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作者： Sun, Huiyu Hu, Siyuan McIntosh, Suzanne Cao, Yi Department of Computer Science New York University United States Jiangsu Engineering Centre of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology China

Millions of trips are made every day by taxis and Uber in New York City. We first employ big data technologies to analyze this vast dataset: Apache Spark is used for data processing and classification, Apache Hive is used for data storage, and MapReduce is used for data profiling. Since taxis and Uber are equipped with GPS sensors, we then visualize a mobile sensor network over New York City separated into fine-sized regions each acting as a mobile sensing node. Each location on the network falls into a region and is classified into one of three categories based on which service dominates the particular region: Yellow taxi, Green taxi, or Uber. We utilize logistic regression to classify a region into one of the three categories. Our classification algorithm is then used to analyze the interaction between taxi and Uber, for example to quantify the expansion of Uber. Experiments run on the Spark cluster show our classifier achieves an accuracy of over 85% scored on the 2014 taxi and Uber dataset. Finally, we propose a trip recommendation system for users using classification results together with a web service application. © 2018 Taiwan Academic network Management Committee. All rights reserved.

关键词： Classification (of information)

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Intelligent Mobile Drone System Based on Real-Time Object Detection

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Journal on Artificial Intelligence 2019年第1期1卷 1-8页

作者： Chuanlong Li Xingming Sun Junhao Cai School of Computer and Software Nanjing University of Information Science and TechnologyNanjingChina Jiangsu Engineering Centre of Network Monitoring Nanjing210044China School of Politics Economics and International RelationsUniversity of ReadingBerkshireRG66BGUnited Kingdom

Drone also known as unmanned aerial vehicle(UAV)has drawn lots of attention in recent *** as one of the most popular drones has great potential in both industrial and academic *** drones are capable of taking off vertically and flying towards any *** researches of drones mainly focus on their mechanical structures and movement *** aircraft movement is usually controlled by a remote controller manually or the trajectory is pre-programmed with specific *** drones typically use mobile device together with remote controllers to realize flight control and video *** different functions on mobile devices can result in different behaviors of drones *** the development of deep learning in computer vision field,commercial drones equipped with camera can be much more intelligent and even realize autonomous *** the past,running deep learning based algorithms on mobile devices is highly computational intensive and time *** paper utilizes a novel real-time object detection method and deploys the deep learning model on the modern mobile device to realize autonomous object detection and object tracking of drones.

关键词： Drone UAV CNN object detection mobile application Ios

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A Novel Quantum Stegonagraphy Based on Brown States

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computers, Materials & Continua 2018年第7期56卷 47-59页

作者： Zhiguo Qu Tiancheng Zhu Jinwei Wang Xiaojun Wang Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and TechnologyNanjing 210044P.R.China School of Computers&Software Nanjing University of Information Science and TechnologyNanjing 210044P.R.China School of Electronic Engineering Dublin City UniversityDublinIreland

In this paper,a novel quantum steganography protocol based on Brown entangled states is *** new protocol adopts the CNOT operation to achieve the transmission of secret information by the best use of the characteristics of entangled *** with the previous quantum steganography algorithms,the new protocol focuses on its anti-noise capability for the phase-flip noise,which proved its good security resisting on quantum ***,the covert communication of secret information in the quantum secure direct communication channel would not affect the normal information transmission process due to the new protocol’s good *** the number of Brown states transmitted in carrier protocol is many enough,the imperceptibility of the secret channel can be further *** aspect of capacity,the new protocol can further expand its capacity by combining with other quantum steganography *** to that the proposed protocol does not require the participation of the classic channel when it implements the transmission of secret information,any additional information leakage will not be caused for the new algorithm with good *** detailed theoretical analysis proves that the new protocol can own good performance on imperceptibility,capacity and security.

关键词： Quantum steganography quantum secure direct communication entanglement anti-noise robustness

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Study on Initial Alignment Under Large Misalignment Angle

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Journal of Information Hiding and Privacy Protection 2019年第3期1卷 95-108页

作者： Qi Wang Changsong Yang Shaoen Wu School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Science Ball State UniversityMuncieUSA School of Automation Nanjing University of Information Science and TechnologyNanjing210044China

Misalignment angle error model describing the SINS mathematical platform error is presented in this paper following the idea of small misalignment angle error model and large azimuth misalignment angle error *** can be considered that the three misalignment angles are independent of the rotational sequence in the misalignment error model,but not suitable in the large misalignment error *** error angle of Euler platform is used to represent the three misalignment angles from theoretical navigation coordinate system to computational navigation coordinate *** Euler platform error angle is utilized to represent the mathematical platform error and its physical meaning is very *** SINS nonlinear error model is deduced by using the error angle of Euler platform and is simplified under the condition of large azimuth error and small *** simplified results are more comprehensive and accurate than the large azimuth misalignment error *** damping SINS algorithm and its error model are proposed to change the structure of the strapdown inertial navigation algorithm by using the external damping *** accuracy of SINS error model of large Euler platform error angle is simulated,and has strong practicability in initial alignment and is conducive to reducing the amount of calculation.

关键词： Misalignment error model large misalignment angle Euler platform error angle SINS.

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Identifying Materials of Photographic Images and Photorealistic computer Generated Graphics Based on Deep CNNs

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computers, Materials & Continua 2018年第5期55卷 229-241页

作者： Qi Cui Suzanne McIntosh Huiyu Sun School of Computer and Software Nanjing University of Information Science and TechnologyNing Liu RoadNo.219Nanjing210044China Jiangsu Engineering Centre of Network Monitoring Ning Liu RoadNo.219Nanjing210044China Computer Science Department New York UniversityNew YorkNY 10012USA

Currently,some photorealistic computer graphics are very similar to photographic *** computer generated graphics can be forged as photographic images,causing serious security *** aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime *** paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network *** results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.

关键词： Image identification CNN DNN DCNNs computer generated graphics

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A Fusion Steganographic Algorithm Based on Faster R-CNN

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computers, Materials & Continua 2018年第4期55卷 1-16页

作者： Ruohan Meng Steven G.Rice Jin Wang Xingming Sun School of Computer and Software Nanjing University of Information Science and TechnologyNing Liu RoadNo.219Nanjing210044China Jiangsu Engineering Centre of Network Monitoring Ning Liu RoadNo.219Nanjing210044China Department of Mathematics and Computer Science Northeastern State University TahlequahOK 74464USA School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China

The aim of information hiding is to embed the secret message in a normal cover media such as image,video,voice or text,and then the secret message is transmitted through the transmission of the cover *** secret message should not be damaged on the process of the cover *** order to ensure the invisibility of secret message,complex texture objects should be chosen for embedding *** this paper,an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret ***,complex texture regions are selected based on a kind of objects detection ***,three different steganographic methods were used to hide secret message into the selected block *** results show that the approach enhances the security and robustness.

关键词： Faster R-CNN fusion steganography object detection CNNs information hiding.

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A Survey of Image Information Hiding Algorithms Based on Deep Learning

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computer Modeling in engineering & Sciences 2018年第12期117卷 425-454页

作者： Ruohan Meng Qi Cui Chengsheng Yuan School of Computer and Software Nanjing University of Information Science and TechnologyNing Liu RoadNo.219Nanjing210044China Jiangsu Engineering Centre of Network Monitoring Ning Liu RoadNo.219Nanjing210044China Department of Electrical and computer Engineering University of Windsor401 Sunset AvenueWindsorONN9B 374Canada.

With the development of data science and technology,information security has been further *** order to solve privacy problems such as personal privacy being peeped and copyright being infringed,information hiding algorithms has been *** information hiding is to make use of the redundancy of the cover image to hide secret information in *** that the stego image cannot be distinguished from the cover image,and sending secret information to receiver through the transmission of the stego *** present,the model based on deep learning is also widely applied to the field of information *** paper makes an overall conclusion on image information hiding based on deep *** is divided into four parts of steganography algorithms,watermarking embedding algorithms,coverless information hiding algorithms and steganalysis algorithms based on deep *** these four aspects,the state-of-the-art information hiding technologies based on deep learning are illustrated and analyzed.

关键词： Steganography deep learning steganalysis watermarking coverless information hiding.

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Instance Retrieval Using Region of Interest Based CNN Features

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Journal of New Media 2019年第2期1卷 87-99页

作者： Jingcheng Chen Zhili Zhou Zhaoqing Pan Ching-nung Yang Jiangsu Engineering Center of Network Monitoring&Department of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Department of Electrical and computer Engineer University of WinsorN9B3P4WinsorONCanada Department of Computer Science and Information Engineering National Dong Hwa University ShoufengHualien 974Taiwan

Recently, image representations derived by convolutional neural networks(CNN) have achieved promising performance for instance retrieval, and they outperformthe traditional hand-crafted image features. However, most of existing CNN-based featuresare proposed to describe the entire images, and thus they are less robust to backgroundclutter. This paper proposes a region of interest (RoI)-based deep convolutionalrepresentation for instance retrieval. It first detects the region of interests (RoIs) from animage, and then extracts a set of RoI-based CNN features from the fully-connected layerof CNN. The proposed RoI-based CNN feature describes the patterns of the detected RoIs,so that the visual matching can be implemented at image region-level to effectively identifytarget objects from cluttered backgrounds. Moreover, we test the performance of theproposed RoI-based CNN feature, when it is extracted from different convolutional layersor fully-connected layers. Also, we compare the performance of RoI-based CNN featurewith those of the state-of-the-art CNN features on two instance retrieval *** results show that the proposed RoI-based CNN feature provides superiorperformance than the state-of-the-art CNN features for in-stance retrieval.

关键词： Image retrieval instance retrieval RoI CNN convolutional layer,convolutional feature maps

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Quantum Algorithm for Appointment Scheduling

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Journal of Quantum Computing 2019年第2期1卷 111-118页

作者： Wenbin Yu Yinsong Xu Wenjie Liu Alex Xiangyang Liu Baoyu Zheng Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering Michigan State UniversityEast LansingMI 48824-1266USA National Engineering Research Center for Communications and Network Technology Nanjing University of Posts and TelecommunicationsNanjing210003China

Suppose a practical scene that when two or more parties want to schedule anappointment, they need to share their calendars with each other in order to make itpossible. According to the present result the whole communication cost to solve thisproblem should be their calendars’ length by using a classical algorithm. In this work, weinvestigate the appointment schedule issue made by N users and try to accomplish it inquantum information case. Our study shows that the total communication cost will bequadratic times smaller than the conventional case if we apply a quantum algorithm in theappointment-scheduling problem.

关键词： Quantum algorithm appointment scheduling quantum speed-up

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Quantum Multi-User Detection Based on Coherent State Signals

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Journal of Quantum Computing 2019年第2期1卷 81-88页

作者： Wenbin Yu Yinsong Xu Wenjie Liu Alex Xiangyang Liu Baoyu Zheng Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering Michigan State UniversityEast LansingMI 48824-1266USA National Engineering Research Center for Communications and Network Technology Nanjing University of Posts and TelecommunicationsNanjing210003China

Multi-user detection is one of the important technical problems for moderncommunications. In the field of quantum communication, the multi-access channel onwhich we apply the technology of quantum information processing is still an openquestion. In this work, we investigate the multi-user detection problem based on thebinary coherent-state signals whose communication way is supposed to be seen as aquantum channel. A binary phase shift keying model of this multi-access channel isstudied and a novel method of quantum detection proposed according to the conclusionof the quantum measurement theory. As a result, the average interference betweendeferent users is presented and the average error probability of the quantum detection isderived theoretically. Finally, we show the maximum channel capacity of this effectivedetection for a two-access quantum channel.

关键词： Multi-user detection multi-access channels quantum communication,quantum information processing

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