Pluggable multitask diffractive neural networks based on cascaded metasurfaces

Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Coordinated Capacitor Voltage Balancing Method for Cascaded H-bridge Inverter with Supercapacitor and DC-DC Stage

Cascaded H-bridge inverter(CHBI) with supercapacitors(SCs) and dc-dc stage shows significant promise for medium to high voltage energy storage applications. This paper investigates the voltage balance of capacitors within the CHBI, including both the dc-link capacitors and SCs. Balance control over the dc-link capacitor voltages is realized by the dcdc stage in each submodule(SM), while a hybrid modulation strategy(HMS) is implemented in the H-bridge to balance the SC voltages among the SMs. Meanwhile, the dc-link voltage fluctuations are analyzed under the HMS. A virtual voltage variable is introduced to coordinate the balancing of dc-link capacitor voltages and SC voltages. Compared to the balancing method that solely considers the SC voltages, the presented method reduces the dc-link voltage fluctuations without affecting the voltage balance of SCs. Finally, both simulation and experimental results verify the effectiveness of the presented method.

Model Predictive Control for Cascaded H-Bridge PV Inverter with Capacitor Voltage Balance

We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc-ing control methods,the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control.Besides,the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking.A cost function was con-structed to achieve the high-precision grid-connected control of the CHB inverter.Finally,the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules.

Inner Cascaded U^(2)-Net:An Improvement to Plain Cascaded U-Net

Deep neural networks are now widely used in the medical image segmentation field for their performance superiority and no need of manual feature extraction.U-Net has been the baseline model since the very beginning due to a symmetricalU-structure for better feature extraction and fusing and suitable for small datasets.To enhance the segmentation performance of U-Net,cascaded U-Net proposes to put two U-Nets successively to segment targets from coarse to fine.However,the plain cascaded U-Net faces the problem of too less between connections so the contextual information learned by the former U-Net cannot be fully used by the latter one.In this article,we devise novel Inner Cascaded U-Net and Inner Cascaded U^(2)-Net as improvements to plain cascaded U-Net for medical image segmentation.The proposed Inner Cascaded U-Net adds inner nested connections between two U-Nets to share more contextual information.To further boost segmentation performance,we propose Inner Cascaded U^(2)-Net,which applies residual U-block to capture more global contextual information from different scales.The proposed models can be trained from scratch in an end-to-end fashion and have been evaluated on Multimodal Brain Tumor Segmentation Challenge(BraTS)2013 and ISBI Liver Tumor Segmentation Challenge(LiTS)dataset in comparison to related U-Net,cascaded U-Net,U-Net++,U^(2)-Net and state-of-the-art methods.Our experiments demonstrate that our proposed Inner Cascaded U-Net and Inner Cascaded U^(2)-Net achieve better segmentation performance in terms of dice similarity coefficient and hausdorff distance as well as get finer outline segmentation.

Logformer: Cascaded Transformer for System Log Anomaly Detection

Modern large-scale enterprise systems produce large volumes of logs that record detailed system runtime status and key events at key points.These logs are valuable for analyzing performance issues and understanding the status of the system.Anomaly detection plays an important role in service management and system maintenance,and guarantees the reliability and security of online systems.Logs are universal semi-structured data,which causes difficulties for traditional manual detection and pattern-matching algorithms.While some deep learning algorithms utilize neural networks to detect anomalies,these approaches have an over-reliance on manually designed features,resulting in the effectiveness of anomaly detection depending on the quality of the features.At the same time,the aforementioned methods ignore the underlying contextual information present in adjacent log entries.We propose a novel model called Logformer with two cascaded transformer-based heads to capture latent contextual information from adjacent log entries,and leverage pre-trained embeddings based on logs to improve the representation of the embedding space.The proposed model achieves comparable results on HDFS and BGL datasets in terms of metric accuracy,recall and F1-score.Moreover,the consistent rise in F1-score proves that the representation of the embedding spacewith pre-trained embeddings is closer to the semantic information of the log.

一种新的非线性光学现象——Cascaded二级非线性光学效应

从Maxwell方程组出发 ,研究了一种新的非线性光学效应———Cascaded二级非线性现象 ,推导了依赖于光强的折射率变化———类克尔效应 ,分析了Cascaded非线性系数依赖于基波波长及波矢失配的变化规律

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

A distributed VSG control method for a battery energy storage system with a cascaded H-bridge in a grid-connected mode

With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role in renewable energy integration.In this paper,a distributed virtual synchronous generator(VSG)control method for a battery energy storage system(BESS)with a cascaded H-bridge converter in a grid-connected mode is proposed.The VSG is developed without communication dependence,and state-of-charge(SOC)balancing control is achieved using the distributed average algorithm.Owing to the low varying speed of SOC,the bandwidth of the distributed communication networks is extremely slow,which decreases the cost.Therefore,the proposed method can simultaneously provide inertial support and accurate SOC balancing.The stability is also proved using root locus analysis.Finally,simulations under different conditions are carried out to verify the effectiveness of the proposed method.

Adaptive Cascaded High-Resolution Source Localization Based on Collaboration of Multi-UAVs

Effective information fusion is very important in hybrid source localization. In this paper, the performance analysis of conventional joint direction of arrival(DOA) and time difference of arrival(TDOA) system is derived and it is shown that this hybrid system may inferior to the single system when the ratio of angular measurements error to distance measurements error exceeds a threshold. To avoid this problem, an effective DOA/TDOA adaptive cascaded(DTAC) technique is presented. The rotation feature of UAVs and spatial filtering technique are applied to gain the signal-to-noise ratio(SNR), which leads to more accurate estimation of time delay by using DOAs. Nevertheless, the time delay estimation precision is still limited by the sampling frequency, which is constrained by the finite load of UAV. To break through the limitation, an enhanced self-delay-compensation(SDC) method is proposed, which aims at detecting the overlooked time delay within the sampling interval by adding a tiny time delay. Finally, the position of the source is estimated by the Chan algorithm. Compared to DOA-only algorithm, TDOA-only algorithm and joint DOA/TDOA(JDT) algorithm, the proposed method shows better localization accuracy regardless of different SNRs and sampling frequencies. Numerical simulations are presented to validate the effectiveness and robustness of the proposed algorithm.

Three-wavelength generation from cascaded wavelength conversion in monolithic periodically poled lithium niobate

Tunable coherent emission is generated in a single-pass, cascaded wavelength conversion process from mode-locked laser-pumped monolithic periodically poled lithium niobate（PPLN）. Three ranges of wavelength, including visible output from 628 nm to 639 nm, near-infrared output from 797 nm to 816 nm, and mid-infrared output from 3167 nm to 3459 nm,were obtained from the monolithic PPLN, which consists of a 10-mm section for 532-nm-pumped optical parametric generation（OPG） and a 7-mm section for 1064-nm-pumped sum frequency generation（SFG）. A pump-to-signal conversion efficiency of 23.4% for OPG at 50°C and a quantum efficiency of 26.2% for SFG at 200°C were obtained.

Characteristics of Single Cathode Cascaded Bias Voltage Arc Plasma

A single cathode with a cascaded bias voltage arc plasma source has been developed with a new quartz cathode chamber,instead of the previous copper chambers,to provide better diagnostic observation and access to the plasma optical emission.The cathode chamber cooling scheme is also modified to be naturally cooled only by light emission without cooling water to improve the optical thin performance in the optical path.A single-parameter physical model has been developed to describe the power dissipated in the cascaded bias voltage arc discharge argon plasmas,which have been investigated by utilizing optical emission spectroscopy（OES） and Langmuir probe.In the experiments,discharge currents from 50 A to 100 A,argon flow rates from 800 sccm to 2000 sccm and magnetic fields of 0.1 T and 0.2 T were chosen.The results show：（a） the relationship between the averaged resistivity and the averaged current density exhibits an empirical scaling law as η∝ j^（-0.63369） and the power dissipated in the arc has a strong relation with the filling factor;（b） through the quartz,the argon ions optical emission lines have been easily observed and are dominating with wavelengths between 340 nm and 520 nm,which are the emissions of Ar^＋-434.81 nm and Ar^＋-442.60 nm line,and theintensities are increasing with the arc current and decreasing with the inlet argon flow rate;and（c） the electron density and temperature can reach 2.0 × 10^19 m^-3 and 0.48 eV,respectively,under the conditions of an arc current of 90 A and a magnetic field of 0.2 T.The half-width of the ne radial profile is approximatively equal to a few Larmor radii of electrons and can be regarded as the diameter of the plasma jet in the experiments.

Measurement of electron density and electron temperature of a cascaded arc plasma using laser Thomson scattering compared to an optical emission spectroscopic approach

As advanced linear plasma sources, cascaded arc plasma devices have been used to generate steady plasma with high electron density, high particle flux and low electron temperature. To measure electron density and electron temperature of the plasma device accurately, a laser Thomson scattering（LTS） system, which is generally recognized as the most precise plasma diagnostic method, has been established in our lab in Dalian University of Technology. The electron density has been measured successfully in the region of 4.5？×10^19m^-3 to7.1？×10^20m^-3 and electron temperature in the region of 0.18 eV to 0.58 eV. For comparison,an optical emission spectroscopy（OES） system was established as well. The results showed that the electron excitation temperature（configuration temperature） measured by OES is significantly higher than the electron temperature（kinetic electron temperature） measured by LTS by up to 40% in the given discharge conditions. The results indicate that the cascaded arc plasma is recombining plasma and it is not in local thermodynamic equilibrium（LTE）. This leads to significant error using OES when characterizing the electron temperature in a non-LTE plasma.

Optical encryption with cascaded fractional wavelet transforms

On the basis of fractional wavelet transform, we propose a new method called cascaded fractional wavelet transform to encrypt images. It has the virtues of fractional Fourier transform and wavelet transform. Fractional orders, standard focal lengths and scaling factors are its keys. Multistage fractional Fourier transforms can add the keys easily and strengthen information se-curity. This method can also realize partial encryption just as wavelet transform and fractional wavelet transform. Optical reali-zation of encryption and decryption is proposed. Computer simulations confirmed its possibility.

Ultra-broadband absorber based on cascaded nanodisk arrays

An ultra-broadband perfect absorber consisting of cascaded nanodisk arrays is demonstrated by placing insulatormetal-insulator-metal nanodisks on insulator-metal film stacks.The absorber shows over 90% absorption in a wavelength range between 600 nm and 4000 nm under transverse magnetic(TM) polarization,with an average absorptivity of 91.5%and a relative absorption bandwidth of 147.8%.The analysis of the electric field and magnetic field show that the synergy of localized surface plasmons,propagating surface plasmons,and plasmonic resonant cavity modes leads to the ultrabroadband perfect absorption,which accords well with the results of impedance-matched analysis.The influences of structural parameters and different metal materials on absorption performance are discussed.Furthermore,the absorber is polarization-independent,and the absorption remains more than 90% at a wide incident angle up to 400 under TE polarization and TM polarization.The designed ultra-broadband absorber has promising prospects in photoelectric detection and imaging.

An on-line free handwritten Chinese character recognition method based on component cascaded HMMs

This paper presents a cascaded Hidden Markov Model （HMM）, which allows state＇s transition, skip and duration. The cascaded HMM extends the way of HMM pattern description of Handwritten Chinese Character （HCC） and depicts the behavior of handwritten curve more reliably in terms of the statistic probability. Hence character segmentation and labeling are unnecessary. Viterbi algorithm is integrated in the cascaded HMM after the whole sample sequence of a HCC is input. More than 26,000 component samples are used tor training 407 handwritten component HMMs. At the improved training stage 94 models of 94 Chinese characters are gained by 32,000 samples, Compared with the Segment HMMs approach, the recognition rate of this model tier the tirst candidate is 87.89% and the error rate could be reduced by 12.4%.

Cascaded plasmonic nanorod antenna for large broadband local electric field enhancement

We propose a cascaded plasmonic nanorod antenna for large broadband electric near-field enhancement. The structure has one big gold nanorod on each side of a small two-wire antenna which consists of two small gold nanorods. For each small nanorod, the enhanced and broadened optical response can be obtained due to the efficient energy transfer from its adjacent big nanorod through strong plasmonic near-field coupling. Thus, the electric field intensity of the cascaded antenna is significantly larger and broader than that of the individual small two-wire antenna. The resonant position, field intensity enhancement, and spectral width of the cascaded antenna are highly tunable by varying the geometry of the system. The quantum efficiency of the cascaded antenna is also greatly enhanced compared with that of the small antenna. Our results are important for the applications in field-enhanced spectroscopy.

Signal-Pressure Curves of Cascaded Four-Wave Mixing in Gas-Filled Capillary by fs Pulses

The theoretical framework for the cascaded four waves mixing (CFWM) in gas-filled capillary by fs pulses is constructed. Based on the theoretical framework, the signal-pressure curves (SPC) of the CFWM in gas-filled capillary by fs pulses are calculated. With a comparison between the theoretical and experimental SPC we have discussed the influence of the walk-off and Phase modulation on the SPC. At the same time, we have discussed the possible origin of the first three peaks of the SPC.

Theory of noise in a kilo-Hz cascaded high-energy Yb-doped nanosecond pulsed fiber amplifier

A theoretical analysis of noise in a high-power cascaded fiber amplifier is presented. Unlike the noise theory in low power communication, the noise of a high power system is redefined as the leaked output energy between pulses with coherent beat noise uncounted. This definition is more appropriate for high power usage in which the pulse energy receives more attention than the pulse shape integrity. Then the low power pre-amplifying stages are considered as linear amplification and analyzed by linear theory. In the high-power amplification stages, the inversion is assumed to recover linearly in the time interval between pulses. The time shape of the output pulse is different from that of the input signal because of different gains at the front and back ends of the pulse. Then, a criterion is provided to distinguish the nonlinear and linear amplifications based on the signal-to-noise ratio （SNR） analysis. Then, an experiment that shows that the output SNR actually drops off in nonlinear amplification is performed. The change in the noise factor can be well evaluated by pulse shape distortion.

Evaluating logic functionality of cascaded frac

Look Up Tables(LUTs) are the key components of Field-Programmable Gate Arrays(FPGAs)Many LUT architectures have been studied; nevertheless, it is difficult to quantificationally evaLUT based architecture. Traditionally, dedicated efforts on specific modifications to the temapping tools are required for LUT architecture evaluation. A more feasible evaluation method forfunctionality is strongly required for the design of LUT architecture. In this paper, a mathematical for logic functionality calculation is proposed and conventional and fracturable LUT architectanalyzed. Furthermore, a cascaded fracturable LUT architecture is presented, which achieves twice functionality compared with the conventional LUTs and fracturable LUTs.