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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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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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Platform for big biomedical data streams management and analytics

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International Journal of Circuits, Systems and Signal Processing 2020年 14卷 580-588页

作者： Gancheva, Veska Programming and Computer Technologies Department Technical University of Sofia 8 Kliment Ohridski boul Sofia1000 Bulgaria

Major challenge in the analysis of clinical data and knowledge discovery is to suggest an integrated, advanced and efficient tools, methods and technologies for access and processing of progressively increasing amounts of data in multiple formats. The paper presents a platform for multidimensional large-scale biomedical data management and analytics, which covers all phases of data discovery, data integration, data preprocessing, data storage, data analytics and visualization. The goal is to suggest an intelligent solution as integrated, scalable workflow development environment consisting of a suite of software tools to automate the computational process in conducting scientific experiments. © 2020, North Atlantic University Union. All rights reserved.

关键词： Data Analytics

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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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Neural networks for determining affinity functions

Neural networks for determining affinity functions

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

作者： Valery Dmitrievich Dmitrienko Alexander Yurievich Zakovorotniy Sergey Yurievich Leonov Computer Engineering and Programming Department National Technical University "Kharkiv Polytechnic Institute" Kharkov Ukraine

ISBN: (数字)9781728193526

ISBN: (纸本)9781728193533

The Hamming neural network is an effective tool for solving the problems of recognition and classification of discrete objects whose components are encoded with the binary bipolar alphabet, and the difference between the number of identical bipolar components of the compared objects (vectors images) and the Hamming distance between them (Hamming distance is the number of mismatched bits in the binary vectors being compared) is used as the objects proximity measures. However, the Hamming neural network cannot be used to solve these problems in case the components of the compared objects (vectors) are encoded with the binary alphabet. It also cannot be used to evaluate the affinity (proximity) of objects (binary vectors) with Jaccard, Sokal and Michener, Kulzinsky functions, etc. In this regard, a generalized Hamming neural network architecture has been developed. It consists of two main blocks, which can vary being relatively independent on each other. The first block, consisting of one layer of neurons, calculates the proximity measures of the input image and the reference ones stored in the neuron relations weights of this block. Unlike the Hamming neural network, this block can calculate various proximity measures and signals about the magnitude of these proximity measures from the output of the first block neurons which are followed to the inputs of the second block elements. In the Hamming neural network, the Maxnet neural network is used as the second block, which gives out one maximum signal from the outputs of the first block neurons. If the inputs of the Maxnet network receive not only one but several identical maximum signals, then the second block, and, consequently, the Hamming network, cannot recognize the input vector, which is at the same minimum Hamming distance from two or more reference images stored in the first block. The proposed generalized architecture of the Hamming neural network allows using neural networks instead of the Maxnet network, whi

关键词： Biological neural networks Neurons Hamming distance computer architecture Image recognition programming Weight measurement

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Analysis of Hardware and Software Tools for Implementation of Cognitive Radio Networks

Analysis of Hardware and Software Tools for Implementation o...

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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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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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Application of computer-Aided Technologies for Analysis if Statistical Data of Collectors Wearing Measurements and for Diagnosis of Traction Motors

Application of Computer-Aided Technologies for Analysis if S...

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2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

作者： Zolkin, A.L. Magomedov, I.A. Kucher, O.V. Povolzhskiy State University of Telecommunications and Informatics Computer and Information Sciences Department Samara Russia Chechen State University Programming Information and Communication Technologies Department Grozny Russia Kuban State Agricultural University Named after I.T. Trubilin Economic Cybernetic Department Krasnodar Russia

ISBN: (纸本)9781728169514

This article is dedicated to the study of an integrated approach to technological process of control of measurement of wearing parameters of traction electric motor collectors. Also the article presents the results of studies on the organization of an automated calculation and control system for the wearing of traction electric motor collectors at the stage of their repair using modern software. Special software product that allows to perform quick and truthful calculation of the wearing parameters of traction electric motor collectors depending on their run distance is proposed for implementation. After the entering of initial values, the statistical dependence of the collector diameter and its wearing on the run distance of the locomotive as well as theoretical distribution are calculated. The comparability of the theoretical and empirical distributions and sample regression coefficients that reflect the degree of connection between the theoretical and empirical distributions are estimated. © 2020 IEEE.

关键词： Traction motors

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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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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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