Novel orange-red Sr_(2)GdSbO_(6):xEu^(3+)(x=0,0.05,0.1,0.2,0.3,0.4,0.5 and 0.6) phospho rs were successfully prepared by the traditional high-temperature solid-state *** results of Rietveld refinement,energy dispersiv...
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Novel orange-red Sr_(2)GdSbO_(6):xEu^(3+)(x=0,0.05,0.1,0.2,0.3,0.4,0.5 and 0.6) phospho rs were successfully prepared by the traditional high-temperature solid-state *** results of Rietveld refinement,energy dispersive spectroscopy(EDS) spectrum and elemental mapping demonstrate that Eu^(3+) successfully replaces the Gd^(3+) sites and distributes uniformly in the particles of *** luminescence properties of Sr_(2)GdSbO_(6):Eu_(3+)phosphors were investigated in *** emission spectra of the strongest emission peak is the ^(5)D_(0)→^(7)F_(1)(593 nm) transition,which can emit orange-red light under393 nm *** the doping concentration of Eu3+ions is x=0.2,the luminescence intensity of the phosphors reaches the *** detailed mechanism of concentration quenching is attributed to dipole-dipole *** thermal stability values of Sr_(2)GdSbO_(6):0.2Eu^(3+) phosphors are 87%,82% and114% under 393,467 and 527 nm excitations,*** causes of the abnormal thermal quenching under 527 nm excitation were *** on the abnormal thermal quenching under527 nm excitation,the optical thermometry properties of Sr_(2)GdSbO_(6):0.2Eu^(3+)phosphors were investigated by fluorescence intensity ratio(FIR) technique,and appreciable relative sensitivity was *** results suggest that Sr_(2)GdSbO_(6):0.2Eu^(3+)phosphors can be potentially applied to w-LEDs and optical thermometers.
This paper considers the distributed online optimization(DOO) problem over time-varying unbalanced networks, where gradient information is explicitly unknown. To address this issue, a privacy-preserving distributed on...
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This paper considers the distributed online optimization(DOO) problem over time-varying unbalanced networks, where gradient information is explicitly unknown. To address this issue, a privacy-preserving distributed online one-point residual feedback(OPRF) optimization algorithm is proposed. This algorithm updates decision variables by leveraging one-point residual feedback to estimate the true gradient information. It can achieve the same performance as the two-point feedback scheme while only requiring a single function value query per iteration. Additionally, it effectively eliminates the effect of time-varying unbalanced graphs by dynamically constructing row stochastic matrices. Furthermore, compared to other distributed optimization algorithms that only consider explicitly unknown cost functions, this paper also addresses the issue of privacy information leakage of nodes. Theoretical analysis demonstrate that the method attains sublinear regret while protecting the privacy information of agents. Finally, numerical experiments on distributed collaborative localization problem and federated learning confirm the effectiveness of the algorithm.
Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF...
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Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.
Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving *** ...
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Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving *** vehicle instance segmentation can perform instance-level semantic parsing of vehicle information,which is more accurate and reliable than object ***,the existing instance segmentation algorithms still have the problems of poor mask prediction accuracy and low detection ***,this paper proposes an advanced real-time instance segmentation model named FIR-YOLACT,which fuses the ICIoU(Improved Complete Intersection over Union)and Res2Net for the YOLACT ***,the ICIoU function can effectively solve the degradation problem of the original CIoU loss function,and improve the training convergence speed and detection *** Res2Net module fused with the ECA(Efficient Channel Attention)Net is added to the model’s backbone network,which improves the multi-scale detection capability and mask prediction ***,the Cluster NMS(Non-Maximum Suppression)algorithm is introduced in the model’s bounding box regression to enhance the performance of detecting similarly occluded *** experimental results demonstrate the superiority of FIR-YOLACT to the based methods and the effectiveness of all *** processing speed reaches 28 FPS,which meets the demands of real-time vehicle instance segmentation.
Flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from ***,the problems related to the difficulty in obtaining ...
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Flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from ***,the problems related to the difficulty in obtaining abnormal data,low model accuracy,and high calculation cost have led to severe challenges with respect to its practical ***,in this study,firstly,several UAV flight data simulation softwares are presented based on a brief presentation of the basic concepts of anomalies,the contents of UAV flight data,and the public datasets for flight data anomaly ***,anomaly detection technologies for UAV flight data are comprehensively reviewed,including knowledge-based,model-based,and data-driven ***,UAV flight data anomaly detection applications are briefly described and ***,the future trends and directions of UAV flight data anomaly detection are summarized and prospected,which aims to provide references for the following research.
Accurate intervertebral disc image segmentation is necessary for further treatment. However, existing methods are difficult to segment due to the intensity inhomogeneity of intervertebral disc MRI images and the simil...
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The direct reduction process is an important development direction of low-carbon ironmaking and efficient comprehensive utilization of poly-metallic iron ore,such as ***,the defluidization of reduced iron particles wi...
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The direct reduction process is an important development direction of low-carbon ironmaking and efficient comprehensive utilization of poly-metallic iron ore,such as ***,the defluidization of reduced iron particles with a high metallization degree at a high temperature will seriously affect the operation of fluidized bed *** the pre-oxidation enhancing reduction and the particle surface modification of titanomagnetite,the behavior and mechanism of pre-oxidation improvement on fluidization in the fluidized bed reduction of titanomagnetite are systematically studied in this ***-oxidation treatment of titanomagnetite can significantly lower the critical stable reduction fluidization gas velocity to 0.17 m/s,which is reduced by 56%compared to that of titanomagnetite reduction without pre-oxidation,while achieving a metallization degree of>90%,Corresponding to the different reduction fluidization behaviors,three pre-oxidation operation regions have been divided,taking oxidation degrees of 26%and 86%as the *** on the particle surface morphology evolution in the pre-oxidation-reduction process,the relationship between the surface morphology of pre-oxidized ore and the reduced iron with fluidization properties is *** improving method of pre-oxidation on the reduction fluidization provides a novel approach to prevent defluidization by particle surface modification,especially for the fluidized bed reduction of poly-metallic iron ore.
1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromi...
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1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromisingperformance even competitive to many complete solvers in recent MaxSAT Evaluations.
In description logic,axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical *** recent years,SAT-based axiom pinpointing techniques,which rely on the enumeration of...
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In description logic,axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical *** recent years,SAT-based axiom pinpointing techniques,which rely on the enumeration of minimal unsatisfiable subsets(MUSes)of pinpointing formulas,have gained increasing *** with traditional Tableau-based reasoning approaches,SAT-based techniques are more competitive when computing justifications for consequences in large-scale lightweight description logic *** this article,we propose a novel enumeration justification algorithm,working with a replicated *** replicated driver discovers new justifications from the explored justifications through cheap literals resolution,which avoids frequent calls of SAT ***,when the use of SAT solver is inevitable,we adjust the strategies and heuristic parameters of the built-in SAT solver of axiom pinpointing *** adjusted SAT solver is able to improve the checking efficiency of unexplored *** proposed method is implemented as a tool named *** experimental results show that RDMinA outperforms the existing axiom pinpointing tools on practical biomedical ontologies such as Gene,Galen,NCI and Snomed-CT.
Due to their high-entropy effects,the high-entropy(HE)MAX-phase materials improve the comprehen-sive performance of MAX phases,opening up more possibilities for practical engineering ***,it is still challenging to obt...
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Due to their high-entropy effects,the high-entropy(HE)MAX-phase materials improve the comprehen-sive performance of MAX phases,opening up more possibilities for practical engineering ***,it is still challenging to obtain S-containing high-entropy MAX phases because of the high volatilization behavior of sulfur,suffering from issues such as high reaction temperature and long re-action time of traditional synthesis *** paper proposes a novel process named as liquid metal assistant self-propagating high-temperature synthesis(LMA-SHS)for efficient synthesis of high-purity S-containing high-entropy MAX-phase ***-melting-point metal(Sn or In)has been introduced into the raw mixture and melted into a liquid phase during the early stage of the SHS *** serv-ing as a"binder"between transition metal atoms of the M-site due to the negative mixing enthalpy,this liquid phase can accelerate mass and heat transfer during the SHS process,ensuring a uniform solid solution of each element and realizing the synthesis of high-purity(TiNbVZr)2SC in an extremely short *** synthesis method for high-entropy MAX-phase materials developed in this study,i.e.,LMA-SHS,showing very short reaction time,low energy consumption,high yield,and low cost,has the promise to be a general energy-and resource-efficient route towards high-purity HE materials.
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