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SSRN 2025年

作者： Liu, Ping Li Lü, Zheng Yoon, Seong-Min School of Mathematics and Statistics Chongqing Technology and Business University Chongqing China Chongqing Key Laboratory of Statistical Intelligent Computing and Monitoring Chongqing Technology and Business University Chongqing China Limited Shanghai China China Foreign Exchange Trade System China Department of Economics Pusan National University Busan Korea Republic of

In the context of the global economy facing complex challenges and the increasing tension in US–China relations, studying the effect of these tensions on the volatility, correlation, and hedging effects of gold and crude oil prices is particularly important. This study explores three main aspects of this issue. First, the GARCH-MIDAS approach is implemented to assess the impact of the US–China Tensions Index (UCT) on the long-term volatility of gold and crude oil. Second, the DCC-MIDAS-UCT model is constructed to explore the impact of US–China tensions on the dynamics between gold and crude oil. Finally, the time-varying correlation and covariance matrices estimated by the DCC-MIDAS-UCT model are applied to a portfolio to assess the effectiveness of the model in enhancing the hedging effect of gold against oil. These findings indicate that UCT exerts a statistically significant positive influence on long-term volatility in international crude oil prices. However, its transmission mechanism to gold price fluctuations is more complex. When examining its long-term impact on gold prices exclusively, a notably positive correlation emerges;however, upon incorporating the control variables, this relationship turns negative. This suggests that the gold market may be hedging against the impact of UCT through the risk-premium channel. Furthermore, the DCC-MIDAS-UCT model, which considers UCT, significantly improves the hedging effect of gold against oil in risk management. This study not only enriches our understanding of market dynamics but also serves as an effective guide for investors and policymakers to better cope with market risks. © 2025, The Authors. All rights reserved.

关键词： Risk management

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A universally stable and energy-efficient scheduling protocol for packet switching network

A universally stable and energy-efficient scheduling protoco...

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12th Annual IEEE International Symposium on Network computing and Applications, NCA 2013

作者： Shi, Yangguang Zhang, Fa Liu, Zhiyong Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9780768550436

Energy efficiency is becoming an important issue in networks. Although some research works have been devoted to this topic, only a little attention has been paid to the stability of the network equipped with the energy conservation mechanisms. In fact, we find that the stability of networks can be undermined in the worst case if it isn't considered with care by the energy conservation *** this paper, we propose an energy-efficient scheduling protocol which can guarantee the stability of the network in all cases. We start by building a new model which can be used to verify the stability of the network equipped with the energy conservation mechanisms. With this model, we transform the packet scheduling problem to a Job Shop Scheduling problem. For this problem, we propose a time-stamp based work-conserving scheduling algorithm - G-FSA. Compared with existing methods, this scheduling algorithm guarantees a tighter bound on the make span of the jobs. Then, we integrate G-FSA with a time partition approach to generate our energy-efficient packet scheduling protocol. It is proved that the obtained protocol can guarantee the stability of network in all cases. And its approximation ratio in terms of energy efficiency can be bounded by O((1+ )) for any > 0, where is an input parameter depending on the hardware infrastructure. Typically, 1

关键词： Scheduling algorithms

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Modeling and Analysis of Integrated Air Transportation Cooperative Information SoS Based on Complex Network Theory

Modeling and Analysis of Integrated Air Transportation Coope...

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2022 Chinese Automation Congress, CAC 2022

作者： Li, Song Wu, Zhenfeng Jong, Hans De State Key Laboratory of Air Traffic Management System and Technology Nanjing China DFS Aviation Services GmbH Beijing China

ISBN: (纸本)9781665465335

In this paper, a system of systems (SoS) modeling and evaluation method based on complex network theory is proposed for the Integrated Air Transportation Cooperative Information SoS (IATCI-SoS). In the proposed method, the target SoS is abstracted into a network model composed of multiple types of nodes and their interconnections, so as to facilitate its standardized description and quantitative evaluation. On this basis, SoS evaluation indicators in the aspects of flexibility, robustness, and efficiency are designed and applied to the case simulation of the 'Belt and Road Initiative' air transportation collaborative information environment. By simulating the network model of the current SoS and the target IATCI-SoS, both of them are evaluated and analyzed. Simulation results show the advantages and disadvantages of the target IATCI-SoS, and validate that the proposed method can provide theoretical support for the top-level architecture construction of the future IATCI-SoS. © 2022 IEEE.

关键词： Complex networks

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Integrating DBMSs as a read-only execution layer into Hadoop

Integrating DBMSs as a read-only execution layer into Hadoop

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11th International Conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2010

作者： An, Mingyuan Wang, Yang Wang, Weiping Sun, Ninghui Key Laboratory of Computer System and Architecture Graduate University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769542874

To obtain the efficiency of DBMS, HadoopDB combines Hadoop and DBMS, and claims the superiority over Hadoop in terms of performance. However, the approach of HadoopDB is simply putting MapReduce onto unmodified single-machined DBMSs which has several obvious weaknesses. In essence, HadoopDB is a parallel DBMS with fault tolerance, which incurs unnecessary overhead due to the DBMS legacy. Instead of augmenting DBMS with Hadoop techniques, we propose a new system architecture integrating modified DBMS engines as a read-only execution layer into Hadoop, where DBMS plays a role of providing efficient readonly operators rather than managing the data. Besides the obtained efficiency from DBMS engine, there are other advantages. The modified DBMS engine is able to directly process data from the HDFS (Hadoop Distributed File system) files at the block level, which means that the data replication can be handled by HDFS naturally, and the blocklevel parallelism is easily achieved. The global index access mechanism is added according to the MapReduce paradigm. The data loading speed is also guaranteed by directly writing the data into HDFS with simplified logic. Experiments show that our system outperforms both original Hadoop and HadoopDB styled system. © 2010 IEEE.

关键词： Database systems

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A Graph Reasoning Model Based on Multiple Types of Nodes 7

A Graph Reasoning Model Based on Multiple Types of Nodes

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7th International Conference on Big Data and Information Analytics, BigDIA 2021

作者： Liu, Yibing Huo, Lijun Zhou, Gang Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China National University of Defense Technology Key Laboratory of Information System Engineering Changsha China

ISBN: (纸本)9781665424660

Multi-hop machine reading comprehension (MRC) depends on the model to answer a semantically related question based on the given supporting text. In this study, inspired by previous research about Graph Neural Network(GNN), we develop a new graph covering three kinds of nodes: Sentence, Entity, Candidate. A corresponding MRC method based on graph inference is proposed, called SEC reasoner. The advantage of SECr is that it adopts different granular information as graph nodes, which can execute a more comprehensive reasoning. Our proposed model first initialize the node representations by co-Attention, multi-head attention and self-Attention based on context embedding. SECr then employs GNN based information transfer algorithms to collect evidences from the node encoding, and calculates a score for choosing the answer. In experiments, we evaluate the model on two popular benchmark datasets-WikiHop and MedHop. SECr reachs accuracy rates of 71.6%, 63.1% respectively, which is a competitive result. In addition, a comprehensive analysis proves the effectiveness and interpretability of the SECr. © 2021 IEEE.

关键词： Semantics

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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TraCemop: Towards Federated Learning with Traceable Contribution Evaluation and Model Ownership Protection

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IEEE Transactions on Mobile computing 2025年

作者： Liu, Jingwei Zhou, Zihan Sun, Rong Liu, Lei Lu, Rongxing Dustdar, Schahram Niyato, Dusit Ministry of Education Engineering Research Center of Blockchain Technology Application and Evaluation China Xidian University Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Xidian University Guangzhou Institute of Technology Guangzhou510555 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Queen's University School of Computing KingstonONK7L 2N8 Canada TU Wien Distributed Systems Group Austria UPF ICREA Barcelona Spain Nanyang Technological University School of Computer Science and Engineering Singapore

Federated Learning (FL) allows multiple clients to collaboratively train machine learning models without the need to share their local private data. As a result, it can effectively address the issue of data fragmentation. Nevertheless, insufficient evaluation of individual contributions and the lack of protections for both the intellectual property rights (IPR) of models and client privacy can greatly reduce clients' motivations in federated training. To address these challenges, this paper introduces the Traceable Contribution Evaluation and Model Ownership Protection (TraCemop) framework for federated learning, which allows each client to swiftly assess the contributions of others in each round, with integrated support for the traceability of evaluation results. To safeguard the intellectual property of models, a collective watermark is embedded in the global model. Additionally, a secure mechanism for verifying model ownership is also available in case of disputes. Security analysis indicates that TraCemop is capable of resisting data reconstruction attacks as well as various types of model copyright infringements. Finally, we evaluate the proposed framework using two commonly-used datasets, and the experimental results show a significant improvement in the efficiency of contribution evaluation compared to existing methods. Meanwhile, IPR infringement tests on TraCemop reveal that the proposed framework is resilient against malicious efforts to monopolize model ownership. © 2002-2012 IEEE.

关键词： Federated learning

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A Novel Mutual Information based Ant Colony Classifier 5

A Novel Mutual Information based Ant Colony Classifier

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2017 International Conference on Progress in Informatics and computing(PIC)

作者： Hang Yu Xiaoxiao Qian Yang Yu Jiujun Cheng Ying Yu Shangce Gao College of Computer Science and Technology Taizhou University Faculty of Engineering University of Toyama Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

ISBN: (纸本)9781538619797;9781538619780

By constructing a list of IF-THEN rules, the traditional ant colony optimization(ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for *** paper proposes a novel hybrid mutual information based ant colony algorithm(mrAM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier(i.e., AM+)to perform the classification. Experimental results show that the proposed mrAM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.

关键词： ant colony optimization mutual information classification data mining feature selection

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OnRipple: A Distributed Overlay Framework for Targeted Immunization in Large-Scale Networks

OnRipple: A Distributed Overlay Framework for Targeted Immun...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing (SNPD)

作者： Sirui Yang Hai Jin Xiaofei Liao Hong Yao Services Computing Technology and System Laboratory Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Targeted immunization has been studied as an applicable measure for network epidemics. Unless global information is collected, existing targeted strategies are short of strength in organizing a potent structure to spread the vaccines fleetly. We propose a novel dynamic immunization mechanism, called OnRipple, to propagate vaccines in susceptible-infected-removed (SIR) epidemiological model. With a light-weighted, scalable and distributed framework and an "axis" structure, OnRipple builds-up an effective overlay network. Thus, nodes have essential sampling information of the whole network and targeted immunization can be easily implemented. Nodes are also able to radiate vaccines to both nearby and distant participants almost at the same time. We analyze the performance of this strategy by simulations on small-world networks. On average, OnRipple is 34 % faster than traditional targeted immunization. It is proven to be flexible and effective in large-scale peer-to-peer (P2P) networks and scale-free networks.

关键词： Large-scale systems Immune system Peer to peer computing Vaccines Computer worms Analytical models Computer networks Software engineering Artificial intelligence Distributed computing

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A Web-Based Theme-Related Word Set Construction Algorithm

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Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data, APWeb-WAIM 2018

作者： Wu, Yingkai Li, Yukun Hao, Gang Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin Tianjin China

ISBN: (纸本)9783030012977

Constructing theme-related word set is a basic work for establishing theme-oriented information retrieval systems. Nowadays, most of previous studies focus on identifying representative words of a specific document, and few studies pay attention to constructing a word set related to a theme. By analyzing existing keywords extraction methods, this paper proposes a method to automatically construct theme-related word set based on the primary theme-related word set given by domain experts and the well-known websites related to the theme. As the first step, the method uses existing information extraction techniques to obtain the documents from the websites and every document’s keyword set. Then it calculates the correlation degree between the known theme-related word set and the document keyword set, further gets a word set of the document related to the theme based on the document-theme relevance, and merges the word set to the theme-related word set. By using the method, the theme-related word set is supplemented by iteration based on the documents gotten from the theme-related websites. Because there is little research work focusing on this problem and no relevant experimental data set, this paper uses the proposed method to construct theme-related word sets towards two themes "electricity" and "college entrance examination", and we invite domain experts to evaluate the word sets. The results show that a relatively complete theme-related word set can be obtained based on this method, which shows the feasibility of our methods. © 2018, Springer Nature Switzerland AG.

关键词： Websites

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