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Foundations of Intelligent Systems 1

丛书名： Lecture Notes in computer science

1000年

作者： Troels Andreasen Henning Christiansen Juan-Carlos Cubero Zbigniew W. Raś

ISBN: (数字)9783319083261

ISBN: (纸本)9783319083254

This book constitutes the refereed proceedings of the 21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014, held in Roskilde, Denmark, in June 2014. The 61 revised full papers were carefully reviewed and selected from 111 submissions. The papers are organized in topical sections on complex networks and data stream mining; data mining methods; intelligent systems applications; knowledge representation in databases and systems; textual data analysis and mining; special session: challenges in text mining and semantic information retrieval; special session: warehousing and OLAPing complex, spatial and spatio-temporal data; ISMIS posters.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Database Management Information Storage and Retrieval Information Systems Applications (incl. Internet) User Interfaces and Human computer Interaction

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AbotalebNet: A Novel Deep Learning Architecture for Time Series Forecasting with Convolutional and LSTM Layers Enhanced by Multi-Head Attention

AbotalebNet: A Novel Deep Learning Architecture for Time Ser...

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Trends in Quantum Computing and Emerging Business Technologies (TQCEBT), International Conference on

作者： Mostafa Abotaleb Tatiana Makarovskikh Maad M. Mijwil Indu Bala Kamal Kant Hiran Ruchi Doshi Dep. of System Programming South Ural State University Chelyabinsk Russia Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Electrical and Electronics Engineering Lovely Professional University Punjab India Dep. of Computer Science Sir Padampat Singhania University Udaipur India Dep. of Computer Science and Engineering Universidad Azteca Chalco Mexico

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet’s architecture is mathematically represented as:\begin{equation*}\hat Y = {\text{Attention}}(\operatorname{LSTM} ({\text{CNN}}(X)))\tag{1}\end{equation*}Here, X represents the input time series data, and Ŷ is the forecasted output. AbotalebNet integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the sequential data processing power of Long Short-Term Memory (LSTM) networks, further enhanced by a Multi-Head Attention *** address overfitting, a key challenge in deep learning, the model incorporates regularization strategies, dropout mechanisms, and batch normalization:\begin{equation*}\mathop {\min }\limits_\Theta ( Loss (X,\hat Y;\Theta ) + \lambda R(\Theta ))\tag{2}\end{equation*}In this equation, Θ denotes the model parameters, R(Θ) represents regularization terms, and λ is the regularization coefficient. These additions aid in preventing the model from overfitting to the training data, ensuring robust performance on unseen *** evaluation on COVID-19 time series data demonstrates AbotalebNet’s enhanced predictive accuracy over traditional models, solidifying its potential for advanced non-linear time series analysis.

关键词： COVID-19 Analytical models Solid modeling Time series analysis Training data Predictive models Data models

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OpenModelica - A free open-source environment for system modeling, simulation, and teaching

OpenModelica - A free open-source environment for system mod...

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IEEE International Conference on computer-Aided Design

作者： Peter Fritzson Peter Aronsson Adrian Pop Hakan Lundvall Kaj Nystrom Levon Saldamli David Broman Anders Sandholm PELAB-Programming Environment Laboratory Department Computer Science Linköping University Linkoping Sweden MathCore Engineering AB Teknikringen 1B SE-583 30 Linköping Sweden EPACT AB Linköping Sweden

Modelica is a modern, strongly typed, declarative, and object-oriented language for modeling and simulation of complex systems. This paper gives a quick overview of some aspects of the OpenModelica environment - an open-source environment for modeling, simulation, and development of Modelica applications. An introduction of the objectives of the environment is given, an overview of the architecture is outlined and a number of examples are illustrated.

关键词： Open source software Education Load modeling Protection Equations Control systems System testing Packaging Connectors

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An efficient algorithm for the configuration problem of dominance graphs 01

An efficient algorithm for the configuration problem of domi...

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Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms

作者： Ernst Althaus Denys Duchier Alexander Koller Kurt Mehlhorn Joachim Niehren Sven Thiel Max-Planck-Institute for Computer Science Saarbrücken Germany programming Systems Lab Fachbereich Informatik Universität des Saarlandes Saarbrücken Germany Department of Computational Linguistics Universität des Saarlandes Saarbrücken Germany

ISBN: (纸本)9780898714906

Dominance constraints are logical tree descriptions originating from automata theory that have multiple applications in computational linguistics. The satisfiability problem of dominance constraints is NP-complete. In most applications, however, only normal dominance constraints are used. The satisfiability problem of normal dominance constraints can be reduced in linear time to the configuration problem of dominance graphs, as shown recently. In this paper, we give a polynomial time algorithm testing configurability of dominance graphs (and thus satisfiability of normal dominance constraints). Previous to our work no polynomial time algorithms were known.

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research Institute - GIRI.

关键词： Malware

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Improving communication in PGAS environments: Static and dynamic coalescing in UPC 13

Improving communication in PGAS environments: Static and dyn...

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27th ACM International Conference on Supercomputing, ICS 2013

作者： Alvanos, Michail Farreras, Montse Tiotto, Ettore Amaral, José Nelson Martorell, Xavier Programming Models Barcelona Supercomputer Center Barcelona Spain Department of Computer Architecture Universitat Politecnica de Catalunya Cr. Jordi Girona 1-3 08034 Barcelona Spain Static Compilation Technology IBM Toronto Laboratory Toronto ON Canada Dep. of Computing Science University of Alberta Edmonton AB Canada Barcelona Supercomputing Center Cr. Jordi Girona 29 08034 Barcelona Spain IBM Canada CAS Research Markham ON Canada

ISBN: (纸本)9781450321303

The goal of Partitioned Global Address Space (PGAS) languages is to improve programmer productivity in large scale parallel machines. However, PGAS programs may have many fine-grained shared accesses that lead to performance degradation. Manual code transformations or compiler optimizations are required to improve the performance of programs with fine-grained accesses. The downside of manual code transformations is the increased program complexity that hinders programmer productivity. On the other hand, most compiler optimizations of fine-grain accesses require knowledge of physical data mapping and the use of parallel loop constructs. This paper presents an optimization for the Unified Parallel C language that combines compile time (static) and runtime (dynamic) coalescing of shared data, without the knowledge of physical data mapping. Larger messages increase the network efficiency and static coalescing decreases the overhead of library calls. The performance evaluation uses two microbenchmarks and three benchmarks to obtain scaling and absolute performance numbers on up to 32768 cores of a Power 775 machine. Our results show that the compiler transformation results in speedups from 1.15X up to 21X compared with the baseline versions and that they achieve up to 63% the performance of the MPI versions. © 2013 ACM.

关键词： Dynamics

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Industrial machine vision: lessons and challenges

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Optics News 1987年第2期13卷 12-17页

作者： Steven W. Holland Robert B. Tilove STEVEN W. HOLLAND is an assistant department head in the Computer Science Dept. of General Motors Research Laboratories (GMR). He is responsible for research projects involving computer vision robotics mobile robotics process planning knowledge systems natural language advanced programming environments parallel processing and statistics. ROBERT B. TILOVE is senior staff research scientist and project leader of the machine perception project at GMR. His research interests include geometric modeling model-based programming and control of intelligent automation systems.

No abstract available.

关键词： Integral imaging Machine vision Measurement and metrology Optical systems Sensors Statistics

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Formal Methods and Software Safety

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IFAC Proceedings Volumes 1992年第30期25卷 93-98页

作者： J.P. Bowen V. Stavridou Oxford University Computing Laboratory Programming Research Group 11 Keble Road Oxford OX1 3QD UK Department of Computer Science Royal Holloway and Bedford New College University of London Egham Hill Egham Surrey TW20 0EX UK

The safety of software is becoming increasingly important as computers pervade control systems on which human life depends. Whilst hardware has become significantly more reliable over the years, the same cannot be said of software. This has become more complex and methods to ensure its correctness have been slow in development. One approach is to mathematically verify software in such systems. This paper investigates the industrial use of these techniques, their advantages and disadvantages, and the introduction of standards and their recommendations concerning formal methods in this area. The cost of safety is also considered.

关键词： Safety reliability system integrity standards education digital systems computer software formal languages industrial control software engineering

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Automatic creation of both the topology and parameters for a robust controller by means of genetic programming

Automatic creation of both the topology and parameters for a...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： J.R. Koza M.A. Keane F.I. Bennett Jessen Yu W. Mydlowec O. Stiffelman Section on Medical Informatics School of Medicine University of Stanford Stanford CA USA Econometrics Inc. Chicago IL USA Genetic Programming Inc. Los Altos CA USA Computer Science Department University of Stanford Stanford CA USA

The paper describes a general automated method for synthesizing the design of both the topology and parameter values for controllers. The automated method automatically makes decisions concerning the total number of processing blocks to be employed in the controller, the type of each block, the topological interconnections between the blocks, the values of all parameters for the blocks, and the existence, if any, of internal feedback between the blocks of the overall controller. Incorporation of time-domain, frequency-domain, and other constraints on the control or state variables (often analytically intractable using conventional methods) can be readily accommodated. The automatic method described in the paper (genetic programming) is applied to a problem of synthesizing the design of a robust controller for a plant with a second-order lag. A textbook PID compensator preceded by a lowpass pre-filter delivers credible performance on this problem. However, the automatically created controller employs a second derivative processing block (in addition to proportional, integrative, and derivative blocks and a pre-filter). It is better than twice as effective as the textbook controller as measured by the integral of the time-weighted absolute error, has only two-thirds of the rise time in response to the reference (command) input, and is 10 times better in terms of suppressing the effects of disturbance at the plant input.

关键词： Topology Robustness Automatic control Feedback Time domain analysis Frequency domain analysis Genetic programming Robust control PD control Proportional control

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Sports programming as a Tool for Regional Development of the Digital Industry and Higher Education

Sports Programming as a Tool for Regional Development of the...

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Technology Enhanced Learning in Higher Education (TELE), International Conference on

作者： Alexander Galkin Artem Miroshnikov Daniil Sapronov Elena Skarzhinskaya Faculty of Automation and Computer Science Lipetsk State Technical University Lipetsk Russia Department of Applied Mathematics Lipetsk State Technical University Lipetsk Russia Lipetsk branch of the Russian Federation of Sports Programming Lipetsk Russia Department of Cybersport Moscow Financial and Industrial University “Synergy” Moscow Russia

ISBN: (数字)9798350353532

ISBN: (纸本)9798350353549

Abstract-The article presents the history of the development of sports programming as a sport in Russia. The main stages of the formation of the legislative basis for this sport are given. The rationale and description of the process of training athletes in higher education institutions are given - possible traj ectories in the disciplines of “algorithmic programming” and “product programming”, the influence of the development of sports programming on improving the quality of IT education. As an example, the organization of training students in the discipline of “algorithmic programming” at the Lipetsk State Technical University is given. The activities of the Lipetsk regional branch of the All- Russian Sports Federation to popularize this sport including among students are also described.

关键词： Training Industries Organizations History programming profession Sports

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