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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 Dean of the 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 Department of Information-Computer Technologies and Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper analyzes of the hardware and software tools for implementing a cognitive radio network. In particular, software-configurable radio modules, which are considered the main element of the cognitive network, were studied according to their main characteristics, among which the widely used ones were comparatively analyzed. As a result of the analysis, the HackRF One device was selected as the most preferred option for cognitive network research, and its working principles, structure, and characteristics were revealed in detail. It also provides information about the GNU Radio software environment and its capabilities, which are used to operate the HackRF One device.

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Artificial Intelligence in Medicine for Chronic Disease Classification Using Machine Learning

Artificial Intelligence in Medicine for Chronic Disease Clas...

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International Conference on Application of Information and Communication Technologies (AICT)

作者： Mekhriddin Rakhimov Ravshanjon Akhmadjonov Shahzod Javliev Department of Artificial Intelligence Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan Department of System and Application Programming Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan Department of Computer System Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665451635

Artificial intelligence (AI) systems in medicine are one of the most important modern trends in global healthcare. Artificial intelligence technologies are fundamentally changing the global healthcare system, making it possible to radically rebuild the system of medical diagnostics while reducing healthcare costs. AI is actively used in research to develop methods for diagnosing coronary heart disease (CHD). There are different types of CHD. Before treating a disease, it is necessary to determine which class of diseases it belongs to. Based on the feature space of the disease, it is possible to classify the type of CHD. Machine learning algorithms can solve this problem. The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve classification problems. The dataset is the more important part of the supervised machine learning algorithm for training. Gathering data is the most important step in solving any supervised machine learning problem. But choosing more important part from the collected data is one of the tasks to be solved. The main purpose of this study is to select more useful parametric attributes from the dataset to obtain a high F1-score of CHD classification.

关键词： Heart Training Machine learning algorithms Machine learning Market research Classification algorithms Information and communication technology

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A G-covering subgroup system of a finite group for some classes of σ-soluble groups

arXiv

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arXiv 2021年

作者： Liu, A-Ming Guo, W. Safonova, Inna N. Skiba, Alexander N. School of Science Hainan University Haikou570228 China Department of Applied Mathematics and Computer Science Belarusian State University Minsk220030 Belarus Department of Mathematics and Technologies of Programming Francisk Skorina Gomel State University Gomel246019 Belarus

Let F be a class of group and G a finite group. Then a set Σ of subgroups of G is called a G-covering subgroup system for the class F if G ∈ F whenever Σ ⊆ F. We prove that: If a set of subgroups Σ of G contains at least one supplement to each maximal subgroup of every Sylow subgroup of G, then Σ is a G-covering subgroup system for the classes of all σ-soluble and all σ-nilpotent groups, and for the class of all σ-soluble P σT -groups. This result gives positive answers to questions 19.87 and 19.88 from the Kourovka *** Codes 20D10 © 2021, CC BY.

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Intuitionistic Fuzzy Dombi Hybrid Decision-Making Method and Their Applications to Enterprise Financial Performance Evaluation

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Mathematical Problems in Engineering 2021年 2021卷

作者： Jana, Chiranjibe Muhiuddin, G. Pal, Madhumangal Al-Kadi, D. Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Mathematics University of Tabuk Tabuk71491 Saudi Arabia Department of Mathematics and Statistic College of Science Taif University P.O. Box 11099 Taif21944 Saudi Arabia

In the era of the knowledge-based economy, the active branch of information technology plays a crucial role. The enterprise administration covers efficient changes, and it has been entered in the age of reasonable management argument. The standard enterprise financial review evaluation centers on the importance of bondholders. The investor takes operational data as an issue and pays surveillance to the study of material attraction and the result. Otherwise, it is not intelligent to adjust in a modern marketplace period. Therefore, enterprise financial directing the interests of shareholders and business policies that are taking into account stakeholders' needs is continually investigated in the future lively competition. In that view, accumulating data is an essential research tool to draw the researchers' recent attention during the knowledge investigation. In this research, multiple attribute decision-making (MADM) approach has been proposed for the enterprise financial performance evaluation. To this view, financial performance evaluation has been done with intuitionistic fuzzy arguments. We apply new Dombi hybrid operators such as the intuitionistic fuzzy Dombi hybrid average (IFDHWA) operator and intuitionistic fuzzy Dombi hybrid geometric (IFDHWG) operator. These operators have a good advantage of adaptability in the working parameter. Finally, a realistic instance for enterprise financial performance is reported following comment on the benefit or utility of the recommended output. © 2021 Chiranjibe Jana et al.

关键词： Competition

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Modeling of rainfall time series using NAR and ARIMA model over western Himalaya, India

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Arabian Journal of Geosciences 2022年第23期15卷 1-26页

作者： Rawat, Deepa Mishra, Pradeep Ray, Soumik Warnakulasooriya, Himasha Harshani Fernando Sati, Sarswati Prakash Mishra, Gaurav Alkattan, Hussein Abotaleb, Mostafa College of Forestry VCSG Uttarakhand University of Horticulture and Forestry Tehri Garhwal India College of Agriculture Rewa India Centurion University of Technology and Management Paralakhemundi India Department of Statistics & Computer Science Faculty of Science University of Kelaniya Kelaniya Sri Lanka Centre of Excellence on Sustainable Land Management Indian Council of Forestry Research and Education (MoEF & CC Govt. of India) Dehradun India Department of System Programming South Ural State University Chelyabinsk Russia

The high Himalayas in northern India are an essential source of climate generation and maintenance over the entire northern belt of the Indian subcontinent. It also affects extreme weather phenomena such as western disturbances in the region during winter. The work presented here describes the trends in 117-year precipitation changes and their impact on the western Himalayas and suggests some possible explanations in the context of changing rainfall patterns. Under the investigation, the forecasting efficiency and the prediction pattern of artificial neural network (ANN) and seasonal autoregressive integrated moving average (SARIMA) models for rainfall series in the western Himalayan states of India have been assessed. The results revealed significant changes in the monthly, seasonal, and annual rainfall series data for the three states of the Western Himalayan regions from the years 1900 to 2017. The study also concludes that the nonlinear autoregressive neural network (NARNN) models can be used to forecast the western Himalayan region data series well. According to the result interpretation, the highest rainfall may be estimated in August, 1632.63 mm (2023), whereas the lowest rainfall can be obtained in October (0.43 mm) during 2023. The model predicted a gradual decrease in annual rainfall trends in Uttarakhand and Himachal Pradesh from 2018 to 2023 despite heavy rainfall prediction in the monsoon season, whereas Jammu and Kashmir increase in annual rainfall has been predicted from 2018 to 2023. Possible explanations for the change in precipitation over the western Himalayas have also been proposed and explained.

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Image noise reduction by denoising autoencoder

Image noise reduction by denoising autoencoder

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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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Hybrid multi-criteria decision-making method with a bipolar fuzzy approach and its applications to economic condition analysis

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Engineering Applications of Artificial Intelligence 2024年 132卷

作者： Jana, Chiranjibe Simic, Vladimir Pal, Madhumangal Sarkar, Biswajit Pamucar, Dragan Tamil Nadu Chennai602105 India Faculty of Transport and Traffic Engineering University of Belgrade VojvodeStepe 305 Belgrade11010 Serbia Yuan Ze University College of Engineering Department of Industrial Engineering and Management Taoyuan City320315 Taiwan Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Industrial Engineering Yonsei University 50 Yonsei-ro Sinchon-dong Seodaemun-gu Seoul03722 Korea Republic of Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu 600077 India Department of Industrial Engineering and Management National Taipei University of Technology Taipei City 106344 Taiwan Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Computer Science and Mathematics Lebanese American University Byblos 1102 2801 Lebanon

The bipolar fuzzy set and interval-valued bipolar fuzzy set efficiently analyse real-world problems where for each input of an object, there has counter information. This study's main objective is to lay a foundation for considering a new approach to the bipolar fuzzy hybrid operators tool applied in a realistic frame that contains uncertainties. In this view, some mixed aggregation operators, namely, the hybrid bipolar fuzzy weighted averaging geometric (H-BFWAG), hybrid bipolar fuzzy order weighted averaging geometric (H-BFOWAG), hybrid interval-valued bipolar fuzzy weighted averaging geometric (H-IVBFWAG), and hybrid interval-valued bipolar fuzzy order weighted averaging geometric (H-IVBFOWAG) operators are generated in bipolar fuzzy environment. A decision making approach is developed to build the multi-criteria decision making model. A numerical example is considered to study the different effects on various Indian economic sectors in the COVID-19 environment. Managerial implications are highlighted in between many industrial sectors on which the Indian economy depends and the country's gross domestic product depends on their inter-relationship. This study investigates COVID-19's impact on society and the economy in the Indian context. A comparative investigation is introduced with some pre-existing operators and the TOPSIS (technique for order of preference by similarity to ideal solution) approach to justify the proposed method. © 2024 Elsevier Ltd

关键词： COVID-19

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Carrot and Stick approaches when managing Technical Debt

Carrot and Stick approaches when managing Technical Debt

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IEEE/ACM International Conference on Technical Debt (TechDebt)

作者： Terese Besker Antonio Martini Jan Bosch Computer Science and Engineering Software Engineering Chalmers University of Technology Göteborg Sweden University of Oslo Programming and Software Engineering Oslo Norway

When developing software, it is vitally important to keep the level of technical debt down since it is well established from several studies that technical debt can, e.g., lower the development productivity, decrease the developers’ morale, and compromise the overall quality of the software. However, even if researchers and practitioners working in today’s software development industry are quite familiar with the concept of technical debt and its related negative consequences, there has been no empirical research focusing specifically on how software managers actively communicate and manage the need to keep the level of technical debt as low as *** paper aims to explore how software companies encourage and reward practitioners for actively keeping the level of technical debt down and also whether the companies use any forcing or penalizing initiatives when managing technical *** paper reports the results of both an online web-survey provided quantitative data from 258 participants and follow-up interviews with 32 industrial software practitioners. The findings show that having a TD management strategy can significantly impact the amount of TD in the software. When surveying how commonly used different TD management strategies are, we found that only the encouraging strategy is, to some extent, adopted in today’s’ software industry. This study also provides a model describing the four assessed strategies by presenting its strategies and tactics, together with recommendations on how they could be operationalized in today’s software companies.

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A Top-Down Three-Way Merge Algorithm for HTML/XML Documents 1

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Science and Information Conference, SAI 2020

作者： Bakaoukas, Anastasios G. Bakaoukas, Nikolaos G. Faculty of Arts Science and Technology University of Northampton Waterside Campus University Drive NorthamptonNN1 5PH United Kingdom School of Engineering and Sciences Computer Science and Programming Department Foundation College Mitropoleos Street and Mnisikleous Campus Athens105 56 Greece

ISBN: (数字)9783030522490

ISBN: (纸本)9783030522483

Collaborative work, with the need to keep HTML/XML code up-to-date, is now becoming vital particularly in the Web Development field. In order to fully support collaborative work and resolve related problems the need has arisen for an optimum solution to the automated editing of a number of parallel copies originating from a single original HTML/XML code document with the additional requirement to subsequently merge the copies into a single updated document. A number of algorithms have been used in the past for the purpose, such as: Diff3, XmlDiff, DeltaXML & 3DM, but HTML/XML code complexity related issues have now called for an algorithm that is more specifically designed for the purpose. In this paper a new algorithmic approach to merging HTML/XML code documents is presented that is based on the "Three-way Merge" approach and the "Node-per-Node" comparison between ordered trees. For the creation of the actual merging function operating at the heart of the algorithm, a particular methodology was followed in which only the two "Current Versions" are required for the generation of the updated document, and no involvement of the "Original Document" is necessary. This is an important improvement over the currently existing algorithms because eliminates the well-known "Idempotent" problem in merging two HTML/XML documents. In addition, the algorithmic approach presented here allows for the identification and treatment of all the conflicts that arise during a HTML/XML code merging in an ordered and clearly specified manner. © 2020, Springer Nature Switzerland AG.

关键词： HTML

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Analysing the impact of COVID-19 outbreak and economic policy uncertainty on stock markets in major affected economies

Analysing the impact of COVID-19 outbreak and economic polic...

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6th Smart Cities Symposium (SCS 2022)

作者： A. Matuka S. S. Asafo G. O. Eweke P. Mishra S. Ray M. Abotaleb T. Makarovskikh A.A. Alhussan A.A. Abdelhamid E.M. El-Kenawy P. Dutta S. Chowdhury University of Macerata Department of Economics and Law Macerata Italy Department of Banking & Finance Niger Delta University Amassoma Nigeria College of Agriculture J.N.K.V.V. Powarkheda India Centurion University of Technology and Management Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog School of Engineering and Technology Amity University Kolkata Kolkata India MCA Department Sri Venkateshwara College of Engineering and Technology Chittoor India

The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets worldwide. This study is thus an attempt to analyse the impact of the COVID-19 pandemic on stock market behaviour in major affected economies. Moreover, the time frame was extended by using current data which investigate the impact of the virus during the boom and the blast phase in the country's most hit by the pandemic crisis such as China, Italy, UK and US. The frequency of the data is daily, and it dates from 3 January 2020 up to 10 February 2021. The considered time framework will give a deep insight into how stock markets behave in the case of an exogenous shock. The Dickey-Fuller Augmented Unit Root Test indicates that all the variables are stationary at first difference, which is one of the main conditions to have robust result, and the ARCH-LM test for the heteroskedasticity of the residuals, which show that all the probability values are significant, rejecting the null hypothesis of no ARCH effect. Based on the results of GARCH (1,1), we conclude that the change in stock markets volatility is positive and significant in China, Italy, UK and USA. This suggests that the impacts of COVID-19 outbreak and economic policy uncertainty on Stock Markets are a significant and Homogeneous across the studied countries, and the shock on FTSE Italia All Share has the longest time to vanish which makes it the riskiest to invest during this period, while the shock on SP500 USA has the shortest time to disappear meaning that it is safest Stock Market in this study. These findings have significant implications for policymakers, institutional and individual investors and Financial Markets analysts.

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