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Platform for big biomedical data streams management and analytics

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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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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Structure and Functioning of Information Systems of Background Monitoring of Landscape Elements of Gorgany Nature Reserve 10

Structure and Functioning of Information Systems of Backgrou...

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10th International Conference on Advanced computer Information Technologies, ACIT 2020

作者： Nykolaychuk, Yaroslav Petrashchuk, Yaroslav Slobodian, Olena Pitukh, Ihor Grynchyshyn, Taras Nykolaychuk, Lyubov Hryha, Volodymyr Ternopil National Economic University Department of Specialized Computer Systems Ternopil Ukraine Gorgany Nature Reserve Nadvirna Ukraine Nadvirna College by National Transport University Department of Programming and Information Technologies Nadvirna Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Social Communication and Law Ivano-Frankivsk Ukraine Vasyl Stefanyk Precarpathian National University Department of Computer Engineering and Electronics Ivano-Frankivsk Ukraine

This paper discusses the structural organization of the background monitoring system (BMS) of the transboundary UNESCO World Heritage Site 'Beech forests of the Carpathians and ancient beech forests of Germany' using actual data and information from Gorgany Nature Reserve in Ivano-Frankivsk, Ukraine. The features of the structure and functions of background monitoring of the protected natural resources, forests and wildlife of Gorgany Nature Reserve is based on modern methods of collecting and processing of digital data, implementation of the principles of Internet of Things and cloud technologies, combined with GPS-systems, sensor networks with the use of optical and fiber-optic telecommunication channels. The information technology of the background monitoring system is based on figurative cluster models of monitoring objects according to theoretical principles of statistical, correlatory, spectral, cluster, logic-statistical and entropy analysis. © 2020 IEEE.

关键词： Sensor networks

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