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2022 International Conference on Information Science and Communications Technologies, ICISCT 2022

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

ISBN: (纸本)9781665472296

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. © 2022 IEEE.

关键词： Cognitive radio

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Lookback Period, Epochs and Hidden States Effect on Time Series Prediction Using a LSTM based Neural Network 28

Lookback Period, Epochs and Hidden States Effect on Time Ser...

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28th National Conference with International Participation, TELECOM 2020

作者： Koparanov, Kiril Andreev Georgiev, Krasin Krasimirov Shterev, Vasil Aleksandrov Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9781728187174

Forecasting time series problem occurs in various subject areas. Recently neural network techniques have been used for solving such tasks. However, they have not been sufficiently studied. The article explores the influence of the lookback period, the training epochs, and hidden state dimensionality in forecasting time series using long short-term memory. Numerical experiments with example financial data show that using more lags does not improve the results. Such a study of model parameters is important for their proper selection. © 2020 IEEE.

关键词： Time series

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Sensing metric-based hybrid underlay/overlay transmission framework for CR-IoT networks for smart city applications

Sensing metric-based hybrid underlay/overlay transmission fr...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Indu Bala Maad M. Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Abdelhameed Ibrahim School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results.

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Applications of Fuzzy Logic in Recruitment systems

Applications of Fuzzy Logic in Recruitment Systems

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Kunduz Medetova Djamshid Sultanov Department of system and applied programming Tashkent university of information technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of hardware and software of management systems in telcommunications Tashkent university of information technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper presents methods for solving problems using the method of fuzzy logic. This method serves to study the characteristics of determining the level of compliance of a candidate for an existing vacant position. When measuring compliance with database requirements based on the results of assessing compliance with the requirements of an employee for a position. The use of artificial intelligence in personnel records gives high efficiency and serves for decision making.

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A compact QUBO encoding of computational logic formulae demonstrated on cryptography constructions

arXiv

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arXiv 2024年

作者： Morse, Gregory Kozsik, Tamás Mencer, Oskar Rakyta, Péter Department of Programming Languages and Compilers Eötvös Loránd University Budapest1117 Hungary Groq Inc. 400 Castro St Mountain ViewCA94041 United States Department of Physics of Complex Systems Eötvös Loránd University Budapest1117 Hungary Wigner Research Center for Physics P.O. Box 49 Budapest1525 Hungary

We aim to advance the state-of-the-art in Quadratic Unconstrained Binary Optimization formulation with a focus on cryptography algorithms. As the minimal QUBO encoding of the linear constraints of optimization problems emerges as the solution of integer linear programming (ILP) problems, by solving special boolean logic formulas (like ANF and DNF) for their integer coefficients it is straightforward to handle any normal form, or any substitution for multi-input AND, OR or XOR operations in a QUBO form. To showcase the efficiency of the proposed approach we considered the most widespread cryptography algorithms including AES-128/192/256, MD5, SHA1 and SHA256. For each of these, we achieved QUBO instances reduced by thousands of logical variables compared to previously published results, while keeping the QUBO matrix sparse and the magnitude of the coefficients low. In the particular case of AES-256 cryptography function we obtained more than 8× reduction in variable count compared to previous results. The demonstrated reduction in QUBO sizes notably increases the vulnerability of cryptography algorithms against future quantum annealers, capable of embedding around 30 thousands of logical variables. © 2024, CC BY.

关键词： Integer linear programming

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Benchmarking Photonic Quantum Machine Learning Simulators

Benchmarking Photonic Quantum Machine Learning Simulators

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Henrik Varga Attila Kiss Zoltán Kolarovszki Department of Algorithms and their Applications ELTE Eötvös Loránd University Budapest Hungary Department of Information Systems ELTE Eötvös Loránd University Budapest Hungary Department of Informatics J. Selye University Komárno Slovakia Department of Programming Languages and Compilers ELTE Eötvös Loránd University Budapest Hungary Department of Computational Sciences Wigner Research Centre for Physics Budapest Hungary

In the past few years, quantum computing has gotten more attention, and the need for efficient simulations is getting increasingly important as well. A significant branch of quantum computing is photonic quantum computing. For simulating photonic quantum circuits, Strawberry Fields is the most popular framework. In this paper, we compared it with another framework currently under development called Piquasso regarding gradient calculation time, which is an essential part of continuous-variable quantum neural networks. We present the apparent scalability of Piquasso over Strawberry Fields by storing fewer data, but leading to possible accuracy differences as a trade-off, which could motivate future work.

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Optimizing machine learning algorithms to enhance blood donation for liver patients: a case study

Optimizing machine learning algorithms to enhance blood dona...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Maad M. Mijwil El-Sayed M. El-kenawy Indu Bala Mohammad Aljanabi Mostafa Abotaleb Abdelhameed Ibrahim Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood.

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Uniqueness of the Fredholm-Stiltjes Linear Integral Equations Solutions of the Third Kind

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Advances in Linear Algebra & Matrix Theory 2021年第4期11卷 109-116页

作者： Aizat Toigonbaeva Avyt Asanov Aisalkyn Kambarova Gumushai Obodoeva Ularbek Moldoyarov Aibek Toktorbaev Aichurok Abdukadyr Kyzy Zhypargul Abdullaeva Department of Mathematical Analysis Osh State University Osh Kyrgyzstan Mathematics Department Kyrgyz Turkish Manas University Bishkek Kyrgyzstan Department of Automated Systems and Digital Technologies Osh State University Osh Kyrgyzstan Department of Information Systems and Programming Osh State University Osh Kyrgyzstan Science and Research Department Osh State University Osh Kyrgyzstan

Integral equations theoretical parts and applications have been studied and investigated in previous works. In this work, results on investigations of the uniqueness of the Fredholm-Stiltjes linear integral equations solutions of the third kind were considered. Volterra integral equations of the first and third kind with smooth kernels were studied, and proof of the existence of a multiparameter family of solutions is described. Additionally, linear Fredholm integral equations of the first kind were investigated, for which Lavrent’ev regularizing operators were constructed.

关键词： Solution Integral Equations Uniqueness Fredholm-Stiltjes Linear Integral Equations Third Kind

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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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Modified asymptotic method of studying the mathematical model of nonlinear oscillations under the impact of a moving environment 14th

Modified asymptotic method of studying the mathematical mode...

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14th International Scientific and Technical Conference on Computer Science and Information Technologies, CSIT 2019

作者： Pukach, Petro Il’kiv, Volodymyr Nytrebych, Zinovii Vovk, Myroslava Pukach, Pavlo Department of Computational Mathematics and Programming Lviv Polytechnic National University Lviv Ukraine Department of Mathematics Lviv Polytechnic National University Lviv Ukraine Department of Artificial Intelligence Systems Lviv Polytechnic National University Lviv Ukraine

ISBN: (纸本)9783030336943

Wave theory of movement is used to study the mathematical model of a physical system which describes oscillations of a one-dimensional elastic body under the impact of a moving continuous flow of a homogeneous environment. This model accounts for nonlinear elastic properties of the body at transverse oscillations, as well as environment density and movement velocity. Oscillation amplitude and frequency variation laws in nonresonant modes and under the impact of harmonic perturbation are obtained. Variation laws of the aforesaid parameters are defined by geometrical characteristics of the elastic body, physical and mechanical properties of the material, the velocity of the moving environment, the angular velocity of elastic body rotation, and external factors. © Springer Nature Switzerland AG 2020.

关键词： Elasticity

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