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An embedded estimating equation for the additive risk model with biased-sampling data

Science China Mathematics 2018年第8期61卷 1495-1518页

作者： Feipeng Zhang Xingqiu Zhao Yong Zhou School of Mathematics and Statistics Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education)Hunan Normal University Department of Applied Mathematics The Hong Kong Polytechnic University School of Statistics East China Normal University Academy of Mathematics and Systems Science Chinese Academy of Sciences

This paper presents a novel class of semiparametric estimating functions for the additive model with right-censored data that are obtained from general biased-sampling. The new estimator can be obtained using a weighted estimating equation for the covariate coefficients, by embedding the biased-sampling data into left-truncated and right-censored data. The asymptotic properties(consistency and asymptotic normality) of the proposed estimator are derived via the modern empirical processes theory. Based on the cumulative residual processes, we also propose graphical and numerical methods to assess the adequacy of the additive risk *** good finite-sample performance of the proposed estimator is demonstrated by simulation studies and two applications of real datasets.

关键词： additive risk model biased-sampling data missing covariates estimating equation model checking

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A Generic Framework for the Engineering of Self-Adaptive and Self-Organising systems

A Generic Framework for the Engineering of Self-Adaptive and...

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Organic computing - Controlled Self-Organization 2008

作者： Marzo Serugendo, Giovanna Di Fitzgerald, John Romanovsky, Alexander Guelfi, Nicolas School of Computer Science and Information Systems Birkbeck College London United Kingdom School of Computing Science University of Newcastle Newcastle upon Tyne United Kingdom Laboratory for Advanced Software Systems University of Luxembourg Luxembourg

This paper provides a unifying view for the engineering of self-adaptive (SA) and self-organising (SO) systems. We first identify requirements for designing and building trustworthy self-adaptive and self-organising systems. Second, we propose a generic framework combining design-time and run-time features, which permit the definition and analysis at design-time of mechanisms that both ensure and constrain the run-time behaviour of an SA or SO system, thereby providing some assurance of its self-* capabilities. We show how this framework applies to both an SA and an SO system, and discuss several current proof-of-concept studies on the enabling technologies. © 2008 Dagstuhl Seminar Proceedings.

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The collaborative P-GRADE Grid Portal

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5th International Conference on Computational Science - ICCS 2005

作者： Lewis, Gareth J. Sipos, Gergely Urmetzer, Florian Alexandrov, Vassil N. Kacsuk, Peter Advanced Computing and Emerging Technologies Centre School of Systems Engineering University of Reading WhiteKnights Reading RG6 6AY United Kingdom MTA SZTAKI Laboratory of Parallel and Distributed Systems H-1518 Budapest Hungary

ISBN: (纸本)9783540260448

Grid portals are increasingly used to provide uniform access to the grid infrastructure. This paper describes how the P-GRADE Grid Portal could be used in a collaborative manner to facilitate group work and support the notion of Virtual Organisations. We describe the development issues involved in the construction of a collaborative portal, including ensuring a consistent view between participants of a collaborative workflow and management of proxy credentials to allow separate nodes of the workflow to be submitted to different grids. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Computational methods

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INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging 23

INCREASE: Inductive Graph Representation Learning for Spatio...

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2023 World Wide Web Conference, WWW 2023

作者： Zheng, Chuanpan Fan, Xiaoliang Wang, Cheng Qi, Jianzhong Chen, Chaochao Chen, Longbiao Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University Xiamen China School of Computing and Information Systems University of Melbourne Melbourne Australia College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781450394161

Spatio-temporal kriging is an important problem in web and social applications, such as Web or Internet of Things, where things (e.g., sensors) connected into a web often come with spatial and temporal properties. It aims to infer knowledge for (the things at) unobserved locations using the data from (the things at) observed locations during a given time period of interest. This problem essentially requires inductive learning. Once trained, the model should be able to perform kriging for different locations including newly given ones, without retraining. However, it is challenging to perform accurate kriging results because of the heterogeneous spatial relations and diverse temporal patterns. In this paper, we propose a novel inductive graph representation learning model for spatio-temporal kriging. We first encode heterogeneous spatial relations between the unobserved and observed locations by their spatial proximity, functional similarity, and transition probability. Based on each relation, we accurately aggregate the information of most correlated observed locations to produce inductive representations for the unobserved locations, by jointly modeling their similarities and differences. Then, we design relation-aware gated recurrent unit (GRU) networks to adaptively capture the temporal correlations in the generated sequence representations for each relation. Finally, we propose a multi-relation attention mechanism to dynamically fuse the complex spatio-temporal information at different time steps from multiple relations to compute the kriging output. Experimental results on three real-world datasets show that our proposed model outperforms state-of-the-art methods consistently, and the advantage is more significant when there are fewer observed locations. Our code is available at https://***/zhengchuanpan/INCREASE. © 2023 ACM.

关键词： Kriging

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HRPDF: A Software-Based Heterogeneous Redundant Proactive Defense Framework for Programmable Logic Controller

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Journal of Computer Science & Technology 2021年第6期36卷 1307-1324页

作者： Ke Liu Jing-Yi Wang Qiang Wei Zhen-Yong Zhang Jun Sun Rong-Kuan Ma Rui-Long Deng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China School of Information Systems Singapore Management UniversitySingapore 689867Singapore

Programmable logic controllers(PLCs)play a critical role in many industrial control systems,yet face increasingly serious cyber *** this paper,we propose a novel PLC-compatible software-based defense mechanism,called Heterogeneous Redundant Proactive Defense Framework(HRPDF).We propose a heterogeneous PLC architecture in HRPDF,including multiple heterogeneous,equivalent,and synchronous runtimes,which can thwart multiple types of attacks against PLC without the need of external *** ensure the availability of PLC,we also design an inter-process communication algorithm that minimizes the overhead of *** implement a prototype system of HRPDF and test it in a real-world PLC and an OpenPLC-based device,*** results show that HRPDF can defend against multiple types of attacks with 10.22%additional CPU and 5.56%additional memory overhead,and about 0.6 ms additional time overhead.

关键词： industrial control system programmable logic controller proactive defense heterogeneous redundant architecture

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A novel fault diagnostic technique for photovoltaic systems based on cascaded forest 1

A novel fault diagnostic technique for photovoltaic systems ...

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1st Workshop on Smart Internet of Things, SmartIoT 2017

作者： Hu, Liangqing Ye, Jin Chang, Shengqiang Li, Hongtao Chen, Hongyu School of Computer Electronicsand Information Guangxi University Nanning China Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guangxi Colleges and Universities Guilin China Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin China Shijiazhuang Kelin Electric Co. Ltd. Shijiazhuang China

ISBN: (纸本)9781450355285

A variety of faults often occurduring the operation of PV arrays, which may seriously affect the normal operation of the system, the machine diagnosis of the types of fault has become a hotspot in the field of photovoltaic power generation. This paper proposes a novel fault diagnostic technique for photovoltaic systems based on Cascaded Forest. Through the in-depth analysis of the output of PV arrays froma data platform of ShijiazhuangKelin Electric Co, the input variables of the diagnosis model are obtained. Compared with other fault diagnosis methods for the PV array, the proposed method can work under a small number of tagged data and the system can be run online and real-time. Finally, the experimental results show that the fault diagnosis method for the PV array based on the cascading forests can effectively detect four types of fault for PV array such as short-circuit, open-circuit, abnormal degradation and partial shading. This method has a good value for the intelligent fault diagnosis of PV. © 2017 Association for computing Machinery.

关键词： information management

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DMA-Net: A Deep Multi-Attention Network for Brain Tumor Classification on MRI Images 7

DMA-Net: A Deep Multi-Attention Network for Brain Tumor Clas...

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7th International Conference on Biological information and Biomedical Engineering, BIBE 2024

作者： Yu, Wanlong Ma, Zhaopeng Zhang, Xiang He, Bingbing Lang, Xun Zhang, Yufeng Bai, Zhengyao Lv, Wenbing School of Information Yunnan University Yunnan Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Yunnan Kunming650504 China

ISBN: (纸本)9783800762910

Accurate and impartial classification of brain tumors is crucial for early diagnosis and treatment. Deep learning technology can effectively represent and utilize the visual content of images, playing a key role in more precise medical image analysis. In this study, we proposed an advanced deep multi-attention network (DMA-Net) to address the challenge of brain tumor classification on MRI images. The proposed DMA-Net employs a novel multi-layer attention mechanism, integrating efficient channel attention (ECA), spatial attention (SPA), depthwise separable convolutions with vision transformer (DWSC-ViT), and group attention (GA) to enhance the processing of complex neural imaging. Our approach is characterized by its ability to effectively balance detailed image representation and computational efficiency, maintaining excellent classification accuracy even with a substantial reduction in model parameters. With the integration of these new modules, DMA-Net outperformed other state-of-the-art (SOTA) mobile networks, achieving a classification accuracy of 96.70% and an AUC of 0.9971 in brain tumor classification. Furthermore, DMA-Net is the most compact model among the SOTA networks, demonstrating significant potential for deployment on mobile devices to enhance application efficiency. © VDE VERLAG GMBH.

关键词： Magnetic resonance imaging

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Energy efficient scheduling of application components via brownout and approximate markov decision process

arXiv

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arXiv 2017年

作者： Xu, Minxian Buyya, Rajkumar Laboratory School of Computing and Information Systems University of Melbourne

Unexpected loads in cloud data centers may trigger overloaded situation and performance degradation. To guarantee system performance, cloud computing environment is required to have the ability to handle overloads. The existing approaches, like Dynamic Voltage Frequency Scaling and VM consolidation, are effective in handling partial overloads, however, they cannot function when the whole data center is overloaded. Brownout has been proved to be a promising approach to relieve the overloads through deactivating application non-mandatory components or microservices temporarily. Moreover, brownout has been applied to reduce data center energy consumption. It shows that there are trade-offs between energy saving and discount offered to users (revenue loss) when one or more services are not provided temporarily. In this paper, we propose a brownout-based approximate Markov Decision Process approach to improve the aforementioned trade-offs. The results based on real trace demonstrate that our approach saves 20% energy consumption than VM consolidation approach. Compared with existing energy-efficient brownout approach, our approach reduces the discount amount given to users while saving similar energy consumption. Copyright © 2017, The Authors. All rights reserved.

关键词： Energy efficiency

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Practical Teaching Reform of Programming Courses Based on Online Coding Platforms 18th

Practical Teaching Reform of Programming Courses Based on On...

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18th International Conference on Computer Science and Education, ICCSE 2023

作者： Yuan, Guowu Yue, Kun Hu, Kuang School of Information Science and Engineering Yunnan University Yunnan Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan Kunming650504 China

ISBN: (纸本)9789819707904

Programming proficiency stands as one of the most vital competencies for students majoring in computer-related disciplines. This paper scrutinizes the issues prevailing in the cultivation of programming skills. Notably, it emphasizes an imbalance in teaching, whereby concepts and syntax receive undue attention while hands-on programming experiences are inadequately incorporated. Furthermore, the absence of standardized assessment mechanisms and avenues for advanced students to enhance their skills compounds these challenges. To augment students’ programming capabilities, we have established an online coding platform, facilitating a practical teaching reform in programming courses guided by "learning, practicing, certification and competing". "Learning" entails knowledge learning, "practicing" involves extensive programming practicing, "certification" signifies reaching programming competency standards, and "competing" denotes participation in programming competitions to enhance skill sets. Over seven years, this implementation has markedly improved students’ programming prowess. It has also led to advancements in certified software professional (CSP) and various programming competition outcomes, effectively embodying the "promoting learning and teaching through competitions" philosophy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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Solution-based phase saving and MaxSAT for employee scheduling: A computational study 12

Solution-based phase saving and MaxSAT for employee scheduli...

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12th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2018

作者： Demirovic, Emir Winter, Felix Musliu, Nysret Stuckey, Peter J. School of Computing and Information Systems University of Melbourne Australia Chrstn.Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling DBAI TU Wien Austria

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