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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Alexander Chernikov Elena Smirnova Oleg Zhavoronkov Higher School of Automation and Robotics Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Department of System Programming Saint Petersburg State University St. Petersburg Russia Computer Vision Systems LLC St. Petersburg Russia

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation – 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526.

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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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Analysing the Impact of COVID-19 outbreak and Economic Policy Uncertainty on Stock Markets in Major Affected Economies 6

Analysing the Impact of COVID-19 outbreak and Economic Polic...

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6th Smart Cities Symposium, SCS 2022

作者： Matuka, Adelajda Asafo, Shuffield Seyram Eweke, Gamaliel O. Mishra, Pradeep Ray, Soumik Abotaleb, Mostafa Makarovskikh, Tatiana Alhussan, Amel Ali Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Dutta, P.K. Chowdhury, Subrata University of Macerata Department of Economics and Law Italy Niger Delta University Department of Banking & Finance Nigeria J.N.K.V.V. College of Agriculture M.P. Powarkheda India Centurion University of Technology and Management Odisha Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog Egypt School of Engineering and Technology Amity University West Bengal Kolkata India AP Chittoor India

ISBN: (纸本)9781839538544

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. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Investments

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Investigation of a safety parameter observer for wireless communication

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International Journal of Circuits, Systems and Signal Processing 2020年 14卷 1005-1005页

作者： Schwarz, Michael H. Gaus, Larissa Börcsök, Josef Dept. Computer architecture and System programming University Kassel Kassel Germany Dept. Computer architecture and system programming Universität Kassel Kassel Germany

This paper investigates the possibilities to monitor the degree of disturbances of a wireless communication and to use this information to calculate online the necessary safety parameters in order to estimate the probability of failure per hour (PFH) and the safety integrity level (SIL). Depending of the degree of disturbances, addition actions are performed with the intention of keeping the current safety level. A hardware set-up is introduced to get process data and to evaluate the results. © 2020, North Atlantic University Union NAUN. All rights reserved.

关键词： Hamming distance

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WAM Systems: Comparative Analysis of Information Support Quality

WAM Systems: Comparative Analysis of Information Support Qua...

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2020 IEEE International Conference on Problems of Infocommunications Science and Technology, PIC S and T 2020

作者： Obod, Ivan Svyd, Iryna Maltsev, Oleksandr Zavolodko, Ganna Leonov, Sergiy Kharkiv National University of Radio Electronics Dept. of Microprocessor Technologies and Systems Kharkiv Ukraine National Technical University khPI Dept. of Information Systems Kharkiv Ukraine National Technical University khPI Dept. of Computer Engineering and Programming Kharkiv Ukraine

ISBN: (纸本)9781728191775

The paper considers ways to improve the quality of information support for airspace control systems and air traffic control with the help of wide-area multi-position monitoring systems. A comparative analysis has shown that the accuracy of estimating air object coordinates by the wide area multilateration system under consideration is significantly higher than that provided by currently available wide area multilateration systems. It is shown that the introduction of active and passive methods for creating wide-area multi-position observation systems significantly broadens the number of available air object coordinate estimation techniques and, as a result, enhances the quality of information support by providing its users with the opportunity of choosing an optimal estimation method for various primary measurements of received signal parameters. Active wide area multilateration systems significantly expand the number of methods available for solving the problem of adequate information support to airspace control system users;use of secondary surveillance radar aircraft responders allows estimating air object coordinates by both single-position and multi-position method. © 2020 IEEE.

关键词： Air traffic control

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Machine Learning Model for Predicting Failures in the Context of Autonomous Vehicles

Machine Learning Model for Predicting Failures in the Contex...

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International Conference on System Reliability and Science (ICSRS)

作者： Abderrahim Krini Aymen Ouertani Habil. Josef Börcsök Engineering of Reliability and Quality Functional Safety Robert Bosch GmbH Schwäbisch Gmünd Germany Institute of Functional Safety & Cyber Security Baden-Wuerttemberg Cooperative State University Lörrach Germany Computer Architecture und System Programming University of Kassel Kassel Germany

In general, failure data is obtained in the automotive industry during the warranty period. If these contain the expression of a service life characteristic for each failure, statements can be made about the reliability and availability of the systems. For this purpose, estimation methods are used to adapt empirical lifetime distributions to theoretical lifetime distributions. By means of the distribution characteristics, a prognosis of the reliability and availability to be expected is also possible beyond the observation time. In addition to the data basis to be investigated, which is available completely in test bench and experimental trials or re-censored in the field, various methods can be used for estimation. In the past, several methods have been used, such as the estimators according to Eckel [1], Kaplan-Meier [2] or the estimators according to Pauli [3]. In general, a field failure is subject to several stresses, which can be described by expressions of several lifetime characteristics. For this application case, which occurs in the automotive industry, the known estimation methods, [1]–[3], cannot be used. In this paper, the necessity of multidimensional estimation methods will be introduced first. Then, a new estimation method for multidimensional metrics is presented. In a further step, mathematical proof is given that the new method can provide realistic results. Finally, two example data sets from bench testing and field are presented. Furthermore, some recommendations for the use of the new method are concretized in this context.

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A novel reduction method for type-2 uncertain normal critical values and its applications on 4D profit transportation problem involving damageable and substitute items

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International Journal of Applied and Computational Mathematics 2021年第4期7卷 1-30页

作者： Sahoo, Palash Jana, Dipak Kumar Pramanik, Sutapa Panigrahi, Goutam Department of Mathematics National Institute of Technology Durgapur Durgapur 713209 West Bengal India School of Applied Sciences & Humanities Haldia Institute of Technology Haldia Purba Midnapur 721657 West Bengal India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721102 West Bengal India

In this paper, we developed and investigated some four-dimensional profit maximization transportation problems considering damageablity and substitutability, where the parameters are of a type-2 normal uncertain variable in nature. Here, unit transportation cost, distances of the paths, fixed charges, rate of breakability, availability, demands, capacities of conveyances, the unit selling price, unit purchasing cost, unit procurement cost are regarded as type-2 normal uncertain variables. Two models are formulated based on two separate criteria of the substitution items. We use a critical value-based reduction method to reduce type-2 normal uncertain variables into type-1 normal uncertain variables and then apply some properties of uncertainty theory to convert the profit transportation parameters into deterministic form. The two deterministic models are solved using the optimization software named LINGO -18.0. A real-life numerical example and optimal results are presented here to show the application of the proposed model and the proposed reduction method. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Critical value Four dimensional profit transportation problem Reduction method Type-2 normal uncertain variables

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A Systematic Review on Security and Safety of Self-Adaptive Systems

SSRN

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SSRN 2022年

作者： Pekaric, Irdin Groner, Raffaela Witte, Thomas Adigun, Jubril Gbolahan Raschke, Alexander Felderer, Michael Tichy, Matthias University of Innsbruck Department of Computer Science Technikerstraße 21a InnsbruckA-6020 Austria Ulm University Institute of Software Engineering and Programming Languages James-Franck-Ring 9 Ulm89081 Germany

Context: Cyber-physical systems (CPS) are increasingly self-adaptive, i.e. they have the ability to introspect and change their behavior. This self-adaptation process must be considered when modeling the safety and security aspects of the ***: This study collects and compares security attacks and safety hazards on self-adaptive systems (SAS) described in the literature. In addition, mitigation and treatment strategies as well as the modeling and analysis approaches are ***: We conducted a systematic literature review on 21 selected papers. The selection process involved a database search and snowballing methodologies. The coding scheme to analyze the content of the papers was obtained through our research questions, existing domain-specific taxonomies, and open ***: Safety and Security are not jointly modeled in the context of self-adaptive systems. The adaptation process is often not considered in the attack and hazard analysis due to naïve assumptions and modeling. The proposed approaches are mostly verified and validated through ***: A thorough and joint modeling approach for safety and security in self-adaptive systems is still an open challenge that needs to be addressed. Further work is needed to address the gap between safety and security modeling in self-adaptive systems. © 2022, The Authors. All rights reserved.

关键词： Adaptive systems

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Evaluating Length of a Shortest Adaptive Homing Sequence for Weakly Initialized FSMs

Evaluating Length of a Shortest Adaptive Homing Sequence for...

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2020 IEEE East-West Design and Test Symposium, EWDTS 2020

作者： Vinarskii, Evgenii Yevtushenko, Nina Lomonosov Moscow State University Department of Computer Science Moscow Russia Ivannikov Institute for System Programming of Ras Software Engineering Deparment Moscow Russia

ISBN: (数字)9781728198996

ISBN: (纸本)9781728198996

There are many research papers devoted to the state identification problem of finite state machines (FSMs) which are widely used for analysis of discrete event systems. A deterministic complete reduced FSM always has a homing sequence (HS) but a number of non-deterministic FSMs not necessarily have a preset HS;nevertheless, those FSMs can still have an adaptive HS. Moreover, adaptive HS can be shorter than the preset. If each state can be an initial state of a complete FSM, i.e., an FSM is non-initialized, then a shortest adaptive HS (if it exists) has polynomial length in the number of FSM states. We show that it is not the case for weakly-initialized FSMs: such FSMs can have a shortest adaptive HS of exponential length in the number of FSM states/transitions. However, the experimental evaluation shows that the non-polynomial upper bound for a shortest adaptive HS was never reached for randomly generated weakly-initialized two-input FSMs. © 2020 IEEE.

关键词： Adaptive homing sequence Non-deterministic FSM weakly initialized FSM

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Evaluating Keyphrase Extraction Methods for Clustering Influenza-Related Scientific Papers

Evaluating Keyphrase Extraction Methods for Clustering Influ...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Majid Forghani Artyom Firstkov Mohammad. M. AlyanNezhadi Kazem Forghani Mathematical Programming Lab. Krasovskii Institute of Mathematics & Mechanics Yekaterinburg Russia Department of Science University of Science and Technology of Mazandaran Behshahr Iran Computer Science Department Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9781665476249

The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care; molecular biology & immunology; and phylogenetic & epidemiological studies.

关键词： Databases Immunology Biological system modeling Influenza Search engines Phylogeny Molecular biology

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