Farong Gao

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Verified

Farong verified their affiliation via an institutional email.

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• PhD
• Professor (Associate) at Hangzhou Dianzi University

Unsupervised domain adaptation (UDA) is a technique for learning from a label-rich source domain and transferring the learned knowledge to an unlabeled target domain. Current researches on feature-based UDA methods usually utilize the pseudo labels to find new feature representations that can minimize the distribution difference between the two dom...

In developing and exploring extreme and harsh underwater environments, underwater robots can effectively replace humans to complete tasks. To meet the requirements of underwater flexible motion and comprehensive subsea operation, a novel octopus-inspired robot with eight soft limbs was designed and developed. This robot possesses the capabilities o...

In this study, an accurate tool is provided for the evaluation of the effect of joint motion effect on gait stability. This quantitative gait evaluation method relies exclusively on the analysis of data acquired using acceleration sensors. First, the acceleration signal of lower limb motion is collected dynamically in real-time through the accelera...

To enhance the reproducibility of motor unit number index (MUNIX) for evaluating neurological disease progression, this paper proposes a negative entropy-based fast independent component analysis (FastICA) demixing method to assess MUNIX reproducibility in the presence of inter-channel mixing of electromyography (EMG) signals acquired by high-densi...

Domain adaptation is a learning strategy that aims to improve the performance of models in the current field by leveraging similar domain information. In order to analyze the effects of feature disentangling on domain adaptation and evaluate a model’s suitability in the original scene, we present a method called feature disentangling and domain shi...

Underwater vision technology is of great significance in marine investigation. However, the complex underwater environment leads to some problems, such as color deviation and high noise. Therefore, underwater image enhancement has been a focus of the research community. In this paper, a new underwater image enhancement method is proposed based on a...

Segmentation of skin lesions is a critical step in the process of skin lesion diagnosis. Such segmentation is challenging due to the irregular shape, fuzzy contours and severe noise interference in the skin lesion region. Existing deep learning-based skin lesion segmentation methods are usually computationally expensive, hindering their deployment...

Repeatability is an important attribute of motor unit number index (MUNIX) technology. This paper proposes an optimal contraction force combination for MUNIX calculation in an effort to improve the repeatability of this technology. In this study, the surface electromyography (EMG) signals of the biceps brachii muscle of eight healthy subjects were...

Deep-learning-based methods have been widely used in hyperspectral image classification. In order to solve the problems of the excessive parameters and computational cost of 3D convolution, and loss of detailed information due to the excessive increase in the receptive field in pursuit of multi-scale features, this paper proposes a lightweight hybr...

In this paper, a gait classification method based on the deep belief network (DBN) optimized by the sparrow search algorithm (SSA) is proposed. The multiple features obtained based on surface electromyography (sEMG) are fused. These functions are used to train the model. First, the sample features, such as the time domain and frequency domain featu...

This paper aims to study the application of hyperspectral technology in the classification of deep-sea manganese nodules. Considering the spectral spatial variation of hyperspectral images, the difficulty of label acquisition, and the inability to guarantee stable illumination in deep-sea environments. This paper proposes a local binary pattern man...

Due to the unknown motion model and the complexity of the environment, the problem of target tracking for autonomous underwater vehicles (AUVs) became one of the major difficulties in model-based controllers. Therefore, the target tracking task of AUV is modeled as a Markov decision process (MDP) with unknown state transition probabilities. Based o...

Deep convolutional neural networks (CNNs) have enabled significant progress in the single image super-resolution (SISR) field in recent years. However, most super-resolution methods based on deep neural networks obtain spatial information using a single-size convolution kernel, which leads to insufficient local feature extraction. In addition, sinc...

Few-shot learning aims to make classification when few samples are available. In general, metric-based methods map images into a space by learning the embedding function. However, conventional metric-based methods rely on a single distance value, which does not pay attention to the shallow features. In this paper, we propose a multi-distance metric...

Aiming at solving the problems of prototype network that the label information is not reliable enough and that the hyperparameters of the loss function cannot follow the changes of image feature information, we propose a method that combines label smoothing and hyperparameters. First, the label information of an image is processed by label smoothin...

This study aims to solve the problem of sparse reward and local convergence when using a reinforcement learning algorithm as the controller of an AUV. Based on the generative adversarial imitation (GAIL) algorithm combined with a multi-agent, a multi-agent GAIL (MAG) algorithm is proposed. The GAIL enables the AUV to directly learn from expert demo...

Epilepsy is a chronic neurological disorder which can affect 65 million patients worldwide. Recently, network based analyses have been of great help in the investigation of seizures. Now graph theory is commonly applied to analyze functional brain networks, but functional brain networks are dynamic. Methods based on graph theory find it difficult t...

The classification of motor imagery (MI) task based on Electroencephalography (EEG) is an important problem in brain-computer interface (BCI) system. The high-precision classification of MI is a challenging task in which the process of feature extraction is crucial step. In this work, we propose a tensor model of a dynamic brain functional network...

In order to obtain panoramic images in a low contrast underwater environment, an underwater panoramic image mosaic algorithm based on image enhancement and improved image registration (IIR) was proposed. Firstly, mixed filtering and sigma filtering are used to enhance the contrast of the original image and de-noise the image. Secondly, scale-invari...

This study proposed a gait recognition method based on the deep neural network of surface electromyography (sEMG) signals to improve the stability and accuracy of gait recognition using sEMG signals of the lower limbs. First, we determined the parameters of time domain features, including the mean of absolute value, root mean square, waveform lengt...

This work focuses on the study of robust no-wait flow shop scheduling problem (R-NWFSP) under the interval-valued fuzzy processing time, which aims to minimize the makespan within an upper bound on total completion time. As the uncertainty of actual job processing times may cause significant differences in processing costs, a R-NWFSP model whose ob...

Accuracy is a key index of human gait recognition. In this paper, we propose an improved gait recognition algorithm, which combines multiple feature combination and artificial bee colony for optimizing the support vector machine (ABC-SVM). Firstly, considering the complexity characteristics of surface electromyography (sEMG) signals, four types of...

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpe...

Multi-stage flash (MSF) desalination plays an important role in achieving large-scale fresh water driven by thermal energy. In this paper, based on first-principle modeling of a typical multi-stage flash desalination system, the effects of different operational parameters on system performance and operational optimization for cost saving were exten...

Motor Unit Number Index (MUNIX) is a technique that provides a susceptive biomarker for monitoring innervation conditions in patients with neurodegenerative diseases. A satisfactory repeatability is essential for the interpretation of MUNIX results. This study aims to examine the effect of channel number and location on the repeatability of MUNIX....

Surface electromyogram (sEMG) signals are easy to record and offer valuable motion information, such as symmetric and periodic motion in human gait. Due to these characteristics, sEMG is widely used in human-computer interaction, clinical diagnosis and rehabilitation medicine, sports medicine and other fields. This paper aims to improve the estimat...

A regionalized environmental knowledge model (REKModel) is presented to describe the environment in the paper. The REKModel is a hierarchical structure in which small regions are grouped together to form superordinate regions. The REKModel is intrinsically hierarchical iterative and nested. Thus an extended nested-graph(ENG) is proposed to construc...

A gait event is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. However, for the data acquisition of a three-dimensional motion capture (3D Mo-Cap) system, the high cost of setups, such as the high standard laboratory environment, limits widespread clinical application. Inertial sensors are increasingly bei...

The shape changes of soft organisms demonstrate the survival rules in the evolution of self life. It is important for the transform control of soft robots about how to envolve suitable for the shape demands. In this paper, the compositional pattern producing networks (CPPN) algorithm was used to evolve soft robot. By taking simple random functions...

Motor imagery electroencephalography (EEG) has been successfully used in the brain-computer interface (BCI) systems. Broad learning (BL) is an effective and efficient incremental learning algorithm with simple neural network structure. In this work, a novel EEG multi-classification method is proposed by combining with BL and common spatial pattern...

In order to evaluate the effects of time domain (TD) and frequency domain (FD) features as well as muscle number on gait classification recognition, eight channels of electromyography (EMG) signals were collected from four thigh and four lower leg muscles, and two TD features and two FD features were extracted in this study. The method of support v...

Human walking is the composite movement of the musculoskeletal system in lower limbs. The interaction mechanism of the different muscle groups in a combination action is of great importance. To this end, under the stand-squat and squat-stand tasks, the problems of the motion model decomposition and the muscle synergy were studied in this paper. Fir...

To improve the recognition accuracy of the lower limb gait, a classification method based on genetic algorithm (GA) optimizing the support vector machine (SVM) was proposed. Firstly, electromyography (EMG) signals were collected from four thigh muscles related to lower limb movements. Then the values of variance and integral of absolute were extrac...

Inspired by the ‘fine-to-coarse’ way-finding strategy that human utilized in the process of navigation, the paper proposed a fast on-line global path planning algorithm based on regionalized roadmap. First, a regionalized roadmap(RRM) that has a multi-layered structure is proposed for representing environments. Then, the RRM based FTC-A* algorithm...

Brain functional network is introduced to feature extraction of ElectroEncephaloGraphy (EEG), and a novel method is proposed based on Least Absolute Shrinkage and Selection Operator (LASSO)-Granger causality between Region Of Interest (ROI) in the brain, in order to overcome the inherent deficiencies of research methods based on isolated brain regi...

The characteristics of the human physiology and motion are the important factors affecting the gait recognition. By means of the experimental data from the lower limb motion, firstly the surface electromyography (sEMG) was de-noised by the wavelet method and the feature samples were extracted, subsequently the classification and recognition were im...

Recently, semi-supervised learning has received much attention in data mining and machine learning, and a number of algorithms are proposed to discuss how to make good use of the unlabeled data. Some algorithms deal with the unlabeled data in an exact way, in which each unlabeled sample is assigned to one single class and then treated as a labeled...

To improve the lower limb surface ElectroMyoGraphic (EMG) gait recognition accuracy and real time performance, this paper deals with a pattern recognition method for optimizing the Support Vector Machine (SVM) by using the Particle Swarm Optimization (PSO) algorithm. Firstly, the values of Integrated EMG and variance are extracted as the feature sa...

The methods of piezoelectric energy harvest and detection based on forced vibration are introduced in this paper. Firstly, the mechanical energy of the forced vibration is converted into alternating current energy by using the piezoelectric harvester, and then the AC currents are rectified through the full bridge rectifier circuits, and finally the...

A comprehensive method, fused with kinematics information and bioelectricity information, for upper limb motor-function evaluation was proposed. The method was aimed to evaluate the motor functions of the shoulder, elbow and wrist joints of the hemiplegic patients objectively and quantitatively. Acceleration signal and EMG signal were collected and...

Based on the vascular membrane stress model and the pseudo-elastic vessel model, the combination constitutive model with a layered structure in microvessel is presented in this paper. By using obtained constitutive equations of the current model, the circumferential stress of the membrane intimal (inner) layer and the three-dimensional stress distr...

A new method of removing power frequency noise in surface electromyography(sEMG) is designed with matched filtering and independent component analysis. It can be judged effectively whether surface electromyography includes the power frequency noise with matched filtering. It can be avoided that the power frequency noise filter is abused. Under this...

A new method of removing power frequency noise in tactile sensor signal was designed by matched filtering and independent component analysis (ICA), for tactile sensor signal was susceptible to electromagnetic interference of the robot power system. First, the matched filter was used to determine whether tactile sensor signal contain frequency noise...

A blood vessel model of pseudo-elastic constitutive relation in an absolute (vacuum) zero-stress state is employed, and analytical equations of the vessel wall in the three-dimensional stress state are obtained in this paper. The stress distributions in circumferential and axial directions with different blood pressure levels and material parameter...

A three-phase coupled model of the gas–liquid–solid oscillation system is established to analyze the oscillation characteristics of a bubble inside a micro blood vessel with various radii and its shape changes with different interface boundaries. The results show that unlike the spherical symmetric oscillation in an unbounded fluid, the oscillating...

Cardiovascular system plays an important role in medical diagnosis and disease therapy, yet mechanical vascular injury in clinical treatment may cause serious medical accident. In present paper, stress-strain behavior of blood vessel and surrounding tissues is analyzed, and damage criterion based on equivalent strain and damage function is employed...

The evolution of a bubble confined inside a nonlinear micro vessel fully filled with a viscous liquid, subjected to a shock lithotripsy wave (SWL), is analyzed with a previously established asymmetrical model on bubble oscillation. Both the normal and shear stress components within the vessel wall are calculated. It is observed that although the sh...

Asymmetrical oscillation of a micro-bubble confined inside a deformable pseudoelastic vessel with comparable initial radius with the bubble is studied in detail. Unlike the symmetric oscillation in an unconstrained environment, the oscillating bubble under the constraint of a pseudoelastic vessel gradually becomes as an ellipsoid from a sphere (thi...

The vibration of a circular cylindrical piezoelectric ceramic shell with tangential poling is investigated for transformer application and an analytical solution is obtained. Numerical calculations of the output voltage, input admittance and the efficiency of the transformer are presented. The results indicate that the structure analyzed can be use...