TOE-BisDGA)](NO3) by ESI–MS and extraction mechanism.