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Epistemic Multiagent Reasoning with Collaborative Robots 37

Epistemic Multiagent Reasoning with Collaborative Robots

引用

37th Italian Conference on Computational Logic, CILC 2022

作者： Soldà, Davide Fabiano, Francesco Dovier, Agostino Constraint and Logic Programming Lab University of Udine Udine33100 Italy Embedding System Unit of Fondazione Bruno Kessler Trento38123 Italy Department of Mathematical Physical and Computer Sciences University of Parma Parma43124 Italy Department of Mathematics Computer Science and Physics University of Udine Udine33100 Italy

Over the last few years, the fields of Artificial Intelligence, Robotics and IoT have gained a lot of attention. This increasing interest has brought, among other things, to the development of autonomous multi-agent systems where robotic entities may interact with each other. As for all the other autonomous settings, also these systems require arbitration. Our work tries to address this problem by presenting a framework that embeds both a classical and a multi-agent epistemic (epistemic, for brevity) planner in a robotic control architecture. The idea is to combine the (i) classical and the (ii) epistemic solvers to model efficiently the interaction with: the (i) physical world and the (ii) information flows, respectively. In particular, the presented architecture starts by planning on the "epistemic level" refining then single-agent world-altering actions thanks to the classical planner. To further optimize the solving process, we also introduce the concept of macros in epistemic planning. Macros, in fact, have been successfully employed in classical planning as they allow for opportune aggregations of actions that may lead to a reduction of plans' length. Finally, the overall framework is exemplified and validated with two Franka Emika manipulators. This allowed us to empirically justify how the combination of the two planning approaches (classical and epistemic), and the introduction of macros, reduce the computational time required by the orchestrating phase. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Robot programming

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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

引用

2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Chernikov, Alexander Smirnova, Elena Zhavoronkov, Oleg Peter the Great St. Petersburg Polytechnic University Higher School of Automation and Robotics St. Petersburg Russia Saint Petersburg State University Department of System Programming St. Petersburg Russia Computer Vision Systems Llc St. Petersburg Russia

ISBN: (纸本)9781665475952

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation - 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526. © 2023 IEEE.

关键词： Computer vision

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Evaluating the Software Requirements Specifications Using Ontology-Based Intelligent Agent

Evaluating the Software Requirements Specifications Using On...

引用

International Scientific and Technical Conference on Computer Science and Information Technologies

作者： Tetiana Hovorushchenko Olga Pavlova Computer Engineering and System Programming Department Khmelnitsky National University (KhNU) Khmelnitsky Ukraine Informatics department Khmelnitsky Gymnasium No.2 Khmelnitsky Ukraine

The purpose of this study is the development of the method of activity of ontology-based intelligent agent (OBIA) for evaluating the software requirements specifications (SRS). OBIA works on the basis of the developed method, and evaluates the sufficiency of information in the SRS for assessing the non-functional software features - provides the conclusion and the numerical evaluation of the level of sufficiency of information in the SRS for assessment of non-functional features.

关键词： Software Software requirements specification (SRS) Ontology Intelligent agent (IA) Ontology-based intelligent agent (OBIA)

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Formalization of data derivative structures

Formalization of data derivative structures

引用

2020 International Conference on Information Science and Communications Technologies, ICISCT 2020

作者： Vosilovich Kabulov, Rustam Bakhtiyorovich Ruzibaev, Ortik Temur Ataxanovich, Kuchkorov Saidqulovich Muminov, Sanjar Tashkent University of Information Technologies Named after Muhammad Al-Khwarizimi Department of Software Engineering Amir Temur str. 108 Tashkent100200 Uzbekistan Department of System and Application Programming of Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Amir Temur str. 108 Tashkent100200 Uzbekistan

ISBN: (纸本)9781728199696

The paper considers the topical issue of formal description of data structures. Data structures are widely used in modern object-oriented programming to solve various practical problems. The paper introduces functions for performing operations with such data structures as stack, queue, and priority queue. The conditions that these functions must satisfy are introduced as axioms. To describe the axioms, an approach based on an abstract data type, algebraic and programmatic approaches were used. © 2020 IEEE.

关键词： Object oriented programming

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Automatic Type Reconstruction in Disassembled C Programs

Automatic Type Reconstruction in Disassembled C Programs

引用

Working Conference on Reverse Engineering

作者： K. Dolgova A. Chernov Institute for System Programming Russian Academy of Science Moscow Russia Computational Mathematics and Cybernetics Department Moscow State University Moscow Russia

ISBN: (纸本)9780769534299;0769534295

This paper presents an algorithm for automatic type reconstruction from target assembly code compiled by a C compiler. The primitive language types are recovered by an iterative algorithm, which operates over the lattice of primitive types' properties. Layout of composite types is reconstructed by building set of accessible offsets for each composite type. The algorithm is the essential part of a tool for program decompilation being developed by the authors.

关键词： Registers Assembly Equations Finite element methods Construction industry Algorithm design and analysis High level languages

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Reconstruction of Class Hierarchies for Decompilation of C++ Programs

Reconstruction of Class Hierarchies for Decompilation of C++...

引用

(CSMR) European Conference on Software Maintenance and Reengineering

作者： A. Fokin K. Troshina A. Chernov Computational Mathematics and Cybernetics Department Moscow State University Moscow Russia Institute for System Programming Russian Academy of Science Moscow Russia

This paper presents a method for automatic reconstruction of polymorphic class hierarchies from the assembly code obtained by compiling a C++ program. If the program is compiled with run-time type information (RTTI), class hierarchy is reconstructed via analysis of RTTI structures. In case RTTI structures are missing in the assembly, a technique based on the analysis of virtual function tables, constructors and destructors is used. A tool for automatic reconstruction of polymorphic class hierarchies that implements the described technique is presented. This tool is implemented as a plug in for IDA Pro Interactive Disassembler. Experimental study of the tool is provided.

关键词： Assembly Computer languages Open source software Electronic mail Optimization History

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Image noise reduction by denoising autoencoder

Image noise reduction by denoising autoencoder

引用

IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Lev Yasenko Yaroslav Klyatchenko Oksana Tarasenko-Klyatchenko Department of System Programming and Specialized Computer Systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

Neural networks are used in many tasks today. One of them is the images processing. Autoencoder is very popular neural networks for such problems. Denoising autoencoder is an important autoencoder because some tasks we need a preprocessed image to get less noisy result. This research describes ways to analyze noisy images produced by a physically-based render engine and how to reduce that noise. The results showed that the algorithms are logarithmic.

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Deep Learning in IoT: An LSTM Approach for NDVI Forecasting

Deep Learning in IoT: An LSTM Approach for NDVI Forecasting

引用

Electronic Engineering (ICEEM), International Conference on

作者： Khaled Sherif Mohamed Azmy Khder Alakkari Mostafa Abotaleb El-Sayed M. El-Kenawy Department of Communications Delta Higher Institute Mansoura Egypt Department of Civil Engineering Delta Higher Institute Mansoura Egypt Department of Statistics and Programming Faculty of Economics University of Tishreen Tartous Syria Department of System Programming South Ural State University Chelyabinsk Russia

This study presents a novel application of a Long Short-Term Memory (LSTM) deep learning model for time-series analysis of the Normalized Difference Vegetation Index (NDVI) from January 1, 1984, to April 21, 2023. As remote sensing technologies generate substantial environmental data, advanced analytics like LSTM provide essential tools for precise interpretation and forecasting. Through grid search optimization, hyperparameters were fine-tuned for optimal LSTM performance. The NDVI mean value over the study period is 0.332, indicative of a moderate vegetation presence. The data series’ sta-tionarity, confirmed through the Dickey-Fuller test, contributes to accurate prediction outcomes. The LSTM model demonstrates superior predictive performance, evidenced by the Root Mean Squared Error (RMSE) values of 0.000764 and 0.000900 for the training and testing datasets respectively. The high R-squared and correlation values further substantiate its efficacy. This study paves the way for leveraging LSTM models in large-scale NDVI data analysis, contributing to environmental monitoring, climate change tracking, and vegetation health assessments. Future work can extend this model to other remote sensing indices and explore various deep learning architectures for enhanced predictive accuracy. The main objective is to identify the optimal LSTM hyperparameters for NDVI prediction using grid search optimization. Our results are expected to provide valuable insights into how LSTM models can be effectively tuned for improved NDVI prediction, potentially benefiting environmental monitoring and decision-making processes.

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Design of a multifunctional universal mask for patients

Design of a multifunctional universal mask for patients

引用

Middle East Conference on Biomedical Engineering (MECBME)

作者： Roy Abi Zeid Daou Rami Daccache Gerges Andary Ali Hayek Josef Börcsök Faculty of Public Health Lebanese German University Jounieh Lebanon Department of Computer Architecture and System Programming University of Kassel Kassel German

This paper aims to present a universal mask that enables all adult patients to use it. This mask has a universal size and head gear. It has many options; from among we list the embedded SpO2 and EEG electrode connections. This mask enables also the input of oxygen, nebulizer, air CPAP and medication. A mechanical switch is used to select between air CPAP and nebulizer.

关键词： Electroencephalography Switches Electrodes Standards Head Gears

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Forecasting nonlinear nonstationary processes in machine learning task 3

Forecasting nonlinear nonstationary processes in machine lea...

引用

3rd IEEE International Conference on Data Stream Mining and Processing, DSMP 2020

作者： Bidyuk, Peter Gozhyj, Aleksandr Kalinina, Irina Vysotska, Victoria Vasilev, Mikhail Malets, Romanna Department of Mathematical Methods of System Analysis National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Petro Mohyla Black Sea National University Department of Intelligent Information Systems Nikolaev Ukraine National University Lvivska Politechnika Department of Information Systems and Networks Lviv Ukraine Ivan Franko Lviv National University Programming Department Lviv Ukraine

ISBN: (纸本)9781728132143

The article discusses the features of the solving the forecasting problems using machine learning techniques. The issues of accounting and correctly processing non-linear non-stationary processes in the problems of modeling and forecasting time series in various areas are considered. The analysis of stages and methods for solving machine learning problems. As an example, consider the problem of predicting currency pairs based on historical data. A comparative analysis of the normalization methods in data clustering is given. For the six currency pairs a short-term forecast is proposed. © 2020 IEEE.

关键词： Machine learning

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