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A distributed Ensemble of Diverse Deep Learning Models for Predicting COVID-19 Cases 20

A Distributed Ensemble of Diverse Deep Learning Models for P...

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20th international conference on Smart Technologies, EUROCON 2023

作者： Hassan, Mohammad Mehedi Alrakhami, Mabrook S. Elhendi, Ahmed Zohier Alqahtani, Salman A. King Saud University Information Systems Department Ccis Riadh 11543 Saudi Arabia King Saud University Science Technology and Innovation Dept. Riadh 11543 Saudi Arabia King Saud University Computer Engineering Department Ccis Riadh 11543 Saudi Arabia

ISBN: (纸本)9781665463973

the outbreak of the COVID-19 pandemic has resulted in a significant impact on global health and economy. Forecasting the spread of COVID-19 cases is essential for policymakers to make informed decisions and allocate resources accordingly. Deep learning has shown promising results in predicting the spread of infectious diseases, including COVID-19. However, selecting the most appropriate model for a given forecasting task can be challenging, as no single model is guaranteed to perform well for all scenarios. In this paper, we propose a distributed ensemble approach that combines the predictions of different deep learning models, including Autoregressive Integrated Moving Average (Auto-ARIMA), Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), to improve the accuracy of COVID-19 case forecasts. Specifically, we train each deep learning model on a subset of the data and aggregate their predictions to obtain an ensemble forecast. To achieve a distributed ensemble, we use an edge computing framework to train the deep learning models on multiple nodes in a parallel and distributed manner. We evaluate our approach on publicly available COVID-19 datasets, and our results show that the proposed ensemble model outperforms the individual models in terms of forecasting accuracy. Furthermore, our distributed ensemble approach significantly reduces the training and prediction time compared to training each model separately. © 2023 IEEE.

关键词： COVID-19

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Functional knowledge exchange within an intelligent distributed system

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20th international conference on Architecture of computing systems

作者： Buchtala, Oliver Sick, Bernhard Univ Passau Inst Comp Architectures Fac Comp Sci & Math Inn Str 33 D-94032 Passau Germany

ISBN: (纸本)9783540712671

Humans learn from other humans - and intelligent nodes of a distributed system operating in a dynamic environment (e.g., robots, smart sensors, or software agents) should do the same! Humans do not only learn by communicating facts but also by exchanging rules. the latter can be seen as a more generic, abstract kind of knowledge. We refer to these two kinds of knowledge as "descriptive" and "functional" knowledge, respectively. In a dynamic environment, where new knowledge arises or old knowledge becomes obsolete, intelligent nodes must adapt on-line to their local environment by means of self-learning mechanisms. If they exchange functional knowledge in addition to descriptive knowledge, they will efficiently be enabled to cope with a particular phenomenon before they observe this phenomenon in their local environment, for instance. In this article, we present an architecture of so-called organic nodes that face a classification problem. We show how a need for new functional knowledge is detected, how new rules are determined, and how the exchange of locally acquired rules within a network of organic nodes leads to a certain kind of self-optimization of the overall system. We show the potential of our methods using an artificial scenario and a real-world scenario from the field of intrusion detection in computer networks.

关键词： Knowledge representation

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parallel boosted regression trees for web search ranking 11

Parallel boosted regression trees for web search ranking

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20th international conference on World Wide Web, WWW 2011

作者： Tyree, Stephen Weinberger, Kilian Q. Agrawal, Kunal Department of Computer Science and Engineering Washington University St. Louis MO 63130 United States

ISBN: (纸本)9781450306324

Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking - a domain notorious for very large data sets. In this paper, we propose a novel method for parallelizing the training of GBRT. Our technique parallelizes the construction of the individual regression trees and operates using the master-worker paradigm as follows. the data are partitioned among the workers. At each iteration, the worker summarizes its data-partition using histograms. the master processor uses these to build one layer of a regression tree, and then sends this layer to the workers, allowing the workers to build histograms for the next layer. Our algorithm carefully orchestrates overlap between communication and computation to achieve good performance. Since this approach is based on data partitioning, and requires a small amount of communication, it generalizes to distributed and shared memory machines, as well as clouds. We present experimental results on both shared memory machines and clusters for two large scale web search ranking data sets. We demonstrate that the loss in accuracy induced due to the histogram approximation in the regression tree creation can be compensated for through slightly deeper trees. As a result, we see no significant loss in accuracy on the Yahoo data sets and a very small reduction in accuracy for the Microsoft LETOR data. In addition, on shared memory machines, we obtain almost perfect linear speed-up with up to about 48 cores on the large data sets. On distributed memory machines, we get a speedup of 25 with 32 processors. Due to data partitioning our approach can scale to even larger data sets, on which one can reasonably expect even higher speedups. Copyright © 2011 by the Association for computing Machinery, Inc. (ACM).

关键词： parallel processing systems

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Euro-Par 2014: parallel Processing Workshops 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Luís Lopes Julius Žilinskas Alexandru Costan Roberto G. Cascella Gabor Kecskemeti Emmanuel Jeannot Mario Cannataro Laura Ricci Siegfried Benkner Salvador Petit Vittorio Scarano José Gracia Sascha Hunold Stephen L. Scott Stefan Lankes Christian Lengauer Jesus Carretero Jens Breitbart Michael Alexander

ISBN: (数字)9783319143255

ISBN: (纸本)9783319143248

the two volumes LNCS 8805 and 8806 constitute the thoroughly refereed post-conference proceedings of 18 workshops held at the 20th international conference on parallel computing, Euro-Par 2014, in Porto, Portugal, in August 2014. the 100 revised full papers presented were carefully reviewed and selected from 173 submissions. the volumes include papers from the following workshops: APCI&E (First Workshop on Applications of parallel Computation in Industry and Engineering - BigDataCloud (third Workshop on Big Data Management in Clouds) - DIHC (Second Workshop on Dependability and Interoperability in Heterogeneous Clouds) - FedICI (Second Workshop on Federative and Interoperable Cloud Infrastructures) - Hetero Par (12th international Workshop on Algorithms, Models and Tools for parallel computing on Heterogeneous Platforms) - HiBB (5th Workshop on High Performance Bioinformatics and Biomedicine) - LSDVE (Second Workshop on Large Scale distributed Virtual Environments on Clouds and P2P) - MuCoCoS (7th international Workshop on Multi-/Many-core computing systems) - OMHI (third Workshop on On-chip Memory Hierarchies and Interconnects) - PADAPS (Second Workshop on parallel and distributed Agent-Based Simulations) - PROPER (7th Workshop on Productivity and Performance) - Resilience (7th Workshop on Resiliency in High Performance computing with Clusters, Clouds, and Grids) - REPPAR (First international Workshop on Reproducibility in parallel computing) - ROME (Second Workshop on Runtime and Operating systems for the Many Core Era) - SPPEXA (Workshop on Software for Exascale computing) - TASUS (First Workshop on Techniques and Applications for Sustainable Ultrascale computing systems) - UCHPC (7th Workshop on Un Conventional High Performance computing) and VHPC (9th Workshop on Virtualization in High-Performance Cloud computing.

关键词： System Performance and Evaluation Software Engineering/Programming and Operating systems Computer Communication Networks Database Management Algorithm Analysis and Problem Complexity Information systems Applications (incl. Internet)

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Euro-Par 2014: parallel Processing Workshops 1

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丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783319143132

ISBN: (纸本)9783319143125

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Construct a simply and quickly platform to solving linear systems

Construct a simply and quickly platform to solving linear sy...

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international conference on parallel and distributed systems (ICPADS)

作者： Chih-Wei Hsieh Yu-Fen Cheng Chau-Yi Chou National Center for High-Performance Computing Taiwan

ISBN: (纸本)9781479976164

the scientific computing is important research for industrial and society. And, the linear system becomes more important in scientific computing. However, the linear system solvers have many combinations. How to rapidly selecting a best method to solving matrices is expensive. In this paper, we present a linear system solvers platform, which offer easily and quickly interface to users.

关键词： Linear systems Sparse matrices Random access memory Scientific computing Multicore processing parallel processing Graphical user interfaces

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Should I Mine or Should I Break: On the Worthiness of Brute-Forcing Cryptocurrency Addresses

Should I Mine or Should I Break: On the Worthiness of Brute-...

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20th IEEE international conference on Pervasive computing and Communications (IEEE PerCom)

作者： Brighente, Alessandro Camaioni, Martina Conti, Mauro Olivastri, Emilio Univ Padua Dept Math Padua Italy Univ Padua HIT Res Ctr Padua Italy

ISBN: (纸本)9781665416474

Cryptocurrencies are digital assets that can be used as a medium of exchange and are stored in a ledger in the form of a cryptography-secured computer database. Most cryptocurrencies are deployed in decentralized networks such as the blockchain, where they can be transferred from an address to another. However, anyone having access to the private key of an address can fully operate and steal the full balance of such address. Although brute-force attacks consume significant resources in terms of time and power, breaking one of the richest cryptocurrency addresses leads to a huge reward in terms of hard money. therefore, an attacker may be incentivized to run this attack. In this paper, we run a statistical study of cryptocurrencies distribution over the richest addresses and assess the worthiness of a brute-force attack towards their public key. We consider an attacker investing a certain amount of hard money (i.e., a currency that is made up of or directly backed by a valuable commodity such as gold) to run the attack and propose a statistical characterization of the average gained reward. To further assess the worthiness of a brute-forcing attack, we compare the average reward with that of other probabilistic reward systems, such as mining and scratch cards. Results show that the average reward of the proposed attack is six orders of magnitude lower than that of mining and 10 orders of magnitude lower than that of scratching cards for a given initial investment.

关键词： Bitcoin blockchain distributed ledger technology crypto-wallet bruteforce attack

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An Auxiliary Decision Model for Distribution Network Dispatching Based on Scientific computing 20

An Auxiliary Decision Model for Distribution Network Dispatc...

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20th international conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2024

作者： Li, Qiang Ouyang, Hong Zheng, Jianning Xiang, Hui Zhao, Feng Zhao, Linlin Wang, Guaiqiang Li, Wenpu State Grid Information & Telecommunication Group CO. LTD. Beijing China Beijing Sgitg Accenture Information Technology Center CO. LTD. Beijing China

ISBN: (纸本)9798350356328

As distributed generation resources are interconnected on a large scale, the management and dispatching of distribution networks have become increasingly complex, and there is an urgent need for the auxiliary decision-making of distribution network dispatching to transition towards intelligence. Currently, operations such as load transfer still rely on manual handling, encountering issues like low digitalization levels and poor plan optimization. Decisions on load transfer strategies fail to utilize human-machine intelligent collaboration for adaptive decision-making in actual operational contexts. therefore, an auxiliary decision model for distribution network dispatching based on scientific computing is proposed. Firstly, an optimized model for load transfer in distribution networks based on the collaborative optimization of primary and secondary distribution was developed. the objective is to minimize the operation costs of the transmission network and the costs of load shedding in the distribution network, thereby refining load supply transfer strategies and improving the computational efficiency and the optimality of these strategies. Secondly, an intent understanding and information recognition model is built upon LLaMA -CRF and knowledge graph methodologies. this model utilizes the LLaMA large model in conjunction with a parallel application architecture of the knowledge graph to facilitate the comprehension of intentions and the extraction of load supply transfer information. Finally, by establishing evaluation indicators and a test dataset for the load transfer operation auxiliary decision-making model, the effectiveness of intent understanding, information extraction, and optimization strategies for load transfer are assessed, verifying the validity of the proposed scientific computing-based auxiliary decision-making model for distribution network dispatching and operation. © 2024 IEEE.

关键词： Knowledge graph

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distributed Embedded systems: Design, Middleware and Resources 2008

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丛书名： IFIP Advances in Information and Communication Technology

2008年

作者： Bernd Kleinjohann Lisa Kleinjohann Marilyn Wolf

ISBN: (数字)9780387096612

ISBN: (纸本)9780387096605

this book constitutes the refereed proceedings of the IFIP TC 10 Working conference on distributed and parallel Embedded systems, held at the 20th World Computer Congress inMilan, Italy on September 7-10, 2008. the IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. the scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of refereed international conferences in computer science and interdisciplinary fields are featured. these results often precede journal publication and represent the most current research. the principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.

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A Framework for the Design of distributed Reconfigurable Embedded systems

A Framework for the Design of Distributed Reconfigurable Emb...

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20th international conference on Architecture of computing systems 2007

作者： Alessandro Cilardo Luigi Coppolino Nicola Mazzocca University of Naples Federico II Italy

Recent trends in embedded systems architectures are increasingly based on FPGA technologies extending traditional ASIC cores and providing reconfigurable hardware support for performance demanding applications such as multimedia and network or security processing. In this paper, we propose a new framework for the design and management of hardware reconfigurability in distributed embedded environments. the essential aim of the framework is to abstract away the details of the underlying FPGA technology and expose a register transfer level view of the hardwareüaccelerated blocks, allowing the software layer to extract, manipulate, and even export the hardware/software execution state at runütime. the paper also presents some caseüstudy scenarios emphasizing the benefits enabled by the proposed framework for the design of distributed embedded systems.

关键词： Hardware Field programmable gate arrays Java Mobile communication Computer architecture Embedded systems

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