Design of Network Cascade Structure for Image Super-Resolution

Image super resolution is an important field of computer research.The current mainstream image super-resolution technology is to use deep learning to mine the deeper features of the image,and then use it for image restoration.However,most of these models mentioned above only trained the images in a specific scale and do not consider the relationships between different scales of images.In order to utilize the information of images at different scales,we design a cascade network structure and cascaded super-resolution convolutional neural networks.This network contains three cascaded FSRCNNs.Due to each sub FSRCNN can process a specific scale image,our network can simultaneously exploit three scale images,and can also use the information of three different scales of images.Experiments on multiple datasets confirmed that the proposed network can achieve better performance for image SR.

Population inversion study of GaAs/AlGaAs three-quantum-well quantum cascade structures

A population inversion study of GaAs/AlxGa1-xAs three-quantum-well quantum cascade structures is presented. We derive the population inversion condition （PIC） of the active region （AR） and discuss the PICs on different structures by changing structural parameters such as the widths of quantum wells or barriers in the AR. For some instances, the PIC can be simplified and is proportional to the spontaneous emission lifetime between the second and the first excited states, whereas some other instances imply that the PIC is proportional to the state lifetime of the second excited state.

An Optimal DF Based Method for Transient Stability Analysis

The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased.The capacity of the synchronous generators to keep working without losing synchronization when the system is exposed to severe faults such as short circuits is referred to as the power system’s transient stability.As the power system’s safe and stable operation and mechanism of action become more complicated,higher demands for accurate and rapid power system transient stability analysis are made.Current methods for analyzing transient stability are less accurate because they do not account formisclassification of unstable samples.As a result,this paper proposes a novel approach for analyzing transient stability.The key concept is to use deep forest(DF)and a neighborhood rough reduction approach together.Using the neighborhood rough sets,the original feature space is obtained by creating many optimal feature subsets at various granularity levels.Then,by deploying the DF cascade structure,the mapping connection between the transient stability state and the features is reinforced.The weighted voting technique is used in the learning process to increase the classification accuracy of unstable samples.When contrasted to current methods,simulation results indicate that the proposed approach outperforms them.

A STA Current-Constrained Control for PMSM Speed Regulation System with Function Disturbance Observer

The non-cascade permanent magnet synchronous motor control system has the advantages of simple structure and less adjustable parameters,but the non-cascade structure needs to solve the problem of over-current protection.In this paper,a current constrained control method is used to limit the starting current to a safe range.At the same time,to ensure the robustness and rapidity of the system,a super twist current constraint controller(CCSTA)is generated by combining super twist algorithm(STA)with current constraint control;Considering the diversity of internal and external disturbances,a functional disturbance observer(FDOB)is proposed to compensate the matched and unmatched disturbances,which further improves the robustness of the system.

Temperature Control System with Multi-closed Loops for Lithography Projection Lens

Image quality is one of the most important specifications of optical lithography tool and is affected notably by temperature, vibration, and contamination of projection lens（PL）. Traditional method of local temperature control is easier to introduce vibration and contamination, so temperature control system with multi-closed loops is developed to control the temperature inside the PL, and to isolate the influence of vibration and contamination. A new remote indirect-temperature-control（RITC） method is proposed in which cooling water is circulated to perform indirect-temperature-control of the PL. Heater and cooler embedded temperature control unit（TCU） is used to condition the temperature of the cooling water, and the TCU must be kept away from the PL so that the influence of vibration and contamination can be avoided. A new multi-closed loops control structure incorporating an internal cascade control structure（CCS） and an external parallel cascade control structure（PCCS） is designed to prevent large inertia, multi-delay, and multi-disturbance of the RITC system. A nonlinear proportional-integral（PI） algorithm is applied to further enhance the convergence rate and precision of the control process. Contrast experiments of different control loops and algorithms were implemented to verify the impact on the control performance. It is shown that the temperature control system with multi-closed loops reaches a precision specification at ±0.006 ℃ with fast convergence rate, strong robustness, and self-adaptability. This method has been successfully used in an optical lithography tool which produces a pattern of 100 nm critical dimension（CD）, and its performances are satisfactory.

Quantum dot quantum cascade photodetector using a laser structure

We report on a quantum dot quantum cascade detector（QD-QCD）, whose structure is derived from a QD cascade laser. In this structure, more ordered In As QD layers formed in the Stranski-Krastanow growth mode on a thin Ga As buffer layer are incorporated into the active region. This QD-QCD can operate up to room temperature with a peak detection wavelength of 5.8 μm. A responsivity of 3.1 mA/W at 160 K and a detectivity of 3.6 × 10~8 Jones at 77 K are obtained. The initial performance of the detector is promising, and, by further optimizing the growth of InA s QDs, integrated QD-quantum cascade laser/QCD applications are expected.

Group-housed pigs and their body parts detection with Cascade Faster R-CNN

The detection of individual pigs and their parts is a key step to realizing automatic recognition of group-housed pigs’behavior by video monitoring.However,it is still difficult to accurately locate each individual pig and their body parts from video images of groups-housed pigs.To solve this problem,a Cascade Faster R-CNN Pig Detector(C-FRPD)was designed to detect the individual pigs and different parts of their body.Firstly,the features were extracted by 101-layers Residual Networks(ResNet-101)from video images of group-housed pigs,and the features were input into the region proposal networks(RPN)to obtain the region proposals.Then classification and bounding box regression on region proposals were performed to get the location of each pig.Finally,the body parts of the pig were determined by using the Cascade structure to search on the feature map of the pig body area.These operations completed the detection of the whole body of each pig and its different parts of the body,and established the association between the whole and parts of body in the end-to-end detection.In this study,1500 pig pen images were trained and tested.The test results showed that the detection accuracy of C-FRPD reached 98.4%.Compared with the Faster R-CNN without cascade structure,the average detection accuracy was increased by 4.3 percentage points.The average detection time of a single image was 259 ms.The method in this study could accurately detect and correlate the individual pig with its head,back,and tail in the image.This method can provide a technical reference for recognizing the behavior of group-housed pigs.

Near-infrared and mid-infrared semiconductor broadband light emitters

Semiconductor broadband light emitters have emerged as ideal and vital light sources for a range of biomedical sensing/imaging applications,especially for optical coherence tomography systems.Although near-infrared broadband light emitters have found increasingly wide utilization in these imaging applications,the requirement to simultaneously achieve both a high spectral bandwidth and output power is still challenging for such devices.Owing to the relatively weak amplified spontaneous emission,as a consequence of the very short non-radiative carrier lifetime of the inter-subband transitions in quantum cascade structures,it is even more challenging to obtain desirable mid-infrared broadband light emitters.There have been great efforts in the past 20 years to pursue high-efficiency broadband optical gain and very low reflectivity in waveguide structures,which are two key factors determining the performance of broadband light emitters.Here we describe the realization of a high continuous wave light power of 420 mW and broadband width of 4130 nm with near-infrared broadband light emitters and the first mid-infrared broadband light emitters operating under continuous wave mode at room temperature by employing a modulation p-doped InGaAs/GaAs quantum dot active region with a‘J’-shape ridge waveguide structure and a quantum cascade active region with a dual-end analogous monolithic integrated tapered waveguide structure,respectively.This work is of great importance to improve the performance of existing near-infrared optical coherence tomography systems and describes a major advance toward reliable and costeffective mid-infrared imaging and sensing systems,which do not presently exist due to the lack of appropriate low-coherence mid-infrared semiconductor broadband light sources.