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3rd IEEE International Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Goshko, Elena Yu. Kharlamov, Alexey S. Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia Kemerovo region Prokopyevsk Russia

ISBN: (纸本)9798331516321

Blasting operations carried out at mining enterprises and in construction have a negative seismic impact on the production environment of enterprises and other protected objects. As the pit depth increases, the slope angle of the ledges and sides increases, which increases the likelihood of collapses as a result of seismic impacts of blasting *** information system SIBGEO-AM - seismic monitoring of industrial explosions at mining enterprises, created by SIGI LLC, is described. The seismic monitoring system includes a network of seismic stations installed along the perimeter of the quarry excavation, and a computer program designed to automate the process of collecting, data processing, analyzing, presenting, viewing and storing seismic monitoring results. Examples of records of typical seismic impacts of industrial explosions are given. Algorithms of filtration, selection of events, calculation of seismic impact force in the epicenter of the explosion on the side of the quarry are shown. © 2024 IEEE.

关键词： Quarries

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eHealth Mobile Application Using Fitbit Smartwatch 1

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8th International Conference on Advancements of Medicine and Health Care through Technology, MEDITECH 2022

作者： Pop, Adela Fanca, Alexandra Valean, Honoriu Gota, Dan-Ioan Stan, Ovidiu Roman, Marius Nicolae Clitan, Iulia Muresan, Vlad Faculty of Automation and Computer Science Department of Automation Technical University of Cluj Napoca Cluj Napoca Romania Faculty of Electrical Engineering Electrical Engineering and Measurements Department Technical University of Cluj Napoca Cluj Napoca Romania

ISBN: (数字)9783031511202

ISBN: (纸本)9783031511196

Health is one of the most precious aspects of every person's life. Whether we're talking about a well-functioning heart, nervous system, respiratory system, or simply body weight, each of these branches contributes to a person's overall health. It is important to monitor certain body functions and characteristics as often as possible so that we can prevent or, in unfortunate situations, treat health problems early. The developed mobile application facilitates the monitoring of heart rate, ideal weight, basal metabolic rate, and body mass index. The data used by the mobile app is collected by the FITBIT smartwatch. Based on the data, heart rate statistics and nutritional calculation results (body mass index, basal metabolic rate, and ideal body weight) are generated according to the user's gender, age, weight, and height. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Metabolism

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Enhancing the Recommender System Algorithm's Quality Through the Utilization of Affinity Analysis 16

Enhancing the Recommender System Algorithm's Quality Through...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Stubarev, Igor M. Alsova, Olga K. Yakimenko, Alexander A. Novosibirsk State Technical University Faculty of Automation and Computer Engineering FB Consult Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia Novosibirsk State Technical University Faculty of Automation and Computer Engineering Institute of Computational Mathematics and Mathematical Geophysics SB RAS Laboratory of Geophysical Informatics Novosibirsk Russia

ISBN: (纸本)9798350330885

The demand for auxiliary systems that utilize methods and technologies of intellectual data analysis and machine learning is increasing in the CRM system development field. These systems are capable of generating valuable insights from vast amounts of data collected in CRM. The article shows the results of the development and study of the CRM system using the methods of affinity analysis. Earlier, the authors developed and implemented the base version of the recommender algorithm based on the use of cluster data analysis and collaborative filtration [1, 2]. The new version of the algorithm additionally uses affinity analysis methods to form recommendations for the selection of products, which made it possible to increase the accuracy of the recommendation system (service) by metrics F2 on average from 67.98% to 81.24% with an increase in the time for issuing recommendations (On average by 2.47 ms). The study and comparison of the basic and modified versions of the algorithm were executed using data sourced from insurance companies, furnished by "FB Consult". © 2023 IEEE.

关键词： Collaborative filtering

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Improving Dendritic Neuron Model With Dynamic Scale-Free Network-Based Differential Evolution

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 99-110页

作者： Yang Yu Zhenyu Lei Yirui Wang Tengfei Zhang Chen Peng Shangce Gao College of Automation&College of Artificial Intelligence Nanjing University of Posts and TelecommunicationsNanjing 210023China Faculty of Engineering University of ToyamaToyama-shi 930-8555Japan Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Department of Automation School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China

Some recent research reports that a dendritic neuron model(DNM)can achieve better performance than traditional artificial neuron networks(ANNs)on classification,prediction,and other problems when its parameters are well-tuned by a learning ***,the back-propagation algorithm(BP),as a mostly used learning algorithm,intrinsically suffers from defects of slow convergence and easily dropping into local ***,more and more research adopts non-BP learning algorithms to train *** this paper,a dynamic scale-free network-based differential evolution(DSNDE)is developed by considering the demands of convergent speed and the ability to jump out of local *** performance of a DSNDE trained DNM is tested on 14 benchmark datasets and a photovoltaic power forecasting *** meta-heuristic algorithms are applied into comparison,including the champion of the 2017 IEEE Congress on Evolutionary Computation(CEC2017)benchmark competition effective butterfly optimizer with covariance matrix adapted retreat phase(EBOwithCMAR).The experimental results reveal that DSNDE achieves better performance than its peers.

关键词： Artificial neuron networks(ANNs) dendrite neuron network differential evolution(DE) scale-free network

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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

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FPGA-implementation of the Decision Block for Numerical Prediction System Based on Artificial Neural Networks

FPGA-implementation of the Decision Block for Numerical Pred...

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2023 Seminar on Information Computing and Processing, ICP 2023

作者： Krutikov, Alexander K. Meltsov, Vasily Yu. Strabykin, Dmitry A. Vyatka State University Faculty of Automation and Computer Engineering Department of Electronic Computers Kirov Russia

ISBN: (纸本)9798350369830

This paper considers the method of cascading neural network modules to build the operating device of a specialized computing system. Each module implements some model of neural network. The cascade of modules is formed strictly in accordance with the logical links, found after the analysis of training samples. The structure of the input vector is fragmented according to the logical dependencies of the parameter set. Individual nodes of the cascade process certain fragments of the input vector, taking into account the features of neural network models used in them. The library containing the basic elements was prepared in the Quartus II CAD. The prototype with the ensemble of the main modules is implemented on the Cyclone III FPGA. Comparative assessments of the hardware- and software- implementation of the system for predicting numerical results in sports disciplines and multisport competitions are presented. © 2023 IEEE.

关键词： Neural networks

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The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

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computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： Muhammad Dawood Shanshan Tu Chuangbai Xiao Muhammad Haris Hisham Alasmary Muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

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Design of a Control System for Stabilizing the Angular Position of Platforms on a Movable Base 3

Design of a Control System for Stabilizing the Angular Posit...

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3rd IEEE International Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Van Tam, Bui Yurkevich, Valery D. Vietnam Naval Academy Missile and Gunnery Faculty Nha Trang Viet Nam Novosibirsk State Technical University Automation and Computer Engineering Faculty Novosibirsk Russia

ISBN: (纸本)9798331516321

The problem of a control system design is discussed to provide an angular position platform stabilization. The platform is used to install various navigation equipment and communication devices. Stabilization of the platform's angular position eliminates the influence of vibrations of the platform's moving base on the operation of this equipment. The platform is equipped with an electrohydraulic drive, which ensures the horizontal position of the platform under conditions of vibrations of the vessel deck. The control system is designed in such a way that fast and slow processes are created in a closedloop system. The discussed approach to control system design allows to provide stability and robustness for position of the platform under vibrations of the vessel deck. The effect of the small parameters of the electrohydraulic drive on control system stability is treated. The selection of the controller parameters is carried out by additionally taking into account the sensitivity function, which reflects the influence of wave disturbances on the angular position of the platform. © 2024 IEEE.

关键词： Hydraulic drives

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Machine Learning-Based Methods for Materials Inverse Design: A Review

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computers, Materials & Continua 2025年第2期82卷 1463-1492页

作者： Yingli Liu Yuting Cui Haihe Zhou Sheng Lei Haibin Yuan Tao Shen Jiancheng Yin Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650093China Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and TechnologyKunming650500China Yunnan Tin Company Limited Tin Industry Branch Gejiu661000China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming650093China

Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new *** through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired *** paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse ***,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application ***,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are *** authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.

关键词： Materials inverse design machine learning target properties deep learning new materials discovery

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DDT-Net:Deep Detail Tracking Network for Image Tampering Detection

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computers, Materials & Continua 2025年第5期83卷 3451-3469页

作者： Jim Wong Zhaoxiang Zang Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang443002China College of Computer and Information Technology ChinaThree Gorges UniversityYichang443002China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650504China

In the field of image forensics,image tampering detection is a critical and challenging *** methods based on manually designed feature extraction typically focus on a specific type of tampering operation,which limits their effectiveness in complex scenarios involving multiple forms of *** deep learningbasedmethods offer the advantage of automatic feature learning,current approaches still require further improvements in terms of detection accuracy and computational *** address these challenges,this study applies the UNet 3+model to image tampering detection and proposes a hybrid framework,referred to as DDT-Net(Deep Detail Tracking Network),which integrates deep learning with traditional detection *** contrast to traditional additive methods,this approach innovatively applies amultiplicative fusion technique during downsampling,effectively combining the deep learning feature maps at each layer with those generated by the Bayar noise *** design enables noise residual features to guide the learning of semantic features more precisely and efficiently,thus facilitating comprehensive feature-level ***,by leveraging the complementary strengths of deep networks in capturing large-scale semantic manipulations and traditional algorithms’proficiency in detecting fine-grained local traces,the method significantly enhances the accuracy and robustness of tampered region *** with other approaches,the proposed method achieves an F1 score improvement exceeding 30% on the DEFACTO and DIS25k *** addition,it has been extensively validated on other datasets,including CASIA and *** results demonstrate that this method achieves outstanding performance across various types of image tampering detection tasks.

关键词： Image forensics image tampering detection image manipulation detection noise flow Bayar

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