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10th International Conference on Information Security Practice and Experience, ISPEC 2014

作者： Zhou, Hongwei Wu, Xin Shi, Wenchang Yuan, Jinhui Liang, Bin Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing China School of Information Renmin University of China Beijing China Information Engineering University Zhengzhou China

ISBN: (纸本)9783319063195

Combining short instruction sequences originated only from existing code pieces, Return Oriented Programming (ROP) attacks can bypass the code-integrity effort model. To defeat this kind of attacks, current approaches check every instruction executed on a processor, which results in heavy performance overheads. In this paper, we propose an innovative approach, called HDROP, to detecting the attacks. It utilizes the observation that ROP attacks often make branch predictor in modern processors fail to determine the accurate branch destination. With the support of PMC (Performance Monitoring Counters) that is capable of counting performance events, we catch the abnormal increase in branch mis-prediction and detect the existence of ROP attacks. In HDROP, each basic unit being checked consists of hundreds of instructions rather than a single one, which effectively avoids significant performance overheads. The prototype system we developed on commodity hardware shows that HDROP succeeds in detecting ROP attacks, and the performance tests demonstrate that our approach has acceptably lower overheads. © 2014 Springer International Publishing.

关键词： Computers

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Spatio-Temporal neighbors adaptive learning with two-point differences for ocean subsurface temperature reconstruction from 1960 to 2022

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International Journal of Digital Earth 2025年第1期18卷

作者： Wang, An Su, Hua Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education College of Computer and Data Science Fuzhou University Fuzhou China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education The Academy of Digital China Fuzhou University Fuzhou China National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology Fuzhou University Fuzhou China Department of Geography Ghent University Ghent Belgium

Long time series and accurate subsurface temperature data in the global ocean are essential for ocean warming and climate change studies. The sparse in situ observations in the pre-Argo era hinder the reconstruction of long-time series observational data for the global ocean. This study proposes a novel Adaptive Spatio-TEmporal Neighbors with two-point differences (ASTEN) method for subsurface temperature reconstruction, which adaptively learns and adjusts spatio-temporal neighbors depending on the distribution of in situ observations to ensure robust gaps-filling performance across four dimensions. By integrating geoscience domain knowledge and utilizing spatiotemporal autocorrelation, ASTEN simultaneously learns the spatial pattern and temporal variation of subsurface temperature, and significantly enhances the interpretability and accuracy of ocean temperature reconstructions over a long time series compared to the DINCAE and DINEOF. The ASTEN reconstructed temperature data for the upper 1000 m from 1960 to 2022 can effectively track the ocean warming process for more than six decades. This study demonstrates the ASTEN method is well suited for subsurface temperature reconstruction, and holds great potential in the gaps-filling of sparse ocean observations with high missing rates over a large scale. The new reconstruction of subsurface temperature can effectively reduce the uncertainty of subsurface ocean warming analysis. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Global warming

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A Systematic Review of Multi-Sensor Information Fusion for Equipment Fault Diagnosis

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Lin, Tantao Ren, Zhijun Zhu, Linbo Zhu, Yongsheng Feng, Ke Ding, Weiping Yan, Ke Beer, Michael Xi'an Jiaotong University Key Laboratory of Education Ministry for Modern Design & Rotor-Bearing System Xi'an710049 China Xi'an Jiaotong University Frontier Institute of Science and Technology Xi'an710049 China Xi'an Jiaotong University School of School of Chemical Engineering and Technology Xi'an710049 China Xi'an Jiaotong University School of Mechanical Engineering Xi'an710049 China Nantong University School of Artificial Intelligence and Computer Science Nantong226019 China City University of Macau Faculty of Data Science Macau999078 China Leibniz University Institute for Risk and Reliability Hannover30167 Germany University of Liverpool Department of Civil and Environmental Engineering LiverpoolL69 3BX United Kingdom Tongji University International Joint Research Center for Resilient Infrastructure International Joint Research Center for Engineering Reliability and Stochastic Mechanics Shanghai200092 China

In contrast to fault diagnosis relying solely on a single sensor, the method of multi-sensor information fusion for fault diagnosis (MSIFFD) broadens the spectrum of available information sources. It is renowned for its high accuracy and reliability, traits that have attracted growing attention within the research community and led to the generation of a substantial body of publications. However, there is currently a lack of a comprehensive and systematic review in this domain. Thereby, this review aims to thoroughly explore all research achievements in the field of MSIFFD. At the outset, an analysis is undertaken to delineate the fusion level of multi-sensor information, with a specific focus on its location and types of inputs and outputs within the information flow. Subsequently, an examination of the six primary fundamental operations for amalgamating multi-sensor information is undertaken to clarify the motivations and processes involved in information fusion across various operations. Following this, factors influencing fusion diagnostics and strategies aimed at improving their performance are examined to explore approaches for enhancing fusion accuracy. The subsequent sections delve into the analysis of sensor types and application scenarios, providing a reference guide for practical applications. Finally, this review outlines potential future challenges in the field of MSIFFD and provides a range of recommendations and possible solutions for consideration. © 1963-2012 IEEE.

关键词： Information fusion

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Regulation of morphology and visible light-driven photocatalysis of WO_(3)nanostructures by changing pH

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Rare Metals 2021年第7期40卷 1738-1745页

作者： You-Shu Fan Xiao-Li Xi Yang-Si Liu Zuo-Ren Nie Lin-Yan Zhao Qing-Hua Zhang College of Materials Science and Engineering Key Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaBeijing University of TechnologyBeijing 100124China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of TechnologyBeijing 100124China

The controlled preparation of hexagonal tungsten trioxide(h-WO_(3))nanostructures was achieved by adjusting the pH of the precursor *** effect of the pH on the morphology,elemental composition,and photocatalytic performance of the samples was characterized via X-ray diffraction(XRD),scanning electron microscopy,energy dispersive X-ray spectroscopy,and Raman ***-visible(UV-Vis)spectra were used to evaluate the absorbance and the photocatalytic performance of methylene ***(PL),electrochemical impedance spectroscopy,photocurrent response and Brunauer-Emmett-Teller(BET)were used to study the optical properties,electrical performance,and specific surface area of the WO_(3)-nanostructures,*** results indicate that the WO_(3) nanorods prepared at pH=1.0 exhibit the highest photocatalytic performance(87.4%in 1 h),whereas the WO_(3) nanoblocks prepared at p H=3.0 show the *** photocatalytic performance of the one dimensional(1 D)-nanorods can be attributed to their high specific surface area and charge transfer *** h-WO_(3) nanostructures were synthesized via a simple method and without a capping *** show an excellent photocatalytic performance,which is promising for their application in environment purification.

关键词： h-WO_(3) Morphology pH Photocatalysis Charge transfer Optoelectrical properties

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Learning dynamic bayesian network with immune evolutionary algorithm

Learning dynamic bayesian network with immune evolutionary a...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Jia, Hai-Yang Liu, Da-You Yu, Peng Key Laboratory of Symbolic Computing and Knowledge Engineering Juin University Ministry of Education Changchun China

ISBN: (纸本)078039092X

Dynamic Bayesian Networks (DBNs) are directed graphical models of stochastic processes, How to learn the structure of DBNs from data is a hot problem of research. In this paper the author presents an Immune evolutionary algorithm for learning the network structure of DBNs. The results of contrast experiment prove that the constringency rate is more rapid than EGA-DBN algorithms. © 2005 IEEE.

关键词： Learning systems

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LLA: A New High Precision Mobile Node Localization Algorithm Based on TOA

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Journal of Communications 2010年第8期5卷 604-611页

作者： Li, Ruixue Fang, Zhiyi College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Mobile node localization is one of the challenging and crucial issues in wireless sensor networks. The paper proposed a new approach to mobile localization, called LLA (Lee Localization Algorithm), to mitigate TOA measurement errors. The algorithm was divided into three phases: (1) pre-ranging algorithm was proposed to initialize localization by employing TOA method;(2) refinement algorithm was designed to filter out bad nodes;(3) smallest circle covering algorithm was developed to deal with good nodes to complete the localization. Experimental results show that the presented approach efficiently eliminates the effects of the measurement bias and obtains a high accuracy of 2m as well as low complexity, outperforming traditional trilateration. © 2010 ACADEMY PUBLISHER.

关键词： Sensor nodes

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Applications of molten salt and progress of molten salt electrolysis in secondary metal resource recovery

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International Journal of Minerals,Metallurgy and Materials 2020年第12期27卷 1599-1617页

作者： Xiao-li Ming Feng Li-wen Zhang Zuo-ren Nie College of Materials Science and Engineering Key Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaBeijing University of TechnologyBeijing 100124China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of TechnologyBeijing 100124China

Molten salt is an excellent medium for chemical reaction,energy transfer,and *** salt innovative technologies should be developed to recover metals from secondary resources and reserve metals from primary natural *** these technologies,molten salt electrolysis is an economic and environment-friendly method to extract metals from waste *** the perspective of molten salt characteristics,the application of molten salts in chemistry,electrochemistry,energy,and thermal storage should be comprehensively *** review discusses further directions for the research and development of molten salt electrolysis and their use for metal recovery from various metal wastes,such as magnet scrap,nuclear waste,and cemented carbide *** is placed on the development of various electrolysis methods for different metal containing wastes,overcoming some problems in electrolytes,electrodes,and electrolytic *** focus is given to future development directions for current associated processing obstacles.

关键词： molten salt application molten salt electrochemistry resource recycling cemented carbide scrap

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Model counting with boolean algebra and extension rule

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Journal of Convergence Information Technology 2010年第7期5卷 7-7页

作者： Xu, Youjun Ouyang, Dantong Ye, Yuxin College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Model counting is an important problem in artificial intelligence and is applied in several areas of information science. Extension rule is a method which could be used to count models. But it's not appropriate when clause length is short or clause number is huge. After studying extension rule, we found that the satisfiability problem could be solved by hitting set algorithms. And the models could be counted with extension rule after calculating hitting sets of a clause set. Therefore, we proposed an algorithm MCBE in this paper. With Boolean algebra, MCBE could easily calculate hitting sets of a clause set. Then, it gives the number of models with extension rule. The test results show that when clause length is short and clause number is big enough, the algorithm is more efficiency than the algorithm CDP and CER.

关键词： Boolean algebra

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A novel combine forecasting method for predicting news update time

Journal of Software

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Journal of Software 2012年第12期7卷 2787-2793页

作者： Wang, Mengmeng Zuo, Xianglin Zuo, Wanli Wang, Ying College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin Unversity Changchun China

With the rapid development of Internet, information provided by the Internet has shown explosive growth. In the face of massive and constantly updated information on the Internet, how the user can fast access to more valuable and more information has become one of the hot spots. The time of Web Page update appears to be erratic, so forecasting the update time of news reports is even more difficult. From the view of application, we can use mathematical models to maximize the approximation of variation, although it cannot be completely accurate. So is the predicting the update time of news which helps in improving the news crawler's scheduling policy. In this paper, we proposed a combined predict algorithm for news update. In order to predict the update time of news, firstly, we applied the Exponential Smoothing method to our dataset, and we also have selected the optimal parameters. Secondly, we leveraged the Naive Bayes Model for prediction. Finally, we combined two methods for Combination Forecasting, as well as made a compare with former methods. Through the experiments on Sohu News, we show that Combination Forecasting method outperforms other methods while estimating localized rate of updates. © 2012 ACADEMY PUBLISHER.

关键词： Websites

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Multiparticipant Federated Feature Selection Algorithm With Particle Swarm Optimization for Imbalanced data Under Privacy Protection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1002-1016页

作者： Hu, Ying Zhang, Yong Gong, Dunwei Sun, Xiaoyan China University of Mining and Technology School of Information and Control Engineering Xuzhou221008 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun130012 China

In the real world, data describing the same learning task may be distributed in different institutions (called participants), and these participants cannot share their own data due to the need of privacy protection. How to select an optimal feature subset on the basis of ensuring the data privacy of each participant is an important and challenging topic. At the same time, data on part participants show imbalanced or even miss some classes, further increasing the difficulty of solving this kind of problem. In view of this, by introducing a trusted third party to process and integrate optimal information from participants, this article proposes a multiparticipant federated evolutionary feature selection algorithm for imbalanced data under privacy protection. First, a multilevel joint sample filling strategy with multiple participants (called sampling-rough selection-fine tuning strategy) is proposed to fill imbalanced or empty classes on each participant while ensuring data privacy. Then, a federated evolutionary feature selection method based on particle swarm optimization (PSO) is proposed by periodically sharing the optimal feature subsets obtained by PSOs on participants. Finally, the proposed algorithm is applied to 15 test datasets, and compared with several typical imbalanced feature selection algorithms and two kinds of ensemble feature selection algorithms. The experimental results show that the proposed algorithm can significantly promote the ability of each participant on processing imbalanced datasets, and improve the classification accuracy of obtained feature subsets while protecting the participants' data privacy. © 2020 IEEE.

关键词： Clustering algorithms

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