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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Zholkov Jolkov, Sergei Shashev, A.M. National University of Oil and Gas 'Gubkin University' Faculty of Automation and Computer Engineering Moscow Russia Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia

ISBN: (纸本)9798350337907

With an unconventional approach, we regard the problem of building a precise adaptive model of oil price dynamics in the context of investment projects. I. Newton formulated the principle of analysis. We list the Principles of applying the stochastic theory of asset management to building the optimal investment projects in oil and gas field development. We also analyze all the data of daily oil exchange from 1988 to 2019 (spot prices, Platts (Platt's) McGraw Hill Financial). We use methods and quantitative evaluations of adaptive BMS models with stochastic switches. We outline precise (normalized quadratic deviation within 9%) adaptive BMS models, plot extrapolation (quasi-forecast) on a stability period;make a stability period quasi-forecast and list essential quantitative evaluations and graphs. We discuss the possibility of quick profiting using BMS models. We also discuss the approaches to solving the problem of building optimal midterm oil and gas field development projects and operations, as well as the results we acquire. Analysis of incomes and expenses of an optimal investment project would allow for a substantiated decision on whether the development should be started or forgone. © 2023 IEEE.

关键词： Random processes

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Real-time deep learning for multi-label retinal disease diagnosis with embedded system

Computational and Structural Biotechnology Reports

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Computational and Structural Biotechnology Reports 2025年 2卷

作者： Feudjio Ghislain Saha Tchinda Beaudelaire Romain Atangana Tchiotsop Daniel Research Unit of Automation and Applied Computer (UR-AIA) Electrical Engineering Department of IUT-FV University of Dschang P.O. Box: 134 Bandjoun Cameroon Research Unit of Condensed Matter of Electronics and Signal Processing (UR‑MACETS) Department of Physics Faculty of Sciences University of Dschang P.O. Box 67 Dschang Cameroon Department of Computer Science Higher Teacher Training College University of Bertoua-Cameroon P.O.Box 652 Bertoua Cameroon

Background Ophthalmological consultations are essential for the early detection of retinal pathologies. The development of advanced diagnostic devices that combine portability, ease of access, and energy efficiency offers significant benefits, especially in rural or peri-urban areas, which often struggle with limited medical resources and time constraints. Method In this study, we develop a classification platform for various retinal diseases using a Raspberry Pi 4 board. The system relies on a lightweight deep learning model based on convolutional neural networks (CNNs). To enhance the model's efficiency, we integrate biorthogonal wavelet transforms, which facilitate the effective extraction of relevant features from the input images. This approach reduces computational complexity while maintaining the quality of the extracted information. The model, optimized for real-time deployment, was trained on a dataset containing 4303 retinal images, representing four classes of pathologies. Results The proposed embedded model achieves an accuracy of 0.9806 across the four classes of pathologies collected from the two public databases ODIR (Ocular Disease Intelligence Recognition) and RFMiD (Retinal Fundus Multi-Disease Image Dataset). Conclusions Compared to several state-of-the-art methods published to date, the outstanding performance of the proposed embedded system demonstrates its potential as a valuable tool for clinicians to diagnose various ocular diseases in underprivileged healthcare settings.

关键词： Embedded board Real-time classification Lightweight CNN model Wavelet transforms

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Simulation and implementation of a lowcost platform to improve the quality of biological images 49

Simulation and implementation of a lowcost platform to impro...

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49th Summer computer Simulation Conference, SCSC 2017, Part of the 2017 Summer Simulation Multi-Conference, SummerSim 2017

作者： Fabregat, Hermenegildo Del Barrio, Alberto A. Botella, Guillermo Computer Science Faculty Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain

ISBN: (纸本)9781510838284

The development of fluorescence microscopy techniques has help advance in the understanding of molecular mechanisms present at biological systems, as the case of cell migration (Castillo-Lluva et al. 2010, Castillo- Lluva et al. 2013). These techniques allows studying the location, distribution as well as the movement of molecules that have been fluorescently tagged at a high resolution, even dealing with live cells (Rieckher 2017). In this paper a filtering and pattern recognition flow is simulated and implemented on a low-cost hardware platform in order to automate the detection of circular and ellipsoidal cells within the microscopic images. Results show that images keep a high quality after filtering and that 78.4% of the objects are properly recognized. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Neural networks

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Cascade PID control of some processes with distributed parameters through the (Mpdx) method with approximating solutions

Cascade PID control of some processes with distributed param...

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2nd IFAC Workshop on Convergence of Information Technologies and Control Methods with Power Systems, ICPS 2013

作者： Coloşi, T. Abrudean, M. Ungureşan, M.L. Mureşan, V. Department of Automation Technical University of Cluj-Napoca Faculty of Automation and Computer Science 26-28 Gh. Baritiu Street 400027 Cluj-Napoca Romania Department of Physics and Chemistry Technical University of Cluj-Napoca Faculty of Materials Science and Engineering 103-105 Muncii Street 400641 Cluj-Napoca Romania

ISBN: (纸本)9783902823328

Continuing the paper (2013) the analogical modeling and the numerical simulation of a cascade PID control diagram from Fig.1 is presented, containing two distributed parameters processes, each one modeled through an equation with partial derivatives of second order with two independent variables. Through the numerical integration, the method of the Matrix of Partial Derivatives of the State Vector (Mpdx) is used too, associated with approximating solutions. The unitary and systemized character of this method is highlighted, considered known from the previous papers. (2009,2011,2013). Like in the case of paper [1], a program of numerical simulation for the entire PID cascade control scheme was elaborated, resulting a more complete phenomenological interpretation of the obtained results and performances. © IFAC.

关键词： Ordinary differential equations

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Very short term pitch angle optimization in wind turbines: A machine learning approach

Very short term pitch angle optimization in wind turbines: A...

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2013 4th International Conference on Power Engineering, Energy and Electrical Drives, POWERENG 2013

作者： Yesilbudak, Mehmet Kabalci, Ersan Sagiroglu, Seref Colak, Ilhami Department of Electronics and Automation Vocational College of Haci Bektas Veli Nevsehir University Nevsehir Turkey Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nevsehir University Nevsehir Turkey Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey Department of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkey

ISBN: (纸本)9781467363921

This paper proposes a pitch angle forecasting model based on the k-nearest neighbor classification. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters were represented as a 6-dimensional attribute tuple in the forecasting model. Euclidean, Manhattan and Minkowski distance metrics for measuring the proximity between training and test tuples, mean absolute, mean absolute percentage, and normalized root mean square error metrics for measuring the forecasting accuracy were embedded into the forecasting model. The k-nearest neighbor classifier with Manhattan distance metric for k=1 achieved MAE, MAPE and NRMSE as 0.001°, 0.245% and 0.324%, respectively as the best forecasting accuracy. However, as the worst forecasting accuracy, MAE, MAPE and NRMSE were achieved as 0.015°, 3.236% and 2.613%, respectively for Minkowski distance metric and k=10. © 2013 IEEE.

关键词： Wind turbines

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Reversing BLE Remote Control Protocols of Dual Channel LED Lamps with CCT and Illumination Control

Reversing BLE Remote Control Protocols of Dual Channel LED L...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Kandilarov, Rostislav Yordanov, Yordan University of Ruse 'Angel Kanchev' Faculty of Transport Department of Machine Science Machine Elements Engineering Graphics and Physics Ruse Bulgaria University of Ruse 'Angel Kanchev' Computer Systems and Technologies Faculty of Electrical Engeneering Electronics and Automation Ruse Bulgaria

ISBN: (纸本)9798350312911

In this paper various BLE protocols for communication between remote or Android applications and intelligent dual channel (cool and warm white) LED lamps were reverse engineered. Three protocols were fully decoded and several partially. Replay attack is tested and confirmed working. Demo C++ library was developed and a proof-of-concept firmware for esp32 based development board was used to verify the decoding and the attacks applicability. © 2023 IEEE.

关键词： Light emitting diodes

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SIMULATION AND IMPLEMENTATION OF A LOW-COST PLATFORM TO IMPROVE THE QUALITY OF BIOLOGICAL IMAGES 17

SIMULATION AND IMPLEMENTATION OF A LOW-COST PLATFORM TO IMPR...

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computer Simulation Conference

作者： Hermenegildo Fabregat Alberto A. Del Barrio Guillermo Botella Computer Science Faculty Universidad Complutense de Madrid Department of Computer Architecture and Automation Universidad Complutense de Madrid

ISBN: (纸本)9781510838284

The development of fluorescence microscopy techniques has help advance in the understanding of molecular mechanisms present at biological systems, as the case of cell migration (Castillo-Lluva et al. 2010, Castillo-Lluva et al. 2013). These techniques allows studying the location, distribution as well as the movement of molecules that have been fluorescently tagged at a high resolution, even dealing with live cells (Rieckher 2017). In this paper a filtering and pattern recognition flow is simulated and implemented on a low-cost hardware platform in order to automate the detection of circular and ellipsoidal cells within the microscopic images. Results show that images keep a high quality after filtering and that 78.4% of the objects are properly recognized.

关键词： Microscopic images Filter Pattern recognition Neural network FiL

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Aggregation kinetics of carbonyl iron particles under magnetic fields: Influence of particle-wall interactions and confinement 8

Aggregation kinetics of carbonyl iron particles under magnet...

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8th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2017 and 6th International Conference on Smart Materials and Nanotechnology in Engineering, SMN 2017

作者： Shahrivar, Keshvad Carreón-González, Elizabeth Agís, Rodrigo De Vicente, Juan Department of Applied Physics University of Granada Faculty of Science Granada18071 Spain Department of Computer Architecture and Technology ETSI Informática y de Telecomunicación CITIC-UGR CIC University of Granada Granada Spain

ISBN: (纸本)9788494690938

Magnetorheological (MR) fluids are smart colloids that exhibit a dramatic rheological change upon the application of a magnetic field as a result of the field-promoted interparticle aggregation. In this presentation we show our most recent work on the aggregation kinetics of carbonyl iron particles of use in the formulation of MR fluids of commercial interest. First, we demonstrate the importance of experimental conditions in the aggregation kinetics. In particular, we demonstrate the effect of the carrier fluid viscosity and surfactant addition. Second, we demonstrate the importance of magnetic field strength. In particular, we demonstrate that mean cluster size versus time curves can be re-scaled following a purely deterministic aggregation process. Finally, we show that the confinement of the field-induced structures results in a long-time plateau in the mean cluster size presumably as a result of the predominant lateral repulsive interactions between the chain like structures. © 2017 International Center for Numerical Methods in Engineering. All rights reserved.

关键词： Magnetorheological fluids

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Hybrid design tools-image quality assessment of a digitally augmented blackboard integrated system

arXiv

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arXiv 2019年

作者： Banias, Ovidiu Milincu, Camil Octavian Automation and Applied Informatics Department Faculty of Automation and Computer Science Politehnica University of Timisoara Timisoara300223 Romania Architecture Department Faculty of Architecture and Urban Planning Politehnica University of Timisoara Timisoara300223 Romania

In the last two decades, Interactive White Boards (IWBs) have been widely available as a pedagogic tool. The usability of these boards for teaching disciplines where complex drawings are needed, we consider debatable in multiple regards. In a previous study, we proposed an alternative to the IWBs as a blackboard augmented with a minimum of necessary digital elements. The current study continues our previous research on hybrid design tools, analyzing the limitations of the developed hybrid system regarding the perceived quality of the images being repeatedly captured, annotated, and reprojected onto the board. We validated the hybrid system by evaluating the quality of the projected and reprojected images over a blackboard, using both objective measurements and subjective human perception in extensive and realistic case studies. Based on the results achieved in the current research, we conclude that the proposed hybrid system provides good quality support for teaching disciplines that require complex drawings and board interaction. Copyright © 2019, The Authors. All rights reserved.

关键词： Hybrid systems

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Probing invisible neutrino decay with the first six detection units of KM3NeT/ORCA

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Journal of High Energy physics 2025年第4期2025卷 1-24页

作者： Aiello, S. Albert, A. Alhebsi, A. R. Alshamsi, M. Alves Garre, S. Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Benfenati Gualandi, F. Benhassi, M. Bennani, M. Benoit, D. M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Bouasla, A. B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R. M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J. A. B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Wasseige, G. Decoene, V. Deguire, P. Del Rosso, I. Di Mauro, L. S. Di Palma, I. Díaz, A. F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. El Mentawi, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M. D. Filippini, F. Franciotti, D. Fusco, L. A. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B. K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S. R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J. J. Idrissi, A. Idrissi Ibnsalih, W. Illuminati, G. Joly, D. de Jong, M. de Jong, P. Jung, B. J. Kalaczyński, P. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y. Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Lessing, N. Levi, G. Lindsey Clark, M. Longhitano, F. Magnan INFN Sezione di Catania (INFN-CT) Catania Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg France Université de Haute Alsace Mulhouse Cedex France Khalifa University of Science and Technology Department of Physics Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France IFIC — Instituto de Física Corpuscular (CSIC — Universitat de València) Paterna Spain Università di Napoli “Federico II” Dip. Scienze Fisiche “E. Pancini” Complesso Universitario di Monte S. Angelo Napoli Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli Italy INFN Sezione di Roma Roma Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Vilanova i la Geltrú Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université Nantes France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras Gandia Spain Université Paris Cité CNRS Astroparticule et Cosmologie Paris France INFN Sezione di Genova Genova Italy Università di Genova Genova Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS/IN2P3 Caen France Comenius University in Bratislava Department of Nuclear Physics and Biophysics Bratislava Slovak Republic Czech Technical University in Prague Institute of Experimental and Applied Physics Prague Czech Republic Università di Bologna Dipartimento di Fisica e Astronomia Bologna Italy INFN Sezione di Bologna Bologna Italy Università degli Studi della Campania “Luigi Vanvitelli” Dipartimento di Matematica e Fisica Caserta Italy LPC Campus des Cézeaux 24 Aubière Cedex France E. A. Milne Centre for Astrophysics University of Hull Hull United Kingdom Nikhef National Institute for Subatomic Physics Amsterdam Netherlands INFN Laboratori Nazionali del Sud (LNS) Catania Italy North-West University Centre for Space Research Potchefstroom South Africa Université Badji Mokhtar Département de

In the era of precision measurements of neutrino oscillation parameters, it is necessary for experiments to disentangle discrepancies that may indicate physics beyond the Standard Model in the neutrino sector. KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study the oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on the initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photosensors. A high-purity neutrino sample was extracted during 2020 and 2021, corresponding to an exposure of 433 kton-years. This sample is analysed following a binned log-likelihood approach to search for invisible neutrino decay, in a three-flavour neutrino oscillation scenario, where the third neutrino mass state ν3 decays into an invisible state, e.g. a sterile neutrino. The resulting best fit of the invisible neutrino decay parameter is $$ {\alpha}_3={0.92}_{-0.57}^{+1.08}\times {10}^{-4} $$ eV2, corresponding to a scenario with θ23 in the second octant and normal neutrino mass ordering. The results are consistent with the Standard Model, within a 2.1 σ interval.

关键词： Beyond Standard Model Neutrino Detectors and Telescopes (experiments) Oscillation

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