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| 1 | Haze removal for UAV reconnaissance images using layered scattering model显示文摘During the unmanned aerial vehicles(UAV) reconnaissance missions in the middle-low troposphere, the reconnaissance images are blurred and degraded due to the scattering process of aerosol under fog, haze and other weather conditions, which reduce the image contrast and color fidelity. Considering the characteristics of UAV itself, this paper proposes a new algorithm for dehazing UAV reconnaissance images based on layered scattering model. The algorithm starts with the atmosphere scattering model, using the imaging distance, squint angle and other metadata acquired by the UAV. Based on the original model, a layered scattering model for dehazing is proposed. Considering the relationship between wave-length and extinction coefficient, the airlight intensity and extinction coefficient are calculated in the model. Finally, the restored images are obtained. In addition, a classification method based on Bayesian classification is used for classification of haze concentration of the image, avoiding the trouble of manual working. Then we evaluate the haze removal results according to both the subjective and objective criteria. The experimental results show that compared with the origin image, the comprehensive index of the image restored by our method increases by 282.84%, which proves that our method can obtain excellent dehazing effect. | Huang Yuqing Ding Wenrui Li Hongguang | 2016 | Chinese Journal of Aeronautics2016，29，2： | 6 |
| 2 | A GPS Receiver Adaptive Digital Beamforming Interference Suppression Algorithm Based on Kalman Filter显示文摘 | DING Wenrui ZHU Yunlong ZHANG Bo YANG Dongkai | 2013 | Chinese Journal of Electronics2013，22，2： | 3 |
| 3 | Optimization of bits allocation and path planning with trajectory constraint in UAV-enabled mobile edge computing system显示文摘In this paper,an Unmanned Aerial Vehicle(UAV)enabled Mobile Edge Computing(MEC)system is studied,in which UAV acts as server to offer computing offloading service to the Mobile Users(MUs)with limited computing capability and energy budget.We aim to minimize the total energy consumption of MUs by jointly optimizing the bit allocation for uplink,computing at the UAV and downlink,along with the UAV trajectory in a unified framework.To this end,a trajectory constraint model is employed to avoid sudden changes of velocity and acceleration during flying.Due to high-order information in use,we lead to a more reasonable nonconvex optimization problem than prior arts.An Alternating Direction Method of Multipliers(ADMM)method is introduced to solve the optimization problem,which is decomposed into a set of easy subproblems,to meet the requirement on the efficiency in edge computing.Numerical results demonstrate that our approach leads a smoother UAV trajectory,significantly save the energy consumption for UAV during flying. | Yizhe LUO Wenrui DING Baochang ZHANG Wenqian HUANG Chunhui LIU | 2020 | Chinese Journal of Aeronautics2020，33，10： | 2 |
| 4 | Three New Chromone Derivatives Produced by Phomopsis sp. HNY29-2B from Acanthus ilicifolius Linn.显示文摘三新 chromone 衍生物, phomochromenones 交流(1-3 ) ,和一已知的 chaetocyclinone B (4 ) 从 Phomopsis sp 的文化被获得。HNY29-2B 从红树属植物叶板 ilicifolius 悬崖孤立,它从华南海是镇定的。他们的结构被 1 D NMR 和 2 象集体分光镜的数据一样的 D NMR。1 和 2 的绝对配置被电子圆形的二色性(ECD ) 的量化学药品计算分配系列。化合物 3 是拥有唯一的 chromeno 的碱的第三个例子[3,2-c ] pyridine 原子核。在 bioactivity 试金,化合物 4 与 8.13 和 3.59 污穹摥 ? 穩牯歯? 效正愠摮匠穵歵? 楍慹牵 ? 牣獯 ? 潣的 IC 50 价值对人的前列腺癌症房间线(PC-3 和 DU145 房间) 显示出 cytotoxicity 吗? | Bo Ding Zhiyuan Wang Guoping Xia Xishan Huang Fang Xu Wenrui Chen Zhigang She | 2017 | Chinese Journal of Chemistry2017，35，12： | 1 |
| 5 | p21 response to DNA damage induced by genistein and etoposide in human lung cancer cells显示文摘 | Haiming Ding Wenrui Duan Wei-Guo Zhu Rong Ju Kanur Srinivasan Gregory A. Otterson Miguel A. Villalona-Calero | 2003 | Biochemical and Biophysical Research Communications2003，，4： | 1 |
| 6 | The Data-Reusing MCC-Based Algorithm and Its Performance Analysis显示文摘Maximum correntropy criterion(MCC)provides a robust optimality criterion for non-Gaussian signal processing.In this paper,the weight update equation of the conventional MCC-based adaptive filtering algorithm is modified by reusing the past K input vectors,forming a class of data-reusing MCC-based algorithm,called DRMCC algorithm.Comparing with the conventional MCCbased algorithm,the DR-MCC algorithm provides a much better convergence performance when the input data is correlated.The mean-square stability bound of the DRMCC algorithm has been studied theoretically.For both Gaussian noise case and non-Gaussian noise case,the expressions for the steady-state Excess mean square error(EMSE) of DR-MCC algorithm have been derived.The relationship between the data-reusing order and the steadystate EMSEs is also analyzed.Simulation results are in agreement with the theoretical analysis. | LIU Chunhui QI Yue DING Wenrui | 2016 | Chinese Journal of Electronics2016，25，4： | 1 |
| 7 | End-to-end encrypted network traffic classification method based on deep learning显示文摘Network traffic classification,which matches network traffic for a specific class of different granularities,plays a vital role in the domain of network administration and cyber security.With the rapid development of network communication techniques,more and more network applications adopt encryption techniques during communication,which brings significant challenges to traditional network traffic classification methods.On the one hand,traditional methods mainly depend on matching features on the application layer of the ISO/OSI reference model,which leads to the failure of classifying encrypted traffic.On the other hand,machine learning-based methods require human-made features from network traffic data by human experts,which renders it difficult for them to deal with complex network protocols.In this paper,the convolution attention network(CAT)is proposed to overcom those difficulties.As an end-to-end model,CAT takes raw data as input and returns classification results automatically,with engineering by human experts.In CAT,firstly,the importance of different bytes with an attention mechanism of network traffic is achieved.Then,convolution neural network(CNN)is used to learn features automatically and feed the output into a softmax function to get classification results.It enables CAT to learn enough information from network traffic data and ensure the classified accuracy.Extensive experiments on the public encrypted network traffic dataset ISCX2016 demonstrate the effectiveness of the proposed model. | Tian Shiming Gong Feixiang Mo Shuang Li Meng Wu Wenrui Xiao Ding | 2020 | The Journal of China Universities of Posts and Telecommunications2020，27，3： | 1 |
| 8 | Relay selection based on MAP estimation for cooperative communication with outdated channel state information显示文摘In this paper, we consider an amplify-and-forward (AF) cooperative communication system when the channel state information (CSI) used in relay selection differs from that during data transmission, i.e., the CSI used in relay selection is outdated. The selected relay may not be actually the best for data transmission and the outage performance of the cooperative system will deteriorate. To improve its performance, we propose a relay selection strategy based on maximum a posteriori (MAP) estimation, where relay is selected based on predicted signal-to-noise ratio (SNR). To reduce the computation complexity, we approximate the a posteriori probability density of SNR and obtain a closed-form predicted SNR, and a relay selection strategy based on the approximate MAP estimation (RS-AMAP) is proposed. The simulation results show that this approximation leads to trivial performance loss from the perspective of outage probability. Compared with relay selection strategies given in the literature, the outage probability is reduced largely through RS-AMAP for medium-to-large transmitting powers and medium-to-high channel correlation coefficients. | Ding Wenrui Fei Li Gao Qiang Liu Shuo | 2013 | Chinese Journal of Aeronautics2013，26，3： | 0 |
| 9 | Optimal Joint Space Control of a Cable-Driven Aerial Manipulator显示文摘This article proposes a novel method for maintaining the trajectory of an aerial manipulator by utilizing a fast nonsingular terminal sliding mode(FNTSM)manifold and a linear extended state observer(LESO).The developed controlmethod applies an FNTSMto ensure the tracking performance’s control accuracy,and an LESO to estimate the system’s unmodeled dynamics and external disturbances.Additionally,an improved salp swarm algorithm(ISSA)is employed to parameter tune the suggested controller by integrating the salp swarmtechnique with a cloud model.This approach also uses a model-free scheme to reduce the complexity of controller design without relying on complex and precise dynamics models.The simulation results show that the proposed controller outperforms linear active rejection disturbance control and PID controllers in terms of transient performance and resilience against lumped disturbances,and the ISSA can help the proposed controller find optimal control parameters. | Li Ding Rui Ma Zhengtian Wu Rongzhi Qi Wenrui Ruan | 2023 | Computer Modeling in Engineering & Sciences2023，，4： | 0 |
| 10 | A Novel Salient Region Detection Method Based on Hierarchical Spatial Information显示文摘Different patterns in one object will cause unequal saliency degree which makes it hard to highlight the object region uniformly.We propose a salient region detection method which mainly includes image abstraction,saliency calculation and integration.Under the detection framework,the hierarchical spatial information is introduced to improve the performance.The image abstraction with 'pixel level' spatial information is applied to capture some meaningful elements.The local contrast is calculated with the 'element level' spatial information.The'object level' spatial information is represented as compactness and background possibility,which further help to better pop out the object region and suppress the background.The results show that our method has a good performance even though the object consists of complex patterns. | LIU Shuo DING Wenrui LI Hongguang LI Yingting | 2017 | Chinese Journal of Electronics2017，26，2： | 0 |
| 11 | A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province,China显示文摘The aim of this research was to develop a quantitative method for clinicians to predict the probability of improved prognosis in patients with coronavirus disease 2019(COVID-19).Data on 104 patients admitted to hospital with laboratory-confirmed COVID-19 infection from 10 January 2020 to 26 February 2020 were collected.Clinical information and laboratory findings were collected and compared between the outcomes of improved patients and non-improved patients.The least absolute shrinkage and selection operator(LASSO)logistics regression model and two-way stepwise strategy in the multivariate logistics regression model were used to select prognostic factors for predicting clinical outcomes in COVID-19 patients.The concordance index(C-index)was used to assess the discrimination of the model,and internal validation was performed through bootstrap resampling.A novel predictive nomogram was constructed by incorporating these features.Of the 104 patients included in the study(median age 55 years),75(72.1%)had improved short-term outcomes,while 29(27.9%)showed no signs of improvement.There were numerous differences in clinical characteristics and laboratory findings between patients with improved outcomes and patients without improved outcomes.After a multi-step screening process,prognostic factors were selected and incorporated into the nomogram construction,including immunoglobulin A(IgA),C-reactive protein(CRP),creatine kinase(CK),acute physiology and chronic health evaluation II(APACHE II),and interaction between CK and APACHE II.The C-index of our model was 0.962(95%confidence interval(CI),0.931-0.993)and still reached a high value of 0.948 through bootstrapping validation.A predictive nomogram we further established showed close performance compared with the ideal model on the calibration plot and was clinically practical according to the decision curve and clinical impact curve.The nomogram we constructed is useful for clinicians to predict improved clinical outcome probability for each COVID-19 patient,which may facilitate personalized counselling and treatment. | Jiaojiao Xie Ding Shi Mingyang Bao Xiaoyi Hu Wenrui Wu Jifang Sheng Kaijin Xu Qing Wang Jingjing Wu Kaicen Wang Daiqiong Fang Yating Li Lanjuan Li | 2022 | Engineering2022，8，1： | 0 |
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