Miracle-dz/UniFAR-FTUs huggingface dataset:
Carrier-Based Aircraft Steam Catapult Control System

In order to make the carrier-based aircraft take off smoothly, a steam catapult controller is designed in this paper. The thermodynamic model of the capacity selector valve, the steam storage cylinder and the cylinder, and the motion model of the carrier-based aircraft are built. Then the steam catapult controller is designed. Based on the feedback linearization theory, the cylinder system model can be fully linearized to achieve the state of the cylinder decoupling. The influence of various factors such as the change of the thermodynamic state in the steam storage cylinder, the change of the steam flow process, the opening and the circulation characteristics of the launching valve are taken into account. The program is capable of simulating the thermodynamic and kinetic parameters of a series of ejection processes. The simulation results show that the steam catapult controller designed by the feedback linearization method is stable in the process of ejection, so that the carrier-based aircraft can have good tracking ability to the acceleration command.
U-Net Based Moving Target Detection for Unmanned Air Vehicles

In this paper, a moving target detection problem is investigated for the unmanned air vehicles with a monocular vision sensor. First, a detection algorithm based on U-Net network is proposed to obtain the position and velocity direction of a moving target. Then, a Kalman Filter is incorporated into the proposed algorithm to increase the accuracy of states acquisition of the moving targets. Then, the experimental results show the proposed algorithm has low computation and better performance.
An Advanced Adaptive Control of Lower Limb Rehabilitation Robot

Rehabilitation robots play an important role in the rehabilitation field, and effective human-robot interaction contributes to promoting the development of the rehabilitation robots. Though many studies about the human-robot interaction have been carried out, there are still several limitations in the flexibility and stability of the control system. Therefore, we proposed an advanced adaptive control method for lower limb rehabilitation robot. The method was devised with a dual closed loop control strategy based on the surface electromyography (sEMG) and plantar pressure to improve the robustness of the adaptive control for the rehabilitation robots. First, in the outer loop control, an advanced variable impedance controller based on the sEMG and plantar pressure was designed to correct robot's reference trajectory. Then, in the inner loop control, a sliding mode iterative learning controller (SMILC) based on the variable boundary saturation function was designed to achieve the tracking of the reference trajectory. The experiment results showed that, in the designed dual closed loop control strategy, a variable impedance controller can effectively reduce trajectory tracking errors and adaptively modify the reference trajectory synchronizing with the motion intention of patients; the designed sliding mode iterative learning controller can effectively reduce chattering in sliding mode control and excellently achieve the tracking of rehabilitation robot's reference trajectory. This study can improve the performance of the human-robot interaction of the rehabilitation robot system, and expand the application to the rehabilitation field.
Development of a Tetris Playing Robot Controlled by KNR

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system.
Non-UV Patterning of Gelatin Methacryloyl Hydrogel by Optically Induced Electropolymerization

The microenvironment for culturing of cells is important in tissue engineering and biomedical applications. Owing to their excellent biocompatibility, hydrogels are widely used to create microenvironments. One of the most useful hydrogels, gelatin methacryloyl (GeIMA), can be cured by ultraviolet (UV) light to form a polymer. However, the use of a photoinitiator in this process results in cellular toxicity. In this study, we developed a novel method to polymerize GelMA hydrogel into desired patterns based on the principle of optically induced electropolymerization. For this technique, the polymer films were electrodeposited by optical virtual electrodes at the surface of a photoconductive substrate, instead of real conductive metallic electrodes. The shapes of the virtual electrodes depend on digitally projected images. The thickness of the deposited films, ranging from nanometers to micrometers, is controlled by the duration of the applied AC voltage. In this paper, we discuss the parameters used during the optically induced electropolymerization process to realize several microstructures of GelMA hydrogel with different shapes and sizes.
Maritime Target Detection Method Based on Deep Learning

For the problem of low recognition rate of traditional digital image processing in actual maritime target detection, an improved maritime target detection method based on deep convolution neural network is proposed. The maritime targets (mainly including fixed-wing aircraft, surface ships and helicopters under the background of sea and sky) are marked to establish the target datasets. The detection framework of maritime target based on Faster RCNN is given and improved by using the Resnet to extract the feature of target, and using the batch normalization layer to optimize the Faster RCNN network, using online hard-examples-mining algorithm to improve the training process. The training and test experiments of the improved target detection method were completed. The experimental results show that improved method can identify the common maritime target effectively and has better detection accuracy and robustness compared with Faster RCNN.
Identification and localisation of incipient discharges in transformer insulation adopting UHF technique

Incipient discharges formed in natural ester oil due to corona activity, surface discharges and particle movement were investigated using UHF technique. When the applied voltage magnitude is increased, on the inception of discharges, the peak to peak magnitude of the voltage of the UHF signal formed also increases. After certain applied voltage magnitude increase, if it is reduced, the magnitude of UHF signal formed is much higher than the magnitude of the signal formed when the voltage is increased. This phenomenon is observed with all the three types of discharges. Cross Recurrence plot (CRP) can be effectively used to determine the Time Difference Of Arrival (TDOA) of UHF signals. Self-similarity Recurrence Quantification Analysis (RQA) parameter is found to be more suitable technique to estimate the TDOA of UHF signals. CRP method is used to estimate TDOA correctly, even with low signal to noise ratio and it is found to be superior to Cross-correlation technique in estimating the TDOA. Estimated TDOA of UHF signals are validated and incipient discharge source is localized by adopting the non-iterative technique.
Optimization of Illumination Performance of Trichromatic White Light-Emitting Diode and Characterization of Its Modulation Bandwidth for Communication Applications

We study a trichromatic white light-emitting diode (WLED) system that consists of a blue LED covered with layers of red emissive CdSe/ZnS quantum dots (QDs) and yellow emissive YAG:Ce3+ phosphors. With the knowledge of the individual emission spectra of the blue LED, the QDs, and the phosphors, we develop a method of determining the right amounts of QDs and phosphors to optimize the illumination performance of the WLED. The predicted performances of the WLEDs obtained from our method agree well with experimental results. With this method, we are able to produce white light with, for example, a high color-rendering index of 95.4 and an R9 value of 95.0 at a correlated color temperature (CCT) of 3640 K. We also analyze the modulation characteristics of this WLED system for visible light communication (VLC). By combining the frequency responses of the blue LED, the QDs, and the phosphors, we are able to accurately predict the overall frequency responses and the bandwidths of the WLEDs that have various CCTs and, thus, optimize the bandwidth of the WLED. Our approach of optimizing the performance of a WLED, as verified by our measurement data, is simple and general and can facilitate the selection of suitable light-conversion materials for combined illumination and VLC applications.
Coordinated path following control of multiple underactuated underwater vehicles

This paper investigates the coordinated path following problem of multiple underactuated underwater vehicles (UUVs) which move on the desired paths. To deal with the path following control problem, the path tracking error equation is established in Serret-Frenet frame based on ‘virtual’ guidance. The controller design process is divided into kinematic and dynamic two parts with backstepping method, which leads a simplification for the design procedure. To deal with the coordination control problem, the speeds of UUVs are adjusted about their nominal values so as to synchronize their positions and achieve coordination. It is shown that the system that is obtained by putting together the path following and coordination subsystems can be viewed as cascade connection system. Using this fact and recent results from nonlinear systems and graph theory, the path following and coordination errors are driven to a neighborhood of zero. Moreover, these controllers are distributed in the sense that the controller design for each UUV only requires relative state in formation between itself and its neighbors. Finally, a simulation example demonstrates the effectiveness of the control method.
Spectrum Analysis for Vacuum Surface Flashover of Different Insulator Materials

The optical diagnostic method can provide much more information about the physical process of surface flashover. In this paper, the vacuum surface flashover spectra of five different insulator materials (including both organic and inorganic insulator materials) under pulsed excitation are presented. According to the spectrum analysis results, many molecular spectral bands emerge in the spectrum of surface flashover as well as the atomic lines. The flashover band spectra of different insulators are nearly the same, most of these band spectra might be generated by ionized gases which are desorbed from insulator surface. Besides, some of the atomic lines are identified to be emitted by material element, which implies that the material was decomposed during the flashover process, and the decomposed material together with desorbed gas contribute to the final stage of flashover.
Modelling Smart Mobile Robotic Networks from a Cyber Physical System Perspective

Mobile robotic network (MRN) consists of a group of robotic nodes (such as mobile sensors, unmanned vehicles, UAVs and mobile robots) that can communicate with each other for collaboration, in which motion control and communication will both play crucial roles. With recent advances in artificial intelligence, robotic nodes are becoming smart with more powerful computational capability. Therefore, there appears a strong trend to integrally design MRNs from these three aspects: motion control, communication and computation. Cyber physical system that bridges the cyber world of communication and computation with the physical world of motion control provides us a new perspective to MRNs. In this research, we analyze the tight integration and coupling of these cyber physical aspects in MRNs, and provide a framework to specify the effect of each aspect and the transitions among them in terms of their contributions to the network performance. We use illustrative examples of flock motion, topology motion and ad hoc networking in MRNs to demonstrate the framework.
A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography

textabstractComputed Tomography (CT) is an imaging technique that allows to reconstruct volumetric information of the analyzed objects from their projections. The most popular reconstruction technique is the Filtered Back Projection (FBP). It has the advantage of being the fastest technique available, but also the disadvantage to require a high number of projections to retrieve good quality reconstructions. In this article we propose a segmentation method for tomographic volumes composed of few materials. Our method combines existing high-quality variational segmentation frameworks with the data consistency approach used in tomography and discrete tomography. We show that our algorithm performs well under high noise level and with moderately low number of projections, and that the data consistency significantly improves the segmentation, at the cost of only one FBP reconstruction and forward projection.
Demo: Talk2Me - A Framework for D2D Augmented Reality Social Network

In this demo, we present Talk2Me, an augmented re- ality social network framework that enables users to disseminate information in a distributed way and view others' information instantly. Talk2Me advertises users’ messages, together with theirface-signatures, to every nearby device in a Device-to–Device fashion. When a user looks at nearby persons through her camera-enabled wearable devices (e.g., Google Glass), the frame- work automatically extracts the face-signature of the person of interest, compares it with the previously captured signatures, and presents the information shared by this person to the user. We design a lightweight and yet accurate face recognition algorithm, together with an efficient distributed dissemination protocol. We integrate their implementations in an Android prototype.
Methamphetamine decreases K+ channel function in human fetal astrocytes by activating the trace amine‐associated receptor type‐1

Methamphetamine (Meth) is a potent and commonly abused psychostimulant. Meth alters neuron and astrocyte activity; yet the underlying mechanism(s) is not fully understood. Here we assessed the impact of acute Meth on human fetal astrocytes (HFAs) using whole‐cell patch‐clamping. We found that HFAs displayed a large voltage‐gated K+ efflux (IKv) through Kv/Kv‐like channels during membrane depolarization, and a smaller K+ influx (Ikir) via inward‐rectifying Kir/Kir‐like channels during membrane hyperpolarization. Meth at a ‘recreational’ (20 μM) or toxic/fatal (100 μM) concentration depolarized resting membrane potential (RMP) and suppressed IKv/Kv‐like. These changes were associated with a decreased time constant (Ƭ), and mimicked by blocking the two‐pore domain K+ (K2P)/K2P‐like and Kv/Kv‐like channels, respectively. Meth also diminished IKir/Kir‐like, but only at toxic/fatal levels. Given that Meth is a potent agonist for the trace amine‐associated receptor type‐1 (TAAR1), and TAAR1‐coupled cAMP/cAMP‐activated protein kinase (PKA) cascade, we further evaluated whether the Meth impact on K+ efflux was mediated by this pathway. We found that antagonizing TAAR1 with N‐(3‐Ethoxyphenyl)‐4‐(1‐pyrrolidinyl)‐3‐(trifluoromethyl)benzamide (EPPTB) reversed Meth‐induced suppression of IKv/Kv‐like; and inhibiting PKA activity by H89 abolished Meth effects on suppressing IKv/Kv‐like. Antagonizing TAAR1 might also attenuate Meth‐induced RMP depolarization. Voltage‐gated Ca2+ currents were not detected in HFAs. These novel findings demonstrate that Meth suppresses IKv/Kv‐like by facilitating the TAAR1/Gs/cAMP/PKA cascade and altering the kinetics of Kv/Kv‐like channel gating, but reduces K2P/K2P‐like channel activity through other pathway(s), in HFAs. Given that Meth‐induced decrease in astrocytic K+ efflux through K2P/K2P‐like and Kv/Kv‐like channels reduces extracellular K+ levels, such reduction could consequently contribute to a decreased excitability of surrounding neurons.
Parameters identification of a distributed dynamical model using combined approach

We proposed a combined method for identifying the equations of mathematical physics describing the dynamics of spatially-distributed processes on the basis of experimental multidimensional time series. The first component of the method includes the OLS (Ordinary least squares) estimates of the parameters of multidimensional autoregression. However, these estimates are biased due to the presence of errors in the regressors. To reduce this bias, we used the extended Kalman filter as the second component of the method. We given a numerical example confirming the effectiveness of the proposed method.
Research on Image Denoising Method Based on Wavelet Transform

In the process of image acquisition and transmission, the image always generates noise due to internal and external interference. Noise reduces the quality of the image, and makes it difficult for subsequent image processing. Therefore, image denoising is very important in image processing. Wavelet denoising can effectively filter out noise and retain high-frequency information of the image, this method has the characteristics of fast operation speed and has become an important branch of image denoising. Threshold functions commonly used in wavelet threshold denoising include hard threshold function and soft threshold function. The hard threshold function is not continuous as a whole. Although the soft threshold function has good continuity, there is always a constant deviation between the processed coefficient and the original coefficient when the wavelet coefficient is large. In response to these deficiencies, this paper establishes a new improved threshold function based on traditional soft and hard threshold functions. By processing the thresholds of wavelet coefficients, a reasonable balance between smoothing and edge oscillations can be achieved after image denoising. The improved threshold function not only overcomes the shortcomings of the soft and hard threshold functions, but also provides more flexibility in the processing of image noise. Through MATLAB simulation, the denoising effects of the soft, hard threshold functions and the threshold function constructed in this paper are compared in terms of signal-to-noise ratio (SNR) and root mean square error (MSE). The MATLAB simulation results show that compared with the traditional threshold function, the improved threshold function has a higher signal-to-noise ratio (SNR = 26.27709) and a smaller mean square error (MSE = 153.4579), and it has a good noise reduction effect.
Speech Emotion Recognition Based on Linear Discriminant Analysis and Support Vector Machine Decision Tree

For speech emotion recognition, emotional feature set with high dimension may produce redundant features and influence the recognition accuracy. To solve this problem and obtain the optimal emotional feature subset of speech, a feature dimension reduction based on linear discriminant analysis is proposed. According to the confusion degree between different basic emotions, an emotion recognition method based on support vector machine decision tree is proposed. Experiment on speaker-dependent speech emotion recognition using Chinese speech database from institute of automation of Chinese academy of sciences is performed and a speech emotion recognition system is presented, where standard feature sets of the INTER-SPEECH and classic classifiers are used in comparative experiments respectively. Experimental results show that the proposal achieves 84.39% recognition accuracy on average. By proposal, it would be fast and efficient to discriminate emotional states of diverse speakers from speech, and it would make it possible to realize the interaction between speaker and computer/robot in the future.
Performance evaluation of SDN WLAN architecture

This article focuses on mobility of stations under 802.11 standards, with use of Software-Defined Networking (SDN). Lately, there are several SDN-based solutions for seamless handover. These solutions typically use separate control channels to utilize the wireless part of network. In our work, we demonstrate high performance of SDN WLAN architecture under real word test scenarios. Our common control channels solution extends the OpenFlow protocol. Our proposed method is notably improving performance of network architecture in next topics: network scalability, security and parallelly it allows delay critical scenarios to be delivered smoothly including seamless handover.
Evaluation of Objects Recognition Efficiency on Mapes by Various Methods

The paper analyzes the efficiency of image recognition on terrestrial photographs by SURF, SIFT and ORB methods. It has been shown that for high-quality images, the highest probability of recognition in the application of the SIFT method. In the case of identifying fragments of images on noisy and blurred images, the best results are obtained using the ORB method, which, together with this, has the highest performance among the methods used.
I/Q Imbalances in QAM Communication Systems with Multi-Antenna Receivers and IF Architecture

The Inphase/Quadrature phase (I/Q) imbalance is an inevitable problem in wireless communication systems due to imperfections in the transceiver hardware. In this paper, we investigate the effect of I/Q imbalance in Quadrature Amplitude Modulation (QAM) communication systems adopting multiantenna receivers and the IF (Intermediate Frequency) architecture. Two application scenarios are studied: adaptive beamforming and Blind Source Separation (BSS)-based multiuser detection. For both applications, after analyzing the interference introduced by the transceiver I/Q imbalance, we illustrate that, like systems adopting the zero-IF architecture, straightforward digital signal processing algorithms can be applied in systems with the IF architecture as well to correct the effect of I/Q imbalance. The differences between systems adopting the zero-IF and IF architectures are clarified. Computer simulation results are presented to confirm the conclusions of theoretic analysis.
Analysis of Electromagnetic Force Waves of Solid Cylindrical Permanent Magnet Synchronous Motors

Solid cylindrical permanent magnet synchronous motors (SCPMSMs) are taken as the study objects in this paper. Based on the magnetic circuit analysis theory, the analytical expressions of radial electromagnetic force waves are deduced. The electromagnetic forces of the motor under both no-load and load conditions are analyzed. The radial electromagnetic force wave sources, amplitudes, time frequencies and spatial orders and the force components which have great influence on motor electromagnetic vibration and noise under two conditions are summarized. The finite element simulation analyses on radial electromagnetic force waves of a high speed SCPMSM under both no-load and load conditions are carried out and so the correctness of theoretical analysis is verified. The results show that for the SCPMSM under both no-load and load conditions, all the radial electromagnetic force frequencies are twice that of the power, that the spatial orders of the primary electromagnetic forces are 2 and that the electromagnetic vibration of stator caused by the second spatial order radial electromagnetic force wave is the main component of the motor electromagnetic vibration and the main source of the motor electromagnetic noise.