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Mechanism of the use of the fixed assets of the mining industry enterprises

AIP Conference Proceedings 2023年第1期2910卷

作者： Zh. Kenzhin T. Aygumov K. Nursapina A. Zolkin O. Saradzheva West Kazakhstan agrarian and technical University named after Zhangir Khan Uralsk 090009 Kazakhstan Department of computer engineering software and automated systems Dagestan State Technical University Makhachkala Russia Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara 443010 Russia Economic security controlling and audit department A.N. Kosygin Russian State University Moscow 115035 Russia

Orientation of manufacturers on the development of the consumer market, the growth of competition between enterprises of various forms of ownership and various sectors of the economy contribute to a sharp increase in the interest of researchers in the problem of the efficiency of use of fixed assets, identification of the causes of the decline in capital productivity, and quantitative assessment of factors that make an influence on it. All these factors predetermined the relevance of the chosen topic as well the purpose and objectives of the study. Issues of use of fixed assets at mining enterprises are considered in the article. Factors and tools for the efficient use of fixed assets are analysed, and proposals and recommendations for improvement of the efficiency of use of fixed assets at the enterprise are formulated.

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Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

arXiv

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arXiv 2022年

作者： Hennebelle, Alain Ismail, Leila Materwala, Huned Kaabi, Juma Al Ranjan, Priya Janardhanan, Rajiv School of Computing and Information Systems The University of Melbourne Australia Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates College of Health Sciences Department of Internal Medicine United Arab Emirates University United Arab Emirates Mediclinic Al Ain Abu Dhabi United Arab Emirates Bhubaneswar Institute of Technology India Faculty of Medical & Health Sciences SRM Institute of Science & Technology India

Diabetes Mellitus, one of the leading causes of death worldwide, has no cure to date and can lead to severe health complications, such as retinopathy, limb amputation, cardiovascular diseases, and neuronal disease, if left untreated. Consequently, it becomes crucial to take precautionary measures to avoid/predict the occurrence of diabetes. Machine learning approaches have been proposed and evaluated in the literature for diabetes prediction. This paper proposes an IoT-edge-Artificial Intelligence (AI)-blockchain system for diabetes prediction based on risk factors. The proposed system is underpinned by the blockchain to obtain a cohesive view of the risk factors data from patients across different hospitals and to ensure security and privacy of the user’s data. Furthermore, we provide a comparative analysis of different medical sensors, devices, and methods to measure and collect the risk factors values in the system. Numerical experiments and comparative analysis were carried out between our proposed system, using the most accurate random forest (RF) model, and the two most used state-of-the-art machine learning approaches, Logistic Regression (LR) and Support Vector Machine (SVM), using three real-life diabetes datasets. The results show that the proposed system using RF predicts diabetes with 4.57% more accuracy on average compared to LR and SVM, with 2.87 times more execution time. Data balancing without feature selection does not show significant improvement. The performance is improved by 1.14% and 0.02% after feature selection for PIMA Indian and Sylhet datasets respectively, while it reduces by 0.89% for MIMIC III. © 2022, CC BY.

关键词： Logistic regression

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Corrigendum to “Identification of significant features and data mining techniques in predicting heart disease” [Telematics Informatics 36 (2019) 82–93]

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Telematics and Informatics 2022年 70卷

作者： Mohammad Shafenoor Amin Yin Kia Chiam Kasturi Dewi Varathan Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia BRAC University 66 Mohakhali Dhaka 1212 Bangladesh Department of Information Systems Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

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A hybrid solution for smart supermarkets based on actuator networks 7

A hybrid solution for smart supermarkets based on actuator n...

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7th International Conference on Information, Communication and Networks, ICICN 2019

作者： Zhang, Yanping Xiao, Zhifeng Yang, Jianjun Wraith, Katerina Mosca, Patrick Department of Computer Science Gonzaga University SpokaneWA United States Department of Computer Science and Software Engineering Penn State Erie the Behrend College EriePA United States Department of Computer Science and Information Systems University of North Georgia GA United States Apple Inc. ClaytonCA United States

ISBN: (纸本)9781728104263

Smart supermarkets are a recent innovation that allows customers to have a seamless shopping experience. The Internet of Things (IoT) is a key component of smart supermarkets. Take AmazonGo as an example, it successfully implements cashier-less store checkout. However, many staff members are still required to support the running of the supermarket. Labor is always a big cost. In this paper, we propose a hybrid solution for smart supermarkets based on actuator networks as well as IoT, in order to save labor costs and to serve customers effectively and efficiently. © 2019 IEEE.

关键词： Internet of things

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Analysis of the integration of robotic automation in production

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AIP Conference Proceedings 2024年第1期3102卷

作者： A. L. Zolkin T. G. Aygumov A. I. Adzhieva A. S. Bityutskiy Yu. N. Koval Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara 443010 Russia Department of computer engineering software and automated systems Dagestan State Technical University Makhachkala Russia Department of Accounting North Caucasus State Academy Karachay-Cherkess Republic Cherkessk 369001 Russia "Invent Technology" LLP Almaty A10E5P4 Kazakhstan FSBEI HE Siberian Fire and Rescue Academy EMERCOM of Russia Zheleznogorsk Krasnoyarsk Krai 662972 Russia

This scientific paper examines the integration of robotic automation in production and its potential benefits for businesses. The paper presents the results of a study that analyzed the impact of robotic automation on productivity, product quality, and cost savings for three different production lines. The study found that the implementation of robotic automation systems led to significant improvements in productivity and cost savings, as well as a decrease in defect rates. However, the study also highlights important factors that must be considered when deciding whether to integrate robotic automation into production, including the initial investment cost, the need for skilled workers, and the potential impact on workers. The paper concludes that while the integration of robotic automation in production is a complex issue that requires careful consideration, businesses that are able to successfully integrate these systems into their production processes can gain a competitive advantage in the marketplace, leading to increased profitability and long-term sustainability, but proper planning and implementation are key to ensuring success. for implementation.

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AuthCODE: A privacy-preserving and multi-device continuous authentication architecture based on machine and deep learning

arXiv

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arXiv 2020年

作者： Sánchez Sánchez, Pedro Miguel Huertas Celdrán, Alberto Fernández Maimó, Lorenzo Martínez Pérez, Gregorio Department of Information and Communications Engineering University of Murcia Murcia30100 Spain Telecommunication Software and Systems Group Waterford Institute of Technology WaterfordX91 P20H Ireland Department of Computer Engineering University of Murcia Murcia30100 Spain

The authentication field is evolving towards mechanisms able to keep users continuously authenticated without the necessity of remembering or possessing authentication credentials. While existing continuous authentication systems have demonstrated their suitability for single-device scenarios, the Internet of Things and next generation of mobile networks (5G) are enabling novel multi-device scenarios -such as Smart Offices-where continuous authentication is still an open challenge. The paper at hand, proposes an AI-based, privacy-preserving and multi-device continuous authentication architecture called AuthCODE. A realistic Smart Office scenario with several users, interacting with their mobile devices and personal computer, has been used to create a set of single- and multi-device behavioural datasets and validate AuthCODE. A pool of experiments with machine and deep learning classifiers measured the impact of time in authentication accuracy and improved the results of single-device approaches by considering multi-device behaviour profiles. The f1-score average reached for XGBoost on multidevice profiles based on 1-minute windows was 99.33%, while the best performance achieved for single devices was lower than 97.39%. The inclusion of temporal information in the form of vector sequences classified by a Long-Short Term Memory Network, allowed the identification of additional complex behaviour patterns associated to each user, resulting in an average f1-score of 99.02% on identification of long-term behaviours. Copyright © 2020, The Authors. All rights reserved.

关键词： Authentication

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Correction to: Feature selection and risk prediction for patients with coronary artery disease using data mining

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Medical & biological engineering & computing 2022年第3期60卷 887页

作者： Nashreen Md Idris Yin Kia Chiam Kasturi Dewi Varathan Wan Azman Wan Ahmad Kok Han Chee Yih Miin Liew Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Malaya 50603 Kuala Lumpur Malaysia. Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Malaya 50603 Kuala Lumpur Malaysia. yinkia@um.edu.my. Department of Information Systems Faculty of Computer Science and Information Technology Universiti Malaya 50603 Kuala Lumpur Malaysia. Department of Medicine University Malaya Medical Centre 50603 Kuala Lumpur Malaysia. Department of Biomedical Engineering Faculty of Engineering Universiti Malaya 50603 Kuala Lumpur Malaysia.

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Timed data plane update in data center network 25

Timed data plane update in data center network

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25th IEEE International Conference on Parallel and Distributed systems, ICPADS 2019

作者： Liu, Yuxiang Gao, Xiaofeng Zheng, Jiaqi Chen, Guihai Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781728125831

software-Defined Networks make it more principled and formal to operate and verify networks, which decouple the control plane and the data plane and introduce flexibility and programmability into the network. The SDN control plane needs to frequently update the data plane. However, the decoupled control and data planes face new challenges. The network is still an asynchronous distributed system in rule updates. If the update operations are not carefully scheduled, it may result in blackhole, congestions, and violate the consistency properties. Motivated by the tightly synchronized SDNs, we proposed TIDERS Algorithm for consistent network updates in 'timed SDNs'-where one node update can be scheduled at specific time. In TIDERS, we use synchronized time technique to achieve fast network updates while guaranteeing consistency properties. We focus on congestion-free in scheduling the update operations. To achieve this, we first set up a flow-based dependency graph and transform it into switch-operation level dependency graph. Based on operation dependency graph, we generate an update schedule and gradually optimize it to finally get a fast update schedule. After that, we conduct a series of simulations comparing our approach with several other methods to evaluate it. © 2019 IEEE.

关键词： Flow graphs

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Design of a Cryptographically Secure Pseudo Random Number Generator with Grammatical Evolution

Research Square

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Research Square 2021年

作者： Ryan, Conor Kshirsagar, Meghana Vaidya, Gauri Cunningham, Andrew Sivaraman, R. Biocomputing and Developmental Systems Group Lero The Science Foundation Ireland Research Centre for Software Computer Science and Information System Department University of Limerick LimerickV94 T9PX Ireland Intel Research and Development Ireland Limited LeixlipW23 CX68 Ireland Department of Electronics Communication Engineering School of Electrical and Electronics Engineering Shanmugha Arts Science Technology and Research Academy Deemed to be University Thanjavur613401 India

This work investigates the potential of evolving an initial seed with Grammatical Evolution (GE), for the construction of cryptographically secure (CS) pseudo-random number generator (PRNG). We harness the flexibility of GE as an entropy source for returning initial seeds. The initial seeds returned by GE demonstrate an average entropy value of 7.920261600000001 which is extremely close to the ideal value of 8. The initial seed combined with our proposed approach, control_flow_incrementor, is used to construct both, GE-PRNG and GE-CSPRNG. The random numbers generated with CSPRNG meet the prescribed National Institute of Standards and Technology (NIST) SP800-22 requirements. Monte Carlo simulations established the efficacy of the PRNG. The experimental setup was designed to estimate the value for pi, in which 100,000,000 random numbers were generated by our system and which resulted in returning the value of pi to 3.146564000, with a precision up to six decimal digits. The random numbers by GE-PRNG were compared against those generated by Python’s rand() function for sampling. The sampling results, when measured for accuracy against twenty-nine real world regression datasets, showed that GE-PRNG had less error when compared to Python’s rand() against the ground truths in seventeen of those, while there was no discernible difference in the remaining twelve. © 2021, CC BY.

关键词： Monte Carlo methods

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Factor Graph Weight Particles aided Distributed Underwater Cooperative Positioning Algorithm

Research Square

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Research Square 2021年

作者： Zhang, Lingling Yu, Baoguo Tang, Chengkai Zhang, Yi Song, Houbing School of Marine Science and Technology Northwestern Polytechnical University Xi’an710072 China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China School of Electronics and Information Northwestern Polytechnical University Xi’an710072 China Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University FL32114 United States

The growing scale of marine exploration requires high-resolution underwater localization, which necessitates cooperation among underwater network nodes, considering the channel complexity and power efficiency. In this paper, we proposed factor graph weight particles aided distributed underwater nodes cooperative positioning algorithm (WP-DUCP). It capitalized on the factor graph and sum-product algorithm to decompose the global optimization to the product of several local optimization functions. Combined with the Gaussian parameters to construct the weighted particles and to realize the belief transfer, it shows low complexity and high efficiency, suitable to the energy-restricted and communication distance-limited underwater networks. In terms of convergence, localization resolution, and computation complexity, we conducted the simulation and real-test with comparison to the existing co-localization methods. The results verified a higher resolution of the proposed method with no extra computation burden. © 2021, CC BY.

关键词： Global optimization

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