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Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

Journal of Quantum Computing 2019年第1期1卷 1-8页

作者： Yajie Sun Yanqing Yuan Qi Wang Sai Ji Lihua Wang Shaoen Wu Jie Chen Qin Zhang Jiangsu engineering Centre of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Science Ball State UniversityMuncieUSA

A method is proposed based on the transmissibility function and the OnlineSequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to theimpact damage of composite materials. First of all, the transmissibility functions of theundamaged signals and the damage signals at different points are calculated. Secondly,the difference between them is taken as the damage index. Finally, principal componentanalysis (PCA) is used to reduce the noise feature. And then, input to the online sequencelimit learning neural network classification to identify damage and confirm the damagelocation. Taking the amplitude of the transmissibility function instead of the accelerationresponse as the signal analysis for structural damage identification cannot be influencedby the excitation amplitude. The OS-ELM algorithm is based on the ELM (ExtremeLearning Machine) algorithm, in-creased training speed also increases the recognitionaccuracy. Experiment in the epoxy board shows that the method can effectively identifythe structural damage accurately.

关键词： Impact damage transmissibility function OS-ELM

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Coverless Image Steganography Method Based on Feature Selection

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Journal of Information Hiding and Privacy Protection 2019年第2期1卷 49-60页

作者： Anqi Qiu Xianyi Chen Xingming Sun Shuai Wang Guo Wei School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Centre of Network Monitoring Nanjing210044China Department of Radiology and BRIC University of North Carolina at Chapel HillNorth Carolina27599USA Mathematics and Computer Science University of North Carolina at PembrokeNorth Carolina28372USA

A new information hiding technology named coverless information hiding is *** uses original natural images as stego images to represent secret *** focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret *** this paper,we use three kinds of features which are Local Binary Pattern(LBP),the mean value of pixels and the variance value of *** this basis,we realize the transmission of secret ***,the hash sequence of the original cover image is obtained according to the description of the feature,and then the sequence of the secret information and the hash sequence of the original cover image are matched one by *** the values are not the same,the image blocks of the original cover image are replaced according to the secret information to get the stego *** paper explores the effect of three features on the visual quality of stego *** results show that the feature LBP is the best.

关键词： Coverless-image-steganography(CIS) feature visual quality.

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An improved method for fingerprints' singular points detection based on orientation field partition

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2013年第1期6卷 225-234页

作者： Mei, Yuan Hou, Rongtao Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China

As a global feature of fingerprints, singular point plays important roles in fingerprint model, synthesis fingerprint, fingerprint classification, fingerprint alignment and so on. In our previous work, a rapid and effective fingerprint singular points detection method was proposed. That method detects singular points based on partitioning the orientation field into a serious non-overlapping homogenous areas. However, for the same orientation field, different partition schemes may lead to different singular point extraction results, especially for poor quality fingerprint images. For eliminating the uncertainty, we employ three different partition schemes simultaneously for each orientation field, and combine the three extraction results to make the final decision. Experiment proves that: this method is more accuracy than the previous one.

关键词： Extraction

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Real-time detection and recognition of landmarks for mobile robot in indoor scenes

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2013年第4期8卷 329-341页

作者： Xue, Yanbing Zhang, Hua Ju, Yucui Wang, Jin Key Laboratory of Computer Vision and System Tianjin University of Technology Tianjin 300191 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China

This paper proposes a robust real-time artificial landmarks detection and recognition system for indoor mobile robot. Landmarks detection and recognition for indoor robots faces two major difficulties, one is the illumination changes and the other is processing speed. In this paper, first, histograms of oriented gradient (HOG) features are extracted to resolve the problem of illumination changes. Second, AdaBoost based algorithm is used in detection phase to increase the processing speed. Finally, RBF-SVM classifier is used for recognition. Experimental results show a high detection and recognition accuracy and the processing speed is about 10 frames per second.

关键词： Adaptive boosting

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Research and development of mobile application for android platform

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2014年第4期9卷 187-198页

作者： Ma, Li Gu, Lei Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 China

Today, as the developing of hardware of mobile is getting better, the performance index is much higher than the actual requirements of the software configuration. Phone's features more depend on software. As the Android operating system is getting more popular, the application based on Android SDK attracts much more attention. But now, some of the Android application interface is too cumbersome, pop-up ads is overmuch and the function is too single, these cause some inconvenience to the users. This article presents the application by eliminating the redundancy. Three kinds of applications are developed base on Java and Android SDK --- Weibo client, video player and audio player. The audio player uses the ContentResolver and Curor to obtain music files and plays the music by using the Service Components to call the Media Player class in the background. The video player uses the Media Player class provided by Android SDK. This class loads the file through URL, realize the multimedia file parsing by calling the Open Core Library, which is at the bottom of Android, through JNI and by calling the Surface Flinger interface to realize the video files' playback. The users' data is collected through the Sina open platform called by Sina client and the data will be returned under the format of JSON by the Sina server. The system uses the OAuth authentication method for user authorization to complete the login process. The specific functions of this system are developed based on Android Weibo SDK. The interfaces of these Android apps are pretty and the operation is smooth. What's more, the cumbersome interface and excessive advertising are eliminated, so that users are able to manipulate these apps more conveniently and smoothly. © 2014 SERSC.

关键词： Android (operating system)

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A packet loss tolerated method for data integrity protection in wireless sensor networks

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2016年第7期11卷 1-12页

作者： Wang, Baowei Yan, Jingzhou Li, Tao Sun, Xingming Ma, Li School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing210044 China Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology Nanjing210044 China

Among existing watermarking methods for data integrity protection in wireless sensor networks (WSNs), the problem of packet loss has not been considered. Most of methods treat packet loss as anomaly attacks, hardly being used in real network. The paper proposes a packet loss tolerated method for data integrity protection in wireless sensor networks based on double-level watermarking and threshold control. Sensory data collected by nodes generate digital watermarking for integrity detection. Watermarking will be stored in sensory data. The network will have watermarking verification and packet loss rate analysis in the sink to ensure data integrity. Through the experiment in real sensor network, this method can effectively protect data integrity with low power. © 2016 SERSC.

关键词： Wireless sensor networks

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Error analysis of time delay based on ultrasonic phased array structural health monitoring

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Journal of computers (Taiwan) 2018年第4期29卷 176-184页

作者： Ji, Sai Gu, Feihong Sun, Yajie Wang, Jin Jiangsu engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China School of Information Engineering Yangzhou University Yangzhou225002 China

Ultrasonic phased array technology becomes significant in structural health monitoring with its flexible beam deflection and strong focusing performance. The transducer is used to complete the multiple directions scanning of the structure. During the process of beam scanning, the signal exciting from each element needs to add a time delay in time domain, due to the difference to the distance from each element to the far field target point, so that the excitation signal can reach the target point and the far field at the same time. Besides, in the process of receiving and transmitting process, it also needs to add a time delay for the response signal, so that the sensor can receive the reflection signal from the preset deflection angle. Therefore, the error will be generated in the calculation of time delay. Making the anti-rust aluminum plate as the experimental object, the process of ultrasonic phased array structural health monitoring will be introduced. And then the reason of time delay error will be pointed out and analyzed. © 2018 computer Society of the Republic of China. All Rights Reserved.

关键词： Time delay

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A Multi-Objective Data Placement Method for IoT Applications Over Big Data Using NSGA-II

A Multi-Objective Data Placement Method for IoT Applications...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Xiaolong Xu Renhao Gu Yuan Yuan Kai Peng Yadang Chen Wanchun Dou Alex X. Liu Department of Computer Science and Engineering Michigan State University MI USA Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Engineering Huaqiao University Quanzhou Fujian China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

The Internet of Things has been developing fast since it connects various devices for human beings to use, monitor or configure these devices, which brings great convenience. Generally, the big data generated by the sensors of IoT applications needs to be collected, stored and processed to realize the services of such applications. For the execution of task from the IoT applications, it may need a variety of datasets for tasks to access and process. However, it is still a challenge to realize the data placement method when taking into account the resource utilization and the energy consumption in data centers along with the data access time for the task sets to access the datasets. In view of this challenge, a multi-objectives data placement method for IoT applications over big data is proposed in this paper. Technically, multi-objectives are analyzed first. Then a heuristic data placement method is designed based on Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Consequentially, experimental evaluation and comparison analysis are conducted to validate the efficiency and effectiveness of our proposed method.

关键词： Manganese Handheld computers Internet of Things Switches Green computing Social computing Blockchain

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COVID TCL:A Joint Metric Loss Function for Diagnosing COVID-19 Patient in the Early and Incubation Period

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computer Systems Science & engineering 2023年第10期47卷 187-204页

作者： Rui Wen Jie Zhou Zhongliang Shen Xiaorui Zhang Sunil Kumar Jha Department of Electromechanical Engineering Zhejiang Business Technology InstituteNingbo315012China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Department of Physics Faculty of ScienceAdani UniversityAhmedabadIndia

Convolution Neural networks(CNN)can quickly diagnose COVID-19 patients by analyzing computed tomography(CT)images of the lung,thereby effectively preventing the spread of ***,the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 *** reduces the model’s classification sensitivity,resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 *** solve the problem,this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification,combining softmax loss to design a jointly supervised metric loss function COVID Triplet-center Loss(COVID-TCL).Triplet loss can increase inter-class discreteness,and center loss can improve intra-class ***,COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation ***,we use the extreme gradient boosting(XGBoost)as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture,to further improve the CNN-based model’s classification effect and operation *** experiment shows that the classification accuracy of the model proposed in this paper is 97.41%,and the sensitivity is 97.61%,which is higher than the other 7 reference *** COVID-TCL can effectively improve the classification sensitivity of the CNN-based model,the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect.

关键词： Covid-19 diagnose convolutional neural networks XGBoost COVID triplet-center loss early and incubation COVID-19 patients

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An Energy-Aware Virtual Machine Scheduling Method for Cloudlets in Wireless Metropolitan Area networks

An Energy-Aware Virtual Machine Scheduling Method for Cloudl...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Xiaolong Xu Yuancheng Li Yuan Yuan Kai Peng Wenbin Yu Wanchun Dou Alex X. Liu Department of Computer Science and Engineering Michigan State University MI USA Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Engineering Huaqiao University Quanzhou Fujian China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Currently, mobile applications, such as interactive gaming, virtual reality, and natural language processing, are becoming more computational intensive, but the computing capacity of mobile devices is limited. An effective way to solve this problem is offloading the tasks to nearby cloudlets, which are some small mobile data centers deployed in wireless metropolitan area network (WMAN). and consume a large amount of energy. Excessive energy consumption brings about some negative effects, including increased carbon dioxide emissions, aggravating the greenhouse effect, etc. In view of this challenge, we propose an energy-aware virtual machine (VM) scheduling method for cloudlets in WMAN. Technically, an optimization model is designed to formalize our problem. Then, based on VM Live Migration Technology, a corresponding energy saving VM scheduling method abbreviated as MFEA is proposed to determine which VMs should be migrated and where they should be migrated. Finally, experimental data demonstrate that the proposed method is effective.

关键词： Cloud computing Performance evaluation Energy consumption Internet of Things Green computing Social computing Blockchain

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