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arXiv 2021年

作者： Tynda, Aleksandr Noeiaghdam, Samad Sidorov, Denis Higher and Applied Mathematics Department Penza State University Penza440026 Russia Industrial Mathematics Laboratory Baikal School of BRICS Irkutsk National Research Technical University Irkutsk664074 Russia Department of Applied Mathematics and Programming South Ural State University Lenin prospect 76 Chelyabinsk454080 Russia Energy Systems Institute Siberian Branch of Russian Academy of Science Irkutsk664033 Russia Institute of Mathematics and Information Technologies Irkutsk State University Irkutsk664025 Russia

The polynomial spline collocation method is proposed for solution of Volterra integral equations of the first kind with special piecewise continuous kernels. The Gauss-type quadrature formula is used to approximate integrals during the discretization of the proposed projection method. The estimate of accuracy of approximate solution is obtained. Stochastic arithmetics is also used based on the Contrôle et Estimation Stochastique des Arrondis de Calculs (CESTAC) method and the Control of Accuracy and Debugging for Numerical Applications (CADNA) library. Applying this approach it is possible to find optimal parameters of the projective method. The numerical examples are included to illustrate the efficiency of proposed novel collocation *** Codes 45H05, 65R20 © 2021, CC BY.

关键词： Integral equations

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Forecasting Nonlinear Nonstationary Processes in Machine Learning Task

Forecasting Nonlinear Nonstationary Processes in Machine Lea...

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IEEE International Conference on Data Stream Mining & Processing (DSMP)

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

ISBN: (数字)9781728132143

ISBN: (纸本)9781728132150

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.

关键词： Forecasting Time series analysis Machine learning Load modeling Currencies Predictive models Classification algorithms

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Real-Time Gait Reconstruction For Virtual Reality Using a Single Sensor

Real-Time Gait Reconstruction For Virtual Reality Using a Si...

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IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Tobias Feigl Lisa Gruner Christopher Mutschler Daniel Roth Fraunhofer Institute of Integrated Circuits (IIS) Nürnberg Programming Systems Group Friedrich-Alexander University (FAU) Erlangen-Nürnberg Ludwig-MaximiliansUniversity (LMU) Technical University Munich (TUM) Munich Chair for Computer Aided Medical Procedures and Augmented Reality Technical University Munich (TUM)

ISBN: (数字)9781728176758

ISBN: (纸本)9781728176765

Embodying users through avatars based on motion tracking and reconstruction is an ongoing challenge for VR application developers. High quality VR systems use full-body tracking or inverse kinematics to reconstruct the motion of the lower extremities and control the avatar animation. Mobile systems are limited to the motion sensing of head-mounted displays (HMDs) and typically cannot offer *** propose an approach to reconstruct gait motions from a single head-mounted accelerometer. We train our models to map head motions to corresponding ground truth gait phases. To reconstruct leg motion, the models predict gait phases to trigger equivalent synthetic animations. We designed four models: a threshold-based, a correlation-based, a Support Vector Machine (SVM) -based and a bidirectional long-term short-term memory (BLSTM) -based model. Our experiments show that, while the BLSTM approach is the most accurate, only the correlation approach runs on a mobile VR system in real time with sufficient accuracy. Our user study with 21 test subjects examined the effects of our approach on simulator sickness and showed significantly less negative effects on disorientation.

关键词： Support vector machines Solid modeling Tracking Avatars Animation Real-time systems Delays

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Darknet traffic big-data analysis and network management to real-time automating the malicious intent detection process by a weight agnostic neural networks framework

arXiv

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arXiv 2021年

作者： Demertzis, Konstantinos Tsiknas, Konstantinos Takezis, Dimitrios Skianis, Charalabos Iliadis, Lazaros Laboratory of Complex Systems Department of Physics Faculty of Sciences International Hellenic University Kavala Campus St. Loukas65404 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Vas. Sofias 12 Xanthi67100 Greece Hellenic National Defence General Staff Stratopedo Papagou Mesogeion 227-231 Athens15561 Greece University of Aegean Karlovassi Samos83200 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General courses Democritus University of Thrace Kimmeria Xanthi Greece

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets. Copyright © 2021, The Authors. All rights reserved.

关键词： Network management

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ViPR: Visual-odometry-aided pose regression for 6DoF camera localization

arXiv

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arXiv 2019年

作者： Ott, Felix Feigl, Tobias Löffler, Christoffer Mutschler, Christopher Nürnberg Germany Programming Systems Group FAU Erlangen-Nürnberg Germany Machine Learning and Data Analytics Lab FAU Erlangen-Nürnberg Germany

Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks. Although Convolutional Neural Networks (CNNs) improve VO in various aspects, VO still suffers from moving obstacles, discontinuous observation of features, and poor textures or visual information. While recent approaches estimate a 6DoF pose either directly from (a series of) images or by merging depth maps with the optical flow (OF), research that combines absolute pose regression with OF is limited. We propose ViPR, a novel architecture for long-term 6DoF VO that leverages synergies between absolute pose estimates (from PoseNet-like architectures) and relative pose estimates (from FlowNet-based architectures) by combining both through recurrent layers. Experiments with known publicly available datasets and with our own Industry dataset show that our novel design outperforms existing techniques in long-term navigation tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Computer vision

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A flexible framework for web-based virtual reality presentation of cultural heritage

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AIP Conference Proceedings 2021年第1期2333卷

作者： Dimo Chotrov Angel Bachvarov 1Technical University Sofia Faculty of Computer Systems and Technologies Department Programming and Computer Technologies Bulgaria 2Technical University Sofia Faculty of Mechanical Engineering Department Automation of Discrete Production Engineering Bulgaria

The Virtual Reality (VR) experiences are great for an engaging presentation creating wide public awareness of cultural heritage, especially if the experience is built on a web-based technology. One of the still posing challenges is that once an application has been developed, for example for a virtual museum or a virtual tour, it usually remains fixed to an embedded in the application model. Adding new functionalities or interaction paradigms needs additional development and new deployment. In this paper, we propose a framework, which achieves the decoupling of an experience from the used models and interaction paradigms through scene and input templates and configuration files. This allows an easy way for generation of a variety of experiences even by people with no or limited programming skills.

关键词：

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Piquasso: A Photonic Quantum Computer Simulation Software Platform

arXiv

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arXiv 2024年

作者： Kolarovszki, Zoltán Rybotycki, Tomasz Rakyta, Péter Kaposi, Ágoston Poór, Boldizsár Jóczik, Szabolcs Nagy, Dániel T.R. Varga, Henrik El-Safty, Kareem H. Morse, Gregory Oszmaniec, Michal Kozsik, Tamás Zimborás, Zoltán Quantum Computing and Quantum Information Research Group HUN-REN Wigner Research Centre for Physics Konkoly-Thege Miklós út 29-33 BudapestH-1525 Hungary Department of Programming Languages and Compilers Eötvös Loránd University Pázmány Péter sétány 1/a BudapestH-1117 Hungary Center for Theoretical Physics Polish Academy of Sciences Al. Lotników 32/46 Warszawa02-668 Poland Department of Physics of Complex Systems Eötvös Loránd University Pázmány Péter sétány 1/a BudapestH-1117 Hungary Quantinuum 17 Beaumont Street OxfordOX1 2NA United Kingdom Robert Bosch Kft. Gyömrői út 104. BudapestH-1103 Hungary Department of Computer Engineering Technical University of Munich Arcisstraße 21 München80333 Germany Algorithmiq Ltd. Kanavakatu 3C Helsinki00160 Finland

We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can be programmed via a high-level Python programming interface enabling users to perform efficient quantum computing with discrete and continuous variables. Via optional high-performance C++ backends, Piquasso provides state-of-the-art performance in the simulation of photonic quantum computers. The Piquasso framework is supported by an intuitive web-based graphical user interface where the users can design quantum circuits, run computations, and visualize the results. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

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A Bidirectional LSTM for Estimating Dynamic Human Velocities from a Single IMU

A Bidirectional LSTM for Estimating Dynamic Human Velocities...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Tobias Feigl Sebastian Kram Philipp Woller Ramiz H. Siddiqui Michael Philippsen Christopher Mutschler Programming Systems Group Friedrich-Alexander University Erlangen-Nürnberg (FAU) Germany Precise Positioning and Analytics Department Fraunhofer Institute for Integrated Circuits IIS Numberg Germany

The main challenge in estimating human velocity from noisy Inertial Measurement Units (IMUs) are the errors that accumulate by integrating noisy accelerometer signals over a long time. Known approaches that work on step length estimation are optimized for a specific application, sensor position, and movement type, require an exhaustive (manual) parameter tuning, and can thus not be applied to other movement types or to a broader range of applications. Moreover, varying dynamics (as they are present for instance in sports applications) cause abrupt and unpredictable changes in step frequency or step length and hence result in erroneous velocity estimates. We use machine learning (ML) and deep learning (DL) to estimate a human's velocity. Our approach is robust to varying motion states and orientation changes in dynamic situations. On data from a single un-calibrated IMU, our novel recurrent model not only outperforms the state-of-the-art on instantaneous velocity (≤0.10 m/s) and on traveled distance (≤29 m/km). It can also generalize to different and varying rates of motion and provides accurate and precise velocity estimates.

关键词： Microsoft Windows Estimation Acceleration Legged locomotion Feature extraction Pipelines Foot

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Research Dynamics of Change of Electromagnetic Parameters of Controlled Special Electric Drives

Research Dynamics of Change of Electromagnetic Parameters of...

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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： V.Yu Karandey O.B. Popova B.K Popov V.L. Afanasyev Department of power supply of the industrial enterprises Kuban State Technological University Krasnodar Russian Federation Department of information systems and programming Kuban State Technological University Krasnodar Russian Federation

In article the research of dynamics of change of electromagnetic parameters of the controlled special electric drives is conducted. Special electric drives are the controlled cascade electric drives of cylindrical and axial designs. The research of dynamics of change of parameters was executed to a basis of a method of electromagnetic transformation of energy and the theory of electromagnetic chains. As a result for new mathematical models of an electromagnetic system of the research electric drives parameters of the electromagnetic field of the closed round of one coil of an electric winding with electric current in a homogeneous environment are determined. The solved task is spatial as distribution of electromagnetic induction in a round of the set form of the electromagnetic coil is defined. The received conclusions of determination of electromagnetic parameters of cylindrical and axial electric motors of special electric drives allow to solve correctly problems of modeling, design and improvement of efficiency of the research electric drives and other electromechanical converters of energy of various designs. Results of a research are applicable for creation of the computer-aided engineering system of the research electric drives and the solution of problems of modeling and design. The conducted research allows to create electric drives optimum mass-dimensional and power indicators.

关键词： Magnetic separation Industrial engineering Electromagnetic fields Control systems Mathematical model Drives

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Accented visualization by augmented reality for smart manufacturing aplications 1

Accented visualization by augmented reality for smart manufa...

引用

1st IEEE International Conference on Industrial Cyber-Physical systems, ICPS 2018

作者： Ivaschenko, Anton Khorina, Anastasia Sitnikov, Pavel Information Systems and Technologies Department Samara National Research University Samara Russia Department of Applied Programming and Technological Innovations ITMO University Saint-Petersburg Russia

ISBN: (纸本)9781538665312

Effective application of Augmented Reality user interfaces is one of the challenging trends of industrial cyber-physical systems development and implementation. Despite reach functionality of modern AR devices (like goggles, head mounted displays or tablets) the problem of their comfortable and productive use is not completely solved yet. To cover this gap, it is proposed in this paper to implement a new paradigm of 'accented visualization' that allows adapting additional data presented by AR device according to the user's current interest, attention and focus. To provide such context driven functionality there was developed intelligent software based on eye tracking and capturing the user's focus in ontology as a knowledge base. Probation and testing of the proposed approach present 89 % of the solution efficiency. © 2018 IEEE.

关键词： Visualization

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