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4th International Conference on Cloud Computing and Security, ICCCS 2018

作者： Fang, Wei Ding, Yewen Zhang, Feihong School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9783030000059

The convolution neural network for image classification is an application of deep learning on image processing. Convolutional neural networks have the advantage of being able to convolve directly with image pixels and extract image features from image pixels. This approach is closer to the treatment of the human brain’s visual system. However, up to now, it is impossible to achieve 100% classification accuracy regardless of any kind of convolutional neural network models. At the same time, we also found that sometimes the picture background will also affect the recognition effect of the neural network on the picture, and after removing the picture background, it can correctly recognize the same picture. Therefore, we design a model based on the convolutional neural network to remove the image background for some specific images (such as selfies, animals, flowers, etc.) here, and then the image after processing will be identified and classified. Experiments show that the proposed method can maintain a high level of integrity of the target to be detected in the image after removing the background (here the indicator is Intersection Over Union, IOU);moreover, through multiple classification models verify that the classification accuracy of some background-removed pictures is significantly higher than that of pictures without any treatment. © Springer Nature Switzerland AG 2018.

关键词： Image classification

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The research of acceptance and scheduling scheme based on the overall network QoS

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2011 International Conference on Instrumentation, Measurement, Circuits and Systems, ICIMCS 2011

作者： Xu, Zhanyang Ping, Huang Li Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9783642273339

Many factors affect the QoS of network, and the congestion control mechanism is the most important one. In many references, the research on QoS is focused on the specific network architecture, while the QoS of overall network is still relatively seldom studied. In the paper, an acceptance and scheduling scheme based on the overall network QoS (ASSoQoS) proposed is a new acceptance and scheduling algorithm of the link traffic. At first, the data stream with the admission control strategy will be distributed in different weights , the data flow will get the link (with different weight) transmission scheduling to improve the overall network QoS , according to the allocated weight of a network link and status by real-time network monitoring. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Scheduling

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Weak Fault Diagnosis of Rolling Bearing Based on Improved Stochastic Resonance

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computers, Materials & Continua 2020年第7期64卷 571-587页

作者： Xiaoping Zhao Yifei Wang Yonghong Zhang Jiaxin Wu Yunging Shi School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Automation Nanjing University of Information Science and TechnologyNanjing210044China Electrical and Computer Engineering New Jersey Institute of TechnologyNewark07102USA Network Monitoring Center of Jiangsu Province Nanjing University of Information Science and TechnologyNanjing210044China

Stochastic resonance can use noise to enhance weak signals,effectively reducing the effect of noise signals on feature *** order to improve the early fault recognition rate of rolling bearings,and to overcome the shortcomings of lack of interaction in the selection of SR(Stochastic Resonance)method parameters and the lack of validation of the extracted features,an adaptive genetic random resonance early fault diagnosis method for rolling bearings was *** with the existing methods,the AGSR(Adaptive Genetic Stochastic Resonance)method uses genetic algorithms to optimize the system parameters,and further optimizes the parameters while considering the interaction between the *** method can effectively extract the weak fault features of the *** order to verify the effect of feature extraction,the feature signal extracted by AGSR method was input into the Fully connected neural network for fault *** practicality of the algorithm is verified by simulation data and rolling bearing experimental *** results show that the proposed method can effectively detect the early weak features of rolling bearings,and the fault diagnosis effect is better than the existing methods.

关键词： Rolling bearing weak fault stochastic resonance genetic algorithm neural network

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Energy-Efficient Data-Collection with Rendezvous-Based Approaches in Large-Scale WSNs with Multi-UGV 1

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Zhang, Jian Tan, Ling Zhuang, Wei College of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing210044 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

Prolonging the lifetime of wireless sensor networks (WSNs) is a crucial issue referring to energy conservation or balancing of data collection. In this paper, we propose an optimal algorithm for data collection using UGVs based on clustering by definition of rendezvous nodes (RNs). Due to the considerable large difference of long-distance transmission, the rendezvous-based clustered model for load balancing with multiple UGVs is proposed. Furthermore, considering different delay-tolerant applications, we design a data transmission mode called Two-Orbit Back-Propagation algorithm (TOBPA). In these process, we utilized utility function on energy to realize the optimal energy consumption in the sense of energy transmission model and take energy balancing into account meanwhile. As a result, we analyze the cluster lifetimes in different situations and achieve balance to save significant. © 2019, Springer Nature Switzerland AG.

关键词： Energy efficiency

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Hybrid multiplicative watermarking and its decoders

Hybrid multiplicative watermarking and its decoders

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3rd International Conference on Multimedia Information networking and Security, MINES 2011

作者： Wang, Jinwei Lian, Shiguo Yan, Leiming Wang, Yuxiang Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China Beijing Beijing 10080 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China

ISBN: (纸本)9780769545592

With the rapid development and the richer content of the Internet, the copyright protection of the works should be further developed. The watermarking has become a possible solution. In this paper, firstly, a novel hybrid multiplicative rule is presented and utilized to embed the watermark into DWT coefficients controlled by the secret key. Secondly, the optimum and locally optimum hybrid multiplicative multi-watermarking decoders are proposed, respectively, which are based on the minimum Bayesian risk criterion. The DWT coefficients are modeled as the generalized Gaussian distribution. Nextly, the performance of the optimum hybrid watermarking decoder, i.e. the average bit error rate is theoretically analyzed. Then the security of the hybrid multiplicative watermarking scheme is compared with the existing schemes. Finally, experimental results prove the theoretical analysis valid. © 2011 IEEE.

关键词： Watermarking

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A Soft Tissue Acupuncture Model Based on Mass-Spring Force Ne

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computers, Materials & Continua 2021年第10期69卷 727-745页

作者： Xiaorui Zhang Tong Xu Wei Sun Jiali Duan Sunil Kumar Jha Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Faculty of Information Technology University of Information Technology and ManagementRzeszow35-225Poland

In the simulation of acupuncture manipulation,it is necessary to accurately capture the information of acupuncture points and particles around ***,a soft tissue modeling method that can accurately track model particles is *** this paper,a soft tissue acupuncture model based on the mass-spring force net is *** is used as the auxiliary model and the SHF model is *** is used to establish a three-layer soft tissue model of skin,fat,and muscle,and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and *** addition,a springback algorithm is designed to simulate the springback phenomenon of soft tissue skin during *** evaluation results show that the soft tissue acupuncture modeling method based on mass-spring force net can effectively simulate the springback phenomenon of soft tissue surface during acupuncture surgery,and has good comprehensive performance in the application of virtual acupuncture surgery simulation.

关键词： Mass-spring model puncture simulation virtual surgery soft tissue simulation

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Access Control Policy Based on Friend Circle

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computers, Materials & Continua 2020年第3期62卷 1143-1159页

作者： Qin Liu Tinghuai Ma Fan Xing Yuan Tian Abdullah Al-Dhelaan Mohammed Al-Dhelaan School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China CICAEET Jiangsu Engineering Centre of Network MonitoringNanjing University of Information Science and TechnologyNanjing210044China Computer Science Department College of Computer and Information SciencesKing Saud UniversityRiyadh11362Saudi Arabia

Nowadays,the scale of the user’s personal social network(personal network,a network of the user and their friends,where the user we call“center user”)is becoming larger and more *** is difficult to find a suitable way to manage them *** order to solve this problem,we propose an access control model for social network to protect the privacy of the central users,which achieves the access control accurately and *** on the hybrid friend circle detection algorithm,we consider the aspects of direct judgment,indirect trust judgment and malicious users,a set of multi-angle control method which could be adapted to the social network environment is ***,we propose the solution to the possible conflict of rights in the right control,and assign the rights reasonably in the case of guaranteeing the privacy of the users.

关键词： Social network privacy protection circle of friends access control

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Air Quality Forcasting based on Gated Recurrent Long Short-Term Memory Model 19

Air Quality Forcasting based on Gated Recurrent Long Short-T...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Wang, Baowei Kong, Weiwen Guan, Hui School of Computer and Software Jiangsu Engineering Centre of Network Monitoring Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781450371582

With the continuous development of Chinese economy and the gradual acceleration of urbanization, it has caused tremendous damage to the *** effect of smog on people's lives has become more apparent. The bad air environment seriously damages the physical and mental health of people. Predicting smog becomes very ***,?how to accurately predict PM2.5 has become an important issue in recent years. The existing prediction models have limitations. They don't accurately capture the law between the concentration of haze and the factors affecting reality. It is difficult to accurately predict nonlinear smog data. One algorithm proposed in this paper is a two-layer model prediction algorithm based on Long Short Term Memory Neural network and Gated Recurrent Unit(LSTM&GRU). This algorithm is an improvement and enhancement of the existing prediction method Long Short Term Memory. The Recurrent Neural network (RNN) is used to process important events in the series of prediction intervals and time delays. LSTM&GRU is a time-characteristic neural network algorithm. The data of this experiment was obtained from Zhenqi Net(***). We selected daily smog data from 2014/1/1 to 2018/1/1 as a train and test dataset. The first 80% of the data was used for training and the rest for testing. The results of this experiment show that our model can play a better prediction. © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Long short-term memory

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A Three-Stage Cutting Simulation System Based on Mass-Spring Model

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computer Modeling in engineering & Sciences 2021年第4期127卷 117-133页

作者： Xiaorui Zhang Jiali Duan Wei Sun Tong Xu Sunil Kumar Jha Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Faculty of Information Technology University of Information Technology and ManagementRzeszow35-225Poland

The cutting simulation of soft tissue is important in virtual *** includes three major challenges in computation:Soft tissue simulation,collision detection,and handling,as well as soft tissue *** order to address the earlier challenges,we propose a virtual cutting system based on the mass-spring *** this system,MSM is utilized to simulate the soft tissue *** stress is introduced to the model for simulating the shrinking effect of soft tissue in ***,a cylinder-based collision detection method is used to supervise the collision between surgical tools and soft ***,we simulate the cutting operation with a three-stage cutting method with swept volume,B´ezier curve,and an algorithm named shortest distance nodes matching *** order to verify the system performance,we carry out three validation experiments on the proposed system:Cutting accuracy experiment,collision detection validation,and practical cutting *** indicate that our system can well perform the shrinking effect of soft tissue in *** system has fast and accurate collision ***,the system can reconstruct smooth incisions vividly.

关键词： Mass-spring model collision algorithm virtual surgery soft tissue simulation

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Delay-Tolerant Rendezvous-Based Data Collection for Target Tracking in Large-Scale Wireless Sensor networks with UGV 1

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Zhang, Jian Xu, Jiang Wang, Tianbao College of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing210044 China School of Electrical and Information Engineering Jiangsu University Zhenjiang212013 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

Energy efficiency receives significant attention in wireless sensor networks. In this paper, a UGV is employed as an energy-efficient solution to prolong the network lifetime in target tracking. Data collection strategies for target tracking are investigated including the amount of data and the transmitted distances. For contributed data, the quantization technology is exploited for energy efficiency. Considering the uncertainty of sensing data, we determine a group from intra-cluster members to gather data. And then, we formulate our design a selection optimization problem, maximizing the utilization of the quality of contributed data using information matrix. As a result, we develop an optimization algorithm named rendezvous-based data collection (RDC). Furthermore, two stages of data collection for target tracking are analyzed with a UGV. Simulations verify that the proposed scheme achieves network energy saving as well as energy balance in the framework of target tracking. © 2019, Springer Nature Switzerland AG.

关键词： Target tracking

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