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2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Mnushka, Oksana Savchenko, Volodymyr Leonov, Serhii Shaposhnikova, Olena Kharkiv National Automobile and Highway University Computer Technology and Mechatronics Department Kharkiv Ukraine Globallogic Ukraine Kharkiv Ukraine National Technical University 'Kharkiv Polytechnical Institute' Computer Engineering and Programming Department Kharkiv Ukraine

ISBN: (纸本)9781665412629

Remote monitoring of objects or technological processes is used in many industries and service-oriented companies to obtain up-to-date information about the state of things or technical processes. The article is devoted to developing, analyzing, and implementing information technology (IT) for remote monitoring. The high-level design of IT and system for its implementation is based on the IDEF0 Functional Modeling methodology that describes the system hierarchy and establishes horizontal links between various activities. The achieved results confirm the possibility of implementing the proposed technology. The results will be of interest to technical specialists involved in the development of relevant applications but also to business analysts and managers for a better understanding of modern applied information technologies. © 2021 IEEE.

关键词： Remote control

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Uvlhub: A Feature Model Data Repository Using Uvl and Open Science Principles

SSRN

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SSRN 2023年

作者： Romero-Organvidez, David Galindo, José A. Sundermann, Chico Horcas, Jose-Miguel Benavides, David Department of Computer Languages and Systems University of Seville Spain Institute of Software Engineering and Programming Languages Ulm University Germany CAOSD ITIS Software University of Málaga Spain

Feature models are the de facto standard for modelling variabilities and commonalities. Concrete models in different domains exist;however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serialising feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents UVLHUB, a repository of feature models in UVL format. UVLHUB provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo providing a permanent save of datasets and following open science principles. UVLHUB includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling. © 2023, The Authors. All rights reserved.

关键词： Concretes

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Advantages of Fog Computing: A Comparative Analysis with Cloud Computing for Enhanced Edge Computing Capabilities

Advantages of Fog Computing: A Comparative Analysis with Clo...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Mykhailo Hunko Vitalii Tkachov Andriy Kovalenko Heorhii Kuchuk Department of Electronic Computers Kharkiv National University Of Radio Electonics Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

Fog computing extends the capabilities of cloud computing by enabling computing at the edge of the network, involving devices such as mobile collaborative devices or fixed nodes with integrated storage, computing, and communication capabilities. Fog computing offers benefits such as improved efficiency, increased security, savings in network bandwidth, and increased flexibility. In order to provide a complete understanding of Fog computing, this paper presents its salient features and highlights the differences from cloud computing research. Cloud computing is an emerging technology that offers computing resources on a pay-per-use basis. It provides three service models, and the cloud offers cost-effective centrally managed resources for reliable computing for specific tasks. This document presents a comparison between Fog computing and cloud computing, highlighting the differences in design, deployment, services, and tools available to organizations and users. By explicating the distinctiveness of fog computing and its contrast to cloud computing, we contribute to the field by shedding light on the unparalleled potential of fog computing in conserving resources while delivering robust computational solutions at the network periphery. Our study offers a new perspective that challenges the prevailing practices and extends the discourse on optimizing distributed computing architectures.

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Estimation of Potential Locations of Trade Objects on the Basis of Fuzzy Set Theory

Estimation of Potential Locations of Trade Objects on the Ba...

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International Conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Oglu, Alekperov Ramiz Balashirin Oglu, Salahli Vuqar Mamadali Information Technology and Programming Azerimed LLC BakuAZ1147 Azerbaijan Department of Computer Engineering Odlar Yurdu University BakuAZ1072 Azerbaijan

ISBN: (纸本)9783030511555

In the present article, we have considered the issue of selection of potential locations of trade objects as a multi-factor decision-making in the conditions of uncertainty by applying the theory of fuzzy sets. Examples were given to assess the location options of commercial enterprises and the potential location options of the facilities on these samples were assessed on the basis of a fuzzy extraction method in the notation MATLAB\Fuzzy Inferences Systems. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

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computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal Pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin Singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

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Determining the Qualities of Tests Designed for Students' Knowledge Assessment

Determining the Qualities of Tests Designed for Students' Kn...

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International Conference on High Technology for Sustainable Development (HiTech)

作者： Daniela Minkovska Elena Antonova Kiril Koparanov Krasin Georgiev Pamela Minkovska Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria Department of Computer Science Technical University of Sofia Sofia Bulgaria Department of Air Transport Technical University of Sofia Sofia Bulgaria Professional High School of Telecommunications Sofia Bulgaria

ISBN: (数字)9798350358100

ISBN: (纸本)9798350358117

As educators aim to evaluate students' knowledge, the design and quality of their assessment instruments play a vital role. Focusing on test difficulty, as well as comparing real and set results to determine knowledge levels ensure that tests adequately challenge students without overwhelming them. There are various methods incorporating these concepts, such as item response theory and classical test theory. Recognizing the patterns of student performance, thus highlighting areas requiring further attention, can foster targeted interventions to enhance learning outcomes.

关键词： Target recognition Instruments Focusing Pattern recognition Sustainable development

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Customs Fraud Detection Method Based on Artificial Intelligence and Data Analytics

Customs Fraud Detection Method Based on Artificial Intellige...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Veska Gancheva George Popov Ognyan Nakov Kamelia Raynova Antoaneta Popova dept. of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria dept. of Cybersecurity Technical University of Sofia Sofia Bulgaria dept. of Computer Systems Technical University of Sofia Sofia Bulgaria dept. of Information Technologies in Industry Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of customs data are complicated by its extreme imbalance. Finding autonomous, computationally sophisticated solutions for customs handling is therefore crucial. The study described in this paper aims to propose an artificial intelligence-based method for customs fraud detection through data analytics. A machine learning-based approach for detecting customs fraud is proposed. The research methodology includes data preprocessing, data analytics, combining results, and deriving precise solutions from results obtained. The aim is to extract meaningful information from a dataset. For the purpose of classifying customs fraud, seven algorithms for machine-learning-kNN, SGD, Constant, Logistic Regression, Random Forest, Neural Network, and Naive Bayes-are chosen and empirically assessed.

关键词： Training Analytical models Logistic regression Data analysis Neural networks Data models Fraud Bayes methods Data mining Random forests

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Approach for Estimating Distances between Centers of Geometric Shapes based on Image Analysis and its Evaluation

Approach for Estimating Distances between Centers of Geometr...

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2021 International Conference on Information Science and Communications Technologies, ICISCT 2021

作者： Takhirov, Shakhzod Kudratov, Sultan Kubantsev, Konstantin Engineering University of California - Berkeley Department of Civil and Environmental BerkeleyCA United States Technologies and Programming Tashkent University of Information Technologies Department of Information and Computer Tashkent Uzbekistan

ISBN: (纸本)9781665432580

A digital image is usually stored as a two-dimensional matrix consisting of numerical values of the intensity of each color;for example, Red-Green-Blue (RGB). This fact allows a possibility of manipulation of the image data, including making measurements based on the images of a moving object. This paper presents a new approach for estimating distances between the centers of geometric shapes based on image analysis. The algorithm is based on determining the parameters of the matrices - the number of rows and columns of graphic images of target plates and creating vectors of the sums of their values. As a result of such manipulations, peaks (maxima, minima) are formed that coincide with the centers of the squares and circles displayed on the target plates. These peaks are the coordinates of the target centers. © 2021 IEEE.

关键词： Image analysis

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Forecasting and modeling on average rainwater and vapor pressure in Chelyabinsk Russia using deep Learning models 6

Forecasting and modeling on average rainwater and vapor pres...

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6th Smart Cities Symposium, SCS 2022

作者： Abotaleb, Mostafa Makarovskikh, Tatiana Subhi, Alhumaima Ali Alkattan, Hussein Adebayo, Adelaja Oluwaseun Department of System Programming South Ural State University Chelyabinsk454080 Russia Electronic and Computer Center University of Diyala BaqubahMJJ2+R9G Iraq Information Communication and Technology Department Lagos State University Lagos102101 Nigeria

ISBN: (纸本)9781839538544

Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future performance of rainfall data and vapor in Chelyabinsk by using a machine learning technique. The data series is divided into a training set (60%) and a test set (40%) for model developing a validation purpose. We further developed deep learning models such as, LSTM, BILSTM, GRU and compared on the basis of ME, RMSE, MAE, MPE, MAPE, ACF1 on the training data set. For testing data set, we compared these deep learning models based on RMSE. LSTM model acts as a superior machine learning model over BILSTM and GRU in this data series. Forecasting performance of these three models significantly at par. This finding may be significant to build a strong literature of the Chelyabinsk weather's forecast, which can be helpful for policy makers and researchers. Also, we strongly believe that, this work could be used as a literature adaptation of machine learning technique for complex time series over statistical models. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Statistical tests

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Identification of the Parameter of the Single-Phase Flow Model in the Reservoir with the Power Law of Filtration

Identification of the Parameter of the Single-Phase Flow Mod...

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International Conference on Problems of Cybernetics and Informatics (PCI)

作者： Khanlar Gamzaev Sergey Leonov Sevil Huseynzade Sevinc Kerimova Department of General and Applied Mathematics Azerbaijan State Oil and Industry University Baku Azerbaijan Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" (of Affiliation) Kharkiv Ukraine

The process of unsteady flow of a single-phase liquid in a cylindrical reservoir arising under the elastic mode of reservoir development is considered. To describe this process, a power law of filtration is proposed for a single-phase flow in a porous medium. Within the framework of the proposed model, the task of identifying one parameter of the model characterizing the simulated reservoir system is set. To construct a discrete analog of the inverse problem, the finite difference method is used using an explicit–implicit approximation in time. To solve the resulting system of nonlinear equations, a special representation is proposed that allows reducing the nonlinear system to two independent systems of linear equations. As a result, an explicit formula is obtained for determining the approximate value of the desired reservoir parameter. Based on the proposed method, numerical experiments were carried out for model problems.

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