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Develop an unsupervised attention-based LSTM network algorithm for forecasting infectious disease

AIP Conference Proceedings 2023年第1期2977卷

作者： Mostafa Abotaleb Tatiana Makarovskikh Zainalabideen Albadran Ali J. Ramadhan System Programming Department South Ural State University Chelyabinsk Russia Department of Computer Techniques Engineering College of Technical Engineering University of Alkafeel Najaf Iraq

time series Due to better algorithms, more accessible data, and higher computing power over the past ten years, forecasting has become more popular. It is used in a variety of industries, including as financial time series, weather forecasting, and medical diagnostics. In this study, we provide a model of the mechanism governing attention, which enables attended input to be provided to the model in place of actual input. In order for the model to produce more precise predictions, it seeks to demonstrate a fresh perspective on the data. The experiments were conducted with the (encoder-decoder) LSTM model as well to demonstrate the usefulness and superiority of the suggested strategy. The obtained results demonstrate that, when compared to the (encoder-decoder) LSTM base model, the proposed approach could reduce the mean square error (RMSE=9819.05), relative root mean square error (RRMSE=99.09), and coefficient of determination (R Square=0.96). The obtained results support the suggested approach’s efficacy, superiority, and importance in predicting SARS-CoV-2 infection cases.

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Uvl: Feature Modelling with the Universal Variability Language

SSRN

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SSRN 2024年

作者： Benavides, David Sundermann, Chico Feichtinger, Kevin Galindo, José A. Rabiser, Rick Thüm, Thomas Department of Computer Languages and Systems Universidad de Sevilla Av. Reina Mercedes Seville41012 Spain Institute of Software Engineering and Programming Languages University of Ulm Albert-Einstein-Allee 11 Ulm89069 Germany CRC 1608 KASTEL – Dependability of Software-intensive Systems Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe76131 Germany Christian Doppler Laboratory VaSiCS LIT CPS Lab Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria

Feature modelling is a cornerstone of software product line engineering, providing a means to represent software variability through features and their relationships. Since its inception in 1990, feature modelling has evolved through various extensions, and after three decades of development, there is a growing consensus on the need for a standardised feature modelling language. Despite multiple endeavours to standardise variability modelling and the creation of various textual languages, researchers and practitioners continue to use their own approaches, impeding effective model sharing. In 2018, a collaborative initiative was launched by a group of researchers to develop a novel textual language for representing feature models. This paper introduces the outcome of this effort: the Universal Variability Language (\UVL), which is designed to be human-readable and serves as a pivot language for diverse software engineering tools. The development of \UVL drew upon community feedback and leveraged established literature in the field of variability modelling. The language is structured into three levels -Boolean, Arithmetic, and Type- and allows for language extensions to introduce additional constructs enhancing its expressiveness. \UVL is integrated into various existing software tools, such as FeatureIDE and FLAMA, and is maintained by a consortium of institutions. © 2024, The Authors. All rights reserved.

关键词： Modeling languages

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A method for targeting unmanned aerial vehicles for a distributed intelligent control system for a group of dissimilar unmanned aerial vehicles

A method for targeting unmanned aerial vehicles for a distri...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Danylo Parkhomenko Oleksandr Rysovanyi Valery Burtsev Viktor Voronin Volodymyr Startsev Volodymyr Panchenko Doctoral student of the scientific and organizational department of Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine Computer Engineering and Programming Department National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Department of the faculty of anti-aircraft missile forces of Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

the application of a distributed intelligent control system for a group of unmanned aerial vehicles is substantiated, a method for coordinating their interaction to maximize the target indicator is proposed and substa...

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Estimating Solar Power Plant Data Using Time Series Analysis Methods

Estimating Solar Power Plant Data Using Time Series Analysis...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Ebru Idman Emrah Idman Osman Yildirim Computer Programming Istanbul Arel University Istanbul Turkey Electronic Engineering Istanbul Arel University Istanbul Turkey

ISBN: (数字)9781728193526

ISBN: (纸本)9781728193533

When meteorological data such as temperature, precipitation, weather events and economic data such as stock prices and exchange rates reach large levels, it may be necessary to analyze them with time series analysis methods. The aim of this research is to analyze the data of solar power plants with time series and make predictions for the future. To achieve this goal, solar panel data with historical depth will be collected, the collected data will be trained and predicted by various time series analysis methods and comparison will be made according to the prediction success among the related models. Methodology: With this study, using Python 3.6 and R 3.6.1, the time series estimation models were modeled with AR, ARMA, SARIMA, DES and TES, the difference between the real value and the predicted value of the data was found by the RMSE (Square Root of the Mean Square Error) method and it was seen which model has the best ability to estimate the dataset. In addition, with the trend and seasonality of the data, detailed information about the dataset was obtained with descriptive analysis and graphics. As a result, it was seen that using SARIMA or TES models in the datasets that show seasonal change in the light of the studies and estimations performed gives better results.

关键词： Predictive models Market research Time series analysis Data models Meteorology Estimation Prediction algorithms

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Research of Energy Detection Method in Spectrum Sensing in Cognitive Radio Networks

Research of Energy Detection Method in Spectrum Sensing in C...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Ernazar Reypnazarov Halimjon Khujamatov Doston Khasanov Zamira Allamuratova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Computer Enjineering Faculty Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Data Communication Networks and Systems Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Information-Computer Technologies and Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper presents the threshold value determination model, its implementation algorithm, and the characteristics of the threshold value depending on the probability of false signal detection, developed for the purpose of researching the method of energy determination in spectrum sensing in cognitive radio networks. Also, the main methods of single-band spectrum sensing in cognitive radio networks were initially studied in the article, and the main spectrum detection algorithms were comparatively analyzed.

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A principle feature analysis

arXiv

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arXiv 2021年

作者： Breitenbach, Tim Rasbach, Lauritz Liang, Chunguang Jahnke, Patrick Biozentrum Universität Würzburg Am Hubland Würzburg97074 Germany Department of Computer Science Distributed Systems Programming Technische Universität Darmstadt Hochschulstraße 10 Darmstadt64289 Germany

A key task of data science is to identify relevant features linked to certain output variables that are supposed to be modeled or predicted. To obtain a small but meaningful model, it is important to find stochastically independent variables capturing all the information necessary to model or predict the output variables sufficiently. Therefore, we introduce in this work a framework to detect linear and non-linear dependencies between different features. As we will show, features that are actually functions of other features do not represent further information. Consequently, a model reduction neglecting such features conserves the relevant information, reduces noise and thus improves the quality of the model. Furthermore, a smaller model makes it easier to adopt a model of a given system. In addition, the approach structures dependencies within all the considered features. This provides advantages for classical modeling starting from regression ranging to differential equations and for machine learning. To show the generality and applicability of the presented framework 2154 features of a data center are measured and a model for classification for faulty and non-faulty states of the data center is set up. This number of features is automatically reduced by the framework to 161 features. The prediction accuracy for the reduced model even improves compared to the model trained on the total number of features. A second example is the analysis of a gene expression data set where from 9513 genes 9 genes are extracted from whose expression levels two cell clusters of macrophages can be *** Codes 00A71, 93A30, 65C60, 93B40, 93E25 © 2021, CC BY-NC-SA.

关键词： Differential equations

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The e-learning test system module for statistical analysis of tests' results 28

The e-learning test system module for statistical analysis o...

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28th International Scientific Conference Electronics, ET 2019 - Proceedings

作者： Stoyanova, Lyudmila Yordanova Minkovska, Daniela Veleva Percuku, Arber Shefqet Department of Programming and Computer Technologies Faculty of Computer Systems and Technologies Technical University of Sofia 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9781728125749

In this paper are presented the description of the developed and implemented system for tests control and the analysis of the results received from the testing of students. The database and the developed forms are revealed in the paper. Statistical and probability analysis of the received results are being made and described. Conclusions have been made for the advantages of the newly developed system. © 2019 IEEE.

关键词： E-learning

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Slippery Lubricant-Infused Silica Nanoparticulate Film Processing for Anti-Biofouling Applications 73

Slippery Lubricant-Infused Silica Nanoparticulate Film Proce...

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73rd International Astronautical Congress, IAC 2022

作者： Sip, Yuen Yee Li Jacobs, Annabel Morales, Alejandra Sun, Mengdi Roberson, Luke B. Hummerick, Mary E. Roy, Herve Kik, Pieter Zhai, Lei Department of Materials Science & Engineering University of Central Florida FL United States Herbert Wertheim College of Engineering University of Florida FL United States Engineering Computer Programming and Technology Division Valencia College FL United States College of Optics and Photonics University of Central Florida FL United States Kennedy Space Center National Aeronautics and Space Administration FL United States Kennedy Space Center Amentum Services FL United States Burnett School of Biomedical Sciences University of Central Florida FL United States Department of Chemistry University of Central Florida FL United States

Microbial biofilm build-up in water distribution systems can pose a risk to human health and pipe material integrity. The impact is more devastating in space stations and to astronauts due to the isolation from necessary replacement parts and medical resources. As a result, there is a need for coatings to be implemented onto the inner region of the pipe to minimize the adherence and growth of biofilms. Lubricant-infused surfaces has been one such interesting material for anti-biofouling applications in which their slippery property promotes repellence to many liquids and thus prevents bacterial adherence. Textured and porous films are suitable substrate candidates to infuse and contain the lubricant. However, there is little investigation in utilizing a nanoporous thin film as the substrate material for lubricant infusion. A nanoporous film has high porosity within the structure which can promote greater lubricant infusion and retention. The implementation as a thin film structure aids to reduce material consumption and cost. In our study, we utilized a well-studied nanoporous thin film fabricated via layer-by-layer assembly of polycations and colloid silica and calcination for greater stability. The film was further functionalized to promote fluorinated groups upon the surface and pores of the film, which then could interact with a fluorinated lubricant. The pristine nanoporous film was characterized to determine its morphology, thickness, wettability, and porosity. The lubricant-infused film was then tested for its lubricant layer stability upon various washing conditions and its performance against bacterial biofilm adherence as a result of its slippery and thus anti-biofouling property. Copyright © 2022 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Silica

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Stability Analysis of Imprecise Prey-Predator Model 4th

Stability Analysis of Imprecise Prey-Predator Model

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4th IFIP TC 12 International Conference on Intelligence Science, ICIS 2020

作者： De, Anupam Khatua, Debnarayan Maity, Kalipada Panigrahi, Goutam Maiti, Manoranjan Department of Applied Sciences Haldia Institute of Technology Haldia West Bengal India Department of Basic Science and Humanities Global Institute of Science and Technology Haldia West Bengal India Department of Mathematics Mugberia Gangadhar Mahavidyalaya Contai West Bengal India Department of Mathematics National Institute of Technology Durgapur Durgapur West Bengal India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore West Bengal India

ISBN: (纸本)9783030748258

Since the last few decades, the prey-predator system delivers attractive mathematical models to analyse the dynamics of prey-predator interaction. Due to the lack of precise information about the natural parameters, a significant number of research works have been carried out to take care of the impreciseness of the natural parameters in the prey-predator models. Due to direct impact of the imprecise parameters on the variables, the variables also become imprecise. In this paper, we developed an imprecise prey-predator model considering both prey and predator population as imprecise variables. Also, we have assumed the parameters of the prey-predator system as imprecise. The imprecise prey-predator model is converted to an equivalent crisp model using "e" and "g" operator method. The condition for local stability for the deterministic system is obtained mathematically by analysing the eigenvalues of the characteristic equation. Furthermore, numerical simulations are presented in tabular and graphical form to validate the theoretical results. © 2021, IFIP International Federation for Information Processing.

关键词： Eigenvalues and eigenfunctions

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A Novel Solution to Enhance the Oxidative and Physical Properties of Cookies Using Maltodextrin-Based Nano-Sized Oils as a Fat Substitute

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ACS Omega 2025年第22期10卷 23111-23120页

作者： Raciye Meral Mehmet Mustafa Eki̇N Zafer Ceylan Aslıhan Alav Erol Kına Department of Food Engineering Faculty of Engineering Van Yüzüncü Yıl University Van 65080 Turkiye Özalp Vocational School Food Technology Program Van Yuzuncu Yıl University Van 65080 Turkiye Faculty of Science Department of Molecular Biology and Genetics Kutlubey Campus Bartin University Kutlubeyyazıcılar Village Bartin 74110 Turkiye Van Yüzüncü Yıl University Institute of Science Van 65080 Turkiye Computer Programming Program Özalp Vocational School Van Yüzüncü Yıl University Van 65100 Turkiye；Innovan Entrepreneurship Centre Van 65080 Turkiye

This study investigated the effects of maltodextrin-based nanoemulsions as fat substitutes in cookies, focusing on the oxidative stability and physical properties. Full-fat cookies (control, C) and 50% fat-reduced cookies with nanoemulsions (FC) were produced. The addition of nanoemulsions increased the cookie diameter from 46.3 mm (control) to 56.1 mm and reduced the thickness, resulting in a desirable texture. Initial hardness values (30.3 and 45.8 N) were lower in nanoemulsion samples and remained reduced over a 90 day storage period. Black cumin oil-loaded nanoemulsions provided the lowest peroxide values (1.7, 2.7, and 2.4 mequiv O2/kg), maintaining oxidative stability during storage. Final free fatty acid (FFA) values ranged from 0.23% to 0.44% after storage. Thiobarbituric acid (TBA) values indicated slower lipid oxidation, with values ranging from 1.47 to 2.51 mg MDA/kg on day 0 and increasing to a maximum of 4.13 mg MDA/kg by day 90 in fat-reduced cookies. Among the tested formulations, nanoemulsions enriched with black cumin oil demonstrated the highest effectiveness, yielding enhanced oxidative stability and improved quality characteristics. This study presents an innovative strategy by utilizing maltodextrin-based nanoemulsions containing naturally antioxidant-rich oils as fat replacers, offering a clean-label alternative to improve the oxidative resilience and physical quality of cookies.

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