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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Degan Zhang Jinyu Du Ting Zhang Peng Yang Hongrui Fan Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China

ISBN: (数字)9781728198668

ISBN: (纸本)9781728198675

We propose an oriented edge computing nodes energy optimized QoS constrained routing algorithm. The mechanism of this algorithm is to optimize the network energy consumption and extend the network life cycle by creatively combining the edge computing technology to preprocess the original data of the node, accelerating the transmission and processing of effective data, accelerating the algorithm convergence by using the way of automata interacting with the environment and controlling the dormant activation state of the node. Through experimental testing and comparison, this paper gave the Multi-QoS constrained routing algorithm for Edge computing and Node energy optimization algorithm (MQEN), which can meet the requirements of end-to-end delay and reliability service with multi-QoS constraints when significantly reducing network energy consumption.

关键词： Energy consumption Learning automata Quality of service Routing Acceleration Optimization Edge computing

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new Method of MSCA for Edge computing

New Method of MSCA for Edge Computing

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IEEE International Conference on Smart Internet of Things (SmartIoT)

作者： De-gan Zhang Hao-li Zhu Ting Zhang Jia-xu Wang Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Tianjin China Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin

ISBN: (数字)9781728165141

ISBN: (纸本)9781728165158

By innovative use of edge computing technology to construct a node data cache model and step-by-step calculation of node channel separation, a multi-strategy channel allocation algorithm (MSCA) for edge computing is proposed. The mechanism of this algorithm is to use edge computing technology to pre-store the data in the nodes in the multicast tree and calculate the channel separation between the nodes, and then select the transmission channel number of the node with the least interference to avoid mutual interference between node information transmissions. Through experimental tests and comparisons, the MSCA algorithm for edge computing presented in this paper can minimize channel interference and overall network energy consumption while satisfying throughput and end-to-end delay.

关键词： Edge computing Interference Computational modeling Delays Peer-to-peer computing Channel allocation Protocols

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An Adaptive POI Recommendation Algorithm by Integrating User’s Temporal and Spatial Features in LBSNs

An Adaptive POI Recommendation Algorithm by Integrating User...

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作者： Miao Li Wenguang Zheng Yingyuan Xiao Xu Jiao Tianjin Key Laboratory of Intelligence Computing & New Software Technology Tianjin University of Technology Department of Liberal Education Tianjin Foreign Studies University

With the rapid development of Internet technology and global positioning technology, location-based social networks（LBSNs）have emerged. Massive check-in data generated by LBSNs can be employed to explore users’ behavior preferences, and enable a wide range of location-based social services. The most straightforward service is Point of Interest（POI） recommendation, which help users to discover their desired places. In order to achieve effective and precise POI recommendation, complicated high-dimensional data need to be handled, i.e., user-geographical position-visiting timecategory of the visiting place. Besides, such data usually suffer from a data sparsity problem. To this end, this paper proposes a novel POI recommendation model that incorporates spatial and temporal preferences of the users. We propose a tensor factorization-based approach and a Voronoi diagram-based approach to model the impact of temporal and spatial features on users’ preference, respectively. Then, a fusion framework is proposed to calculate similarities between different uses by combining both temporal and spatial preferences of the ***, an adaptive collaborative filtering approach is applied to generate recommendation list. The experiments results on the Foursquare and the Gowalla datasets shows that our model has higher recommendation performance than other comparison models.

关键词： POI Recommendation Temporal Spatial Tensor Factorization

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A new method of mobile Ad Hoc network routing based on improved GF strategy 3

A new method of mobile Ad Hoc network routing based on impro...

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3rd IEEE International Conference on Smart Internet of Things, SmartIoT 2019

作者： Li, Ke Zhang, De-Gan Qiu, Jian-Ning Chen, Lu Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education Tianjin China

ISBN: (纸本)9781728134888

We propose a new mobile ad hoc network routing method based on improved GF (greedy forwarding) strategy in this paper. In the greedy forwarding phase, the reliable communication area is calculated, and then the quality of the link is evaluated according to the relative displacement between the nodes and the maintenance time of the link. Then, according to the quality of the link, the distance from the candidate node to the destination node, and the number of the neighbor nodes, the metric value is obtained, and the node with the large metric value is selected as the next hop. When a routing hole occurs, the waiting forwarding mode is used for a period of time. After a period of time, if the current node is still a routing hole node, the right-hand rule and the left-hand rule are used, and the bypass mode is performed simultaneously. By considering three factors of the deflection angle and the residual energy of the node and the maintenance time of the link, the forwarding node as the next hop with the highest priority value is selected in each direction. According to experiments, the method of this paper has achieved good experimental results. © 2019 IEEE.

关键词： Energy utilization

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MedSteGAN: Medical Embedding-Optimized Steganography with Improved GAN

SSRN

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SSRN 2023年

作者： Peng, Yuxiang Fu, Chong Zheng, Yu Tian, Yunjia Cao, Guixing Chen, Junxin School of Computer Science and Engineering Northeastern University Liaoning Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Liaoning Shenyang110819 China Department of Information Engineering The Chinese University of Hong Kong Ma Liu Shui Shatin New Territories Hong Kong Institute of Telecommunication Satellite China Academy of Space Technology Beijing100094 China School of Software Dalian University of Technology Liaoning Dalian116621 China

Medical diagnosing systems contain sensitive information, especially the resulting certificate of diagnosis that involves the patient’s privacy, required to be protected carefully. An effective way is to secretly embed privacy-sensitive information into medical-generated images, eventually being viewed as arbitrary images of nobody/nothing in public. The current research line of medical steganography targets simple data-hiding methods, yet remains barren in optimal embedding and stronger robustness. To fill this gap, we propose an end-to-end steganographic framework for medical images. Our idea is to integrate medical-image adaptive steganography with a generative adversarial network (GAN), named MedSteGAN. To improve both robustness, we design an optimized U-shape gen- erator that extracts features more efficiently utilizing larger kernel convolutions and the ReLU6 function. Also, deconvolutions are replaced by upsampling and convolution layers to avoid the checkerboard effect. To enhance security and image quality, we employ visual quality loss and mean squared error (MSE) loss based on the multi-scale structural similarity index metric (MS- SSIM) and the high-pass filters, respectively. Extensive experiments demonstrate that MedSteGAN outperforms state-of-the-art steganographic schemes in terms of robustness and image quality. © 2023, The Authors. All rights reserved.

关键词： Image quality

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Research on Character Vector Generation Method Based on Words and Context

Research on Character Vector Generation Method Based on Word...

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作者： Yiying Wang Hongyun Ning Tianjin Key Laboratory of Intelligence Computing &New Software Technology Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing & New Software Technology Tianjin University of Technology

In order to solve the problem of character information limitation and the neglect of polysemy,a character vector generation method based on words and context is *** of all,introduce the concept of context *** the fact that the same word has different meanings in different contexts,some even have the opposite meanings,therefore,to correctly understand the meaning of Chinese words,we must fully consider the context in which it is *** sentence in which the character or word is located is expressed in the form of a vector called context ***,construct the polysemous storage of *** the importance of context and the polysemy of words,this paper expands the expression of the original word vector,and adds a context linked list for each word *** multiple semantics of words are stored in multiple context vectors in the linked list,so as to solve the polysemy problem of ***,a character vector generation method based on words and context is *** target character vector is calculated by using the word vectors of all words containing the target character and its context ***,attention mechanism is *** calculating,the current character context and the word context are compared,according to the character and word context similarity to distribute weights,so that the words with more similar context make greater contribution to the generation of the character *** method not only add the word information to the character,but also distinguishes different semantics according to the context of the character,and makes all words participate in the calculation of the character vector according to different *** experiment uses the character vector evaluation method based on external tasks,taking the news title similarity task as an example,comparing the performance of the traditional CBOW method and the new words and context based character generation method in the t

关键词： CBOW character vector context Attention mechanism

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SG-PBFT: A secure and highly efficient blockchain PBFT Consensus Algorithm for internet of vehicles

arXiv

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arXiv 2021年

作者： Xu, Guangquan Liu, Yihua Xing, Jun Luo, Tao Gu, Yonghao Liu, Shaoying Zheng, Xi Vasilakos, Athanasios V. The Big Data School Qingdao Huanghai University Qingdao266427 China College of Intelligence and Computing Tianjin University Tianjin300350 China The International Engineering Institute Tianjin University Tianjin300350 China The College of Intelligence and Computing Tianjin University Tianjin Tianjin300350 China The school of Computer Science Beijing University of Posts and Telecommunications Beijing100876 China The Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing100876 China School of Informatics and Data Science Hiroshima University Japan The Department of Computing Macquarie University SydneyNSW2109 Australia The University of Technology Sydney Australia The Fuzhou University Fuzhou China Lulea University of Technology Lulea Sweden

The Internet of Vehicles (IoV) is an application of the Internet of things (IoT). It faces two main security problems: (1) the central server of the IoV may not be powerful enough to support the centralized authentication of the rapidly increasing connected vehicles, (2) the IoV itself may not be robust enough to single-node attacks. To solve these problems, this paper proposes SG-PBFT: a secure and highly efficient PBFT consensus algorithm for Internet of Vehicles, which is based on a distributed blockchain structure. The distributed structure can reduce the pressure on the central server and decrease the risk of single-node attacks. The SG-PBFT consensus algorithm improves the traditional PBFT consensus algorithm by using a score grouping mechanism to achieve a higher consensus efficiency. The experimental result shows that our method can greatly improve the consensus efficiency and prevent single-node attacks. Specifically, when the number of consensus nodes reaches 1000, the consensus time of our algorithm is only about 27% of what is required for the state-of-the-art consensus algorithm (PBFT). Our proposed SG-PBFT is versatile and can be used in other application scenarios which require high consensus efficiency. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

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On Pricing Problem of Two-Channel Reverse Supply Chain Considering Consumer Psychology under “Internet +” Environment

On Pricing Problem of Two-Channel Reverse Supply Chain Consi...

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International Conference on Systems and Informatics (ICSAI)

作者： Yi Chen Bin Sun Meiling Feng Junqing Sun Tianjin Key Laboratory of Intelligent Computing & Novel Software Tianjin University of Technology Tianjin China

ISBN: (数字)9781728152561

ISBN: (纸本)9781728152578

In recent years, “Internet +” and e-commerce technology have had a profound impact on the recycling industry. Consumer psychology, as the most important factor in the positive sales chain, has received little attention in the recycling field. Based on the consumer's acceptance of online recycling channels and sensitivity to recycling prices, this paper investigates a two-channel reverse supply chain system consisting of the brand owner and a dismantling center. Firstly, the pricing strategy model, which takes consumer psychology into account, is established based on the Stackelberg game. It is found that the consumer's acceptance of the online recycling channel will reduce the profit of the dismantling center, but has no effect on the profit of the brand owner. Consumers' sensitivity to price will increase the profits of both the brand owner and the dismantling center, and will also make the optimal pricing of both parties tend to be fixed. Finally, the simulation experiment is carried out to verify the influence of psychological indicators on the pricing strategy and profit of the brand owner and dismantling center, and the optimal pricing strategy of both models is obtained after the online acceptance index and price sensitivity index are determined.

关键词： Recycling Pricing Psychology Consumer electronics Games Analytical models Supply chains

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Research and Construction of Word Vector Extension Structure Based on Context

Research and Construction of Word Vector Extension Structure...

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作者： Yiying Wang Hongyun Ning Tianjin Key Laboratory of Intelligence Computing & New Software Technology Tianjin University of Technology

The CBOW(Continuous Bag-of-Words) model is a three-layer forward neural network that predicts the central word vector by the fixed-size window information. In fact,context has a very important role in understanding the meaning of words. However, the context information of the fixed window size is partial and it is not enough to represent the whole context. Due to the polysemy of Chinese words, the same word may have different semantics in different contexts, while the traditional CBOW method ignores the polysemy of ***, this paper proposes a context-based word vector extension structure for the above problems. The main contents are as follows:(1) Introducing the concept of context vector. The entire sentence in which the target word is located is represented by a vector.(2) Constructing the polysemy storage method of words, adding a contextual list to each word vector, so that the multiple semantics of the words can be effectively distinguished.(3) Based on the word vector extension structure of this paper, a new character vector generation model is proposed, and the effect of the new model and the traditional CBOW model in the news headline similarity sorting task is compared. The experimental results show that the new character vector generation model based on the extension structure of the word vector obtains better result.

关键词： Vector Research and Construction of Word Vector Extension Structure Based on Context

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A novel method of android malware detection based on ensemble learning algorithm 8

A novel method of android malware detection based on ensembl...

引用

2018 8th International Workshop on Computer Science and Engineering, WCSE 2018

作者： Zhao, Jingyi Mo, Xiuliang Zheng, Qiao Tianjin Intelligent Computing and Software New Technology Key Laboratory School of computer Science and Engineering Tianjin University of Technology China

ISBN: (纸本)9789811178610

Android is popular for mobile devices in recent years. As the risk of malware is sharply increasing in Android platform, Android malware detection has become an important research topic. However, the current work shows that the detection of malware still needs to be reformed. Many current results suggest a modification of permissions or a combination of permissions and intents, but Android's fragmentation issues and requiring rooting, hindering the widespread adoption of those methods. Many approaches have been proposed to detect this attack by modifying the Android OS. Existing anti-viruses depend on signature databases that need to be updated from time to time and are unable to detect zero-day malware. The Android Operating system allows inter-application communication through the use of component reuse by using intents. A malware detection model is developed based on ensemble learning algorithms and on the basis of the random forest in WEKA. The method we proposed can take a better efficiency and precision. © Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, WCSE 2018. All rights reserved.

关键词： Android (operating system)

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