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Capability description and discovery of Internetware entity

Science China(Information Sciences) 2010年第4期53卷 685-703页

作者： WANG PuWei1*, JIN Zhi2,3* & LIU HongYan4 1Key laboratory of data engineering and knowledge engineering of the Ministry of Education, Renmin University of China, Beijing 100872, China 2Key laboratory of High Confidence Software Technologies of the Ministry of Education, Peking University, Beijing 100871, China 3Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100190, China 4Department of Management Science and engineering, Tsinghua University, Beijing 100084, China 1. Key Laboratory of Data Engineering and Knowledge Engineering of the Ministry of Education Renmin University of China Beijing 100872 China2. Key Laboratory of High Confidence Software Technologies of the Ministry of Education Peking University Beijing 100871 China3. Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing 100190 China4. Department of Management Science and Engineering Tsinghua University Beijing 100084 China

Internetware can be formed through aggregation of Internetware entities bottom-up to satisfy the user's requirements. In the process, capability description of Internetware entity plays an important role. This paper proposes a capability description of Internetware entity based on environment ontology. The environment ontology includes environment entities and possible interactions with the environment entities in a particular domain. Tree-like hierarchical state machines are also included in the ontology to describe domain life-cycle of the environment entities. On the basis of the ideas, the capability of Internetware entity is embodied by interacting with environment entities and the changes of the environment entities during the interactions. Finally, this paper describes the matchmaking between capability descriptions of Internetware entities to support the discovery of Internetware entity. An example of online education course is given to illustrate the ideas.

关键词： Internetware capability description domain environment ontology tree-like hierarchical state machine

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Performance study on logging to another main memory database

Performance study on logging to another main memory database

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作者： Qin, Xiongpai Xiaoyun, Zhou Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing 100872 China Department of Computer Science and Technology Xuzhou Normal University Xuzhou Jiangsu 221008 China

ISBN: (纸本)9788988678183

In update intensive main memory database applications, huge volume of log records is generated, to maintain the ACID properties of the database system, the log records should be persistent efficiently. Delegating logging of one main memory database to another main memory database is proposed. The scheme is elaborated in detail in terms of architecture, logging & safeness levels, checkpointing, and recovery. Strict durability and relax durability are provided. When some form of non-volatile memory is used to temporarily holding log records, not only logging efficiency is improved, but also the scheme could guarantee full ACID of the system. We also propose using parallel logging to speedup log persistence by writing logs to multiple disks in parallel. Since interconnection network techniques progress by leaps and bounds, the scheme eliminates the concern about whether the system's overall performance may be slowed down by bandwidth and latency limitations. Experiment results demonstrate the feasibility of the proposal.

关键词： Interconnection networks (circuit switching)

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Gaussian Model-Based Fully Convolutional Networks for Multivariate Time Series Classification 12

Gaussian Model-Based Fully Convolutional Networks for Multiv...

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12th IEEE International Conference on Big knowledge, ICBK 2021

作者： Tai, Changyang Yang, Ze Zhang, Huicheng Wu, Gongqing Lv, Junwei Bao, Xianyu Key Laboratory of Knowledge Engineering With Big Data of Ministry of Education Hefei University of Technology Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China Shenzhen Academy of Inspection and Quarantine Shenzhen China

ISBN: (纸本)9781665438582

Multivariate time series (MTS) classification has been regarded as one of the most challenging problems in data mining due to the difficulty in modeling the correlation of variables and samples. In addition, high-dimensional MTS modeling has a large time and space consumption. This paper proposes a novel method, Gaussian Model-based Fully Convolutional Networks (GM-FCN), to improve the performance of high-dimensional MTS classification. Each original MTS is converted into multivariate Gaussian model parameters as the input of FCN. These parameters effectively capture the correlation be-tween MTS variables and significantly reduce the data scale by aligning an MTS size to its dimension. FCN is designed to learn more in-depth features of MTS based on these parameters for modeling the correlation between samples. Thus, GM-FCN can not only model the correlation between variables, but also the correlation between samples. We compare GM-FCN with nine state-of-the-art MTS classification methods, INN-ED, INN-DTW-i, INN-DTW-D, KLD-GMC, MLP, ResNet, Encoder, MCNN, and MCDCNN, on four high-dimensional public datasets, experimen-tal results show that the accuracy of G M - FCN is significantly superior to the others. Besides, the training time of GM-FCN is dozens of times faster than FCN using the original equal-length MTS data as input. © 2021 IEEE.

关键词： data mining

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A new steganography without embedding based on adversarial training 20

A new steganography without embedding based on adversarial t...

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2020 ACM Turing Celebration Conference - China, ACM TURC 2020

作者： Jiang, Wenjie Hu, Donghui Yu, Cong Li, Meng Zhao, Zhong-Qiu Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education and College of Computer Science and Information Engineering !!!Hefei University of Technology Hefei China College of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China

ISBN: (纸本)9781450375344

Steganography is an art to hide information in the carriers to prevent from being detected, while steganalysis is the opposite art to detect the presence of the hidden information. With the development of deep learning, several state-of-the-art steganography and steganalysis based on deep learning techniques have been proposed to improve hiding or detection capabilities. Generative Adversarial Networks (GANs) based steganography directly uses the minimax game between the generator and discriminator, to automatically generate steganography algorithms resisting being detected by powerful steganalysis. The steganography without embedding (SWE) based on GANs, where the generated cover images themselves are stego ones carrying secret information has shown its state-of-the-art steganography performance. However, SWE based on GANs has serious weaknesses, such as low information recovery accuracy, low steganography capacity and poor natural showing. To solve these problems, this paper proposes a new SWE based on adversarial training, with carefully designed generator, discriminator and extractor, as well as their loss functions and optimized training mode. The proposed method can achieve a very high information recovery accuracy (100% in some cases), and at the same time improve the steganography capacity and image quality. © 2020 ACM.

关键词： Steganography

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An MRC Framework for Semantic Role Labeling 29

An MRC Framework for Semantic Role Labeling

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29th International Conference on Computational Linguistics, COLING 2022

作者： Wang, Nan Li, Jiwei Meng, Yuxian Sun, Xiaofei Qiu, Han Wang, Ziyao Wang, Guoyin He, Jun Key Laboratory of Data Engineering and Knowledge Engineering of MOE School of Information Renmin University of China China Shannon.AI Zhejiang University China Tsinghua University China University of Leeds United Kingdom Amazon Alexa AI

Semantic Role Labeling (SRL) aims at recognizing the predicate-argument structure of a sentence and can be decomposed into two sub-tasks: predicate disambiguation and argument labeling. Prior work deals with these two tasks independently, which ignores the semantic connection between the two tasks. In this paper, we propose to use the machine reading comprehension (MRC) framework to bridge this gap. We formalize predicate disambiguation as multiple-choice machine reading comprehension, where the descriptions of candidate senses of a given predicate are used as options to select the correct sense. The chosen predicate sense is then used to determine the semantic roles for that predicate, and these semantic roles are used to construct the query for another MRC model for argument labeling. In this way, we are able to leverage both the predicate semantics and the semantic role semantics for argument labeling. We also propose to select a subset of all the possible semantic roles for computational efficiency. Experiments show that the proposed framework achieves state-of-the-art or comparable results to previous work. Code is available at https://***/ShannonAI/MRC-SRL. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Semantics

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A Deletable and Modifiable Blockchain Scheme Based on Record Verification Trees and the Multisignature Mechanism

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Computer Modeling in engineering & Sciences 2021年第7期128卷 223-245页

作者： Daojun Han Jinyu Chen Lei Zhang Yatian Shen Yihua Gao Xueheng Wang Henan Key Laboratory of Big Data Analysis and Processing Henan UniversityKaifeng47500China Institute of Data and Knowledge Engineering Henan UniversityKaifeng47500China School of Computer and Information Engineering Henan UniversityKaifeng47500China Department of Network and Finance Agricultural Bank of China Limited Xuchang BranchXuchang461000China School of Software Pingdingshan UniversityPingdingshan467000China Department of Network and Finance Agricultural Bank of China Limited Nanyang BranchNanyang473000China

As one of the most valuable technologies,blockchains have received extensive attention from researchers and industry circles and are widely applied in various ***,data on a blockchain cannot be *** a result,it is impossible to clean invalid and sensitive data and correct erroneous ***,to a certain extent,hinders the application of blockchains in supply chains and Internet of *** address this problem,this study presents a deletable and modifiable blockchain scheme(DMBlockChain)based on record verification trees(RVTrees)and the multisignature scheme.(1)In this scheme,an RVTree structure is designed and added to the block *** RVTree can not only ensure that a record is true and valid but,owing to its unique binary structure,also verify whether modification and deletion requests are valid.(2)In DMBlockChain,the multisignature mechanism is also *** mechanism requires the stakeholders’signatures for each modification or deletion request and thus ensures that a record will not be modified arbitrarily.A user’s request is deemed valid only if it is dually verified by the RVTree and the multisignature *** analysis finds that DMBlockChain can provide a secure and valid means for modifying and deleting records in a block while ensuring the integrity of the block and that DMBlockChain can effectively save space in some scenarios that require frequent records modification.

关键词： Blockchain record verification trees multisignature DMBlockChain

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Assessing the Improvements Brought by Artificial Intelligence on the Prediction of Aerodynamic Coefficients

Assessing the Improvements Brought by Artificial Intelligenc...

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International Conference on Artificial Intelligence and Smart Environment, ICAISE 2022

作者： Zerouaoui, Jad Alaoui, Altaf Ettaki, Badia Chakir, ElMahjoub Laboratory of Material and Subatomic Physics Faculty of Sciences Ibn Tofail University Campus Universitaire BP 133 Kenitra Morocco LyRICA: Laboratory of Research in Computer Science Data Sciences and Knowledge Engineering School of Information Sciences Rabat Rabat Morocco

ISBN: (纸本)9783031262531

The implementation of Artificial Intelligence in the aerospace field is fairly new and various domains of the aerospace discipline are to be explored. This paper provides a general review on the upbringing and improvements of Artificial Intelligence as a pilar of the next generation of scientific research. Applications and developments brought by Artificial Intelligence and Deep Learning to the aerospace industry generally, mainly the prediction of aerodynamic coefficients and design optimization using intricate neural networks replicating the process of the human brain. Scientific developments participated in improving major areas in the aerospace field. Due to the expensive and time-consuming process related to the complexity of the geometry and the precision of the results required, researchers integrated surrogate models based on Deep Learning in order to improve the calculation process of the aerodynamic coefficients. On one hand, this paper introduces and discusses the general architecture of several networks used to enhance the calculation ability of the machine, while presenting the process of each work along with recounting the different methods employed. On the other hand, a discussion regarding the challenges presented with utilizing Computational Fluid Dynamics while assessing and comparing the results brought by surrogate models based on efficiency and time consumption is also tackled. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

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Cloud detection from visual band of satellite image based on variance of fractal dimension

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Journal of Systems engineering and Electronics 2019年第3期30卷 485-491页

作者： TIAN Pingfang GUANG Qiang LIU Xing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-Time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-Media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

关键词： cloud detection visual image satellite image variance of local fractal dimension (VLFD)

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Generalized Unique Game Problem

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Journal of Computational Information Systems 2012年第16期8卷 6551-6557页

作者： Cui, Peng Key Laboratory of Data Engineering and Knowledge Engineering School of Information Resource Management Renmin University of China Beijing 100872 China

In this paper, the author defines Generalized Unique Game Problem (GUGP), where weights of the edges are allowed to be negative. Two special types of GUGP are illuminated, GUGP-NWA, where the weights of all edges are negative, and GUGP-PWT (ρ), where the total weight of all edges are positive and the negative-positive ratio is at most ρ. The author investigates the counterpart of the Unique Game Conjecture on GUGP-PWT (ρ). The author shows that Unique Game Conjecture on GUGP-PWT (1) holds true, and Unique Game Conjecture on GUGP-PWT (1=2) holds true, if the 2-to-1 Conjecture holds true. The author poses an open problem whether Unique Game Conjecture holds true on GUGP-PWT (ρ) with 0 < ρ < 1. © 2012 Binary Information Press.

关键词： Approximation algorithms

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Joint Subcarrier and Power Allocation in D2D Communications Underlaying Cellular Networks

Joint Subcarrier and Power Allocation in D2D Communications ...

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IEEE Conference on Wireless Communications and Networking

作者： Caihong Kai Yan Wu Xinyue Hu Wei Huang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Hefei China

ISBN: (数字)9781728131061

ISBN: (纸本)9781728131078

For the high density of users and accompanying network service requirements in the cellular system, Device-to-Device (D2D) communication is a promising technology to cope with the increasing wireless traffic demands by reusing spectrum resources. In practice, the wireless signal is easy to be eavesdropped in D2D communications underlaying cellular networks, hence, ensuring a secure communication for cellular user equipments (CUEs) is an urgent and meaningful problem. In this paper, we propose a joint subcarrier and power allocation scheme for maximizing the sum data rate of D2D pairs, meanwhile protecting the CUEs against eavesdropping. Specifically, in the proposed scheme, we first quantify the security performance with the secrecy data rate, and obtain the closed-form expression for the optimal power allocation of CUEs and D2D pairs by tightening the quality of service (QoS) and secrecy rate requirement constraints of CUEs. Based on the obtained power allocation solution, by searching the optimal mapping relationship between CUEs and D2D pairs, we develop a subcarrier assignment strategy with the Hungarian algorithm to solve it, which can further enhance the sum data rate of D2D pairs. Simulation results demonstrate that the proposed scheme can significantly yield better performance than other schemes.

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