The COVID-19 pandemic has witnessed the role of online social networks (OSNs) in the spread of infectious diseases. The rise in severity of the epidemic augments the need for proper guidelines, but also promotes the p...
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ISBN:
(纸本)9798350328066
The COVID-19 pandemic has witnessed the role of online social networks (OSNs) in the spread of infectious diseases. The rise in severity of the epidemic augments the need for proper guidelines, but also promotes the propagation of fake news-items. The popularity of a news-item can reshape the public health behaviors and affect the epidemic processes. There is a clear inter-dependency between the epidemic process and the spreading of news-items. This work creates an integrative framework to understand the interplay. We first develop a population-dependent 'saturated branching process' to continually track the propagation of trending news-items on OSNs. A two-time scale dynamical system is obtained by integrating the news-propagation model with SIRS epidemic model, to analyze the holistic system. It is observed that a pattern of periodic infections emerges under a linear behavioral influence, which explains the waves of infection and reinfection that we have experienced in the pandemic. We use numerical experiments to corroborate the results and use Twitter and COVID-19 data-sets to recreate the historical infection curve using the integrative model.
Early screening of arterial stiffness plays a crucial role in reducing cardiovascular risk and mortality, as well as promoting healthy aging. However, asymptomatic patients are frequently overlooked due to the lack of...
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Early screening of arterial stiffness plays a crucial role in reducing cardiovascular risk and mortality, as well as promoting healthy aging. However, asymptomatic patients are frequently overlooked due to the lack of specialized interpretation and the costly hospital-based equipment required by traditional clinical methods, potentially leading to adverse consequences. This study presents IF-ASS, an interpretable framework designed to facilitate widespread screening of arterial stiffness at an earlier stage by utilizing routinely acquired photoplethysmography (PPG) signals. The data was collected from 205 participants (aged 21-82 years) through two recruitment phases. A novel vascular volume analysis (VVA) of PPG conduction was proposed to expanded the methods for extracting general PPG features. And subsequently 216 features were derived. The features, characterized by their meaningful functionalities, were combined using the proposed feature pooling (FP) algorithm. This method attained the highest dimensionality reduction rate (DRR = 94.9 %, 15.17 % improvement), while offering scalable combinations for model enhancement. The optimal trade-off between effectiveness and interpretability was achieved by modeling an improved probability risk explanation method based on eXtreme Gradient Boosting and Shapley Additive exPlanations. Among multidimensional comparisons and validations, IF- ASS demonstrated superior stability, delivering the highest area under the receiver operating characteristic curve (AUC) of 0.924, and accuracy (ACC) of 0.850 (3.25 % mean improvement). Attributively, inspired explorations significantly boosted the trustworthiness of IF-ASS. In conclusion, the IF-ASS could be considered a reliable and cost-effective tool for screening latent arterial stiffness in ubiquitous settings, particularly in the trends of disease onset at younger ages and an aging population.
The proceedings contain 38 papers. The topics discussed include: a multidisciplinary approach to telegram dataanalysis;addressing hydrogen safety insights and challenges by means of software tools;architectural abstr...
ISBN:
(纸本)9786197603743
The proceedings contain 38 papers. The topics discussed include: a multidisciplinary approach to telegram dataanalysis;addressing hydrogen safety insights and challenges by means of software tools;architectural abstractions in the design of distributed embedded systems platforms;artificial neural network vs. linear regression for modeling reactor of the catalytic cracking process;control system for greenhouses using industrial networked devices;impact of digitization on key performance indicators of the production process on the example of the AGH LEANLINE project;impact of digitization on key performance indicators of the production process on the example of the AGH LEANLINE project;knowledge sharing in distributed teams - the impact of virtual collaboration tools;and organization of mixed-critical computing systems for control of multi-operational technological systems.
The long-term effects of the Vision -Zero (VZ) approach in Scandinavia are well documented. In contrast, information regarding the immediate effects of VZ at the starting phase upon gradual implementation is scarce. T...
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The long-term effects of the Vision -Zero (VZ) approach in Scandinavia are well documented. In contrast, information regarding the immediate effects of VZ at the starting phase upon gradual implementation is scarce. Taking New York City as the case study, we analyzed both the local and global effects of the Vision -Zero gradual implementation on pedestrian crashes in the early stage of implementation starting from 2014. The dataanalysis comprised 8,165 pedestrian injury crashes. Using location data, the crashes were matched to VZ infrastructure improvement location, start and completion dates. The experimental design included a treatment and two types of control conditions, and we controlled for well-known covariates including traffic exposure, land use, and risk -prone areas. We estimated a Geyer Saturation model and kernel density function for modeling the effect of Vision -Zero on crash intensity and dispersion two years before and after the implementation of Vision -Zero. The results reveal a significant global decrease of 6.1 % (p = 0.004) in pedestrian crash incidence in the treated sections compared with the control group two years after the treatment, and a greater dispersion of pedestrian injuries following the policy implementation.
Integrated opto-mechanical analysis (IOA) for Photoelectric detection and tracking systems (PDTS) is crucial both in the early design phase and during later operation and maintenance. The movements of PDTS typically g...
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Integrated opto-mechanical analysis (IOA) for Photoelectric detection and tracking systems (PDTS) is crucial both in the early design phase and during later operation and maintenance. The movements of PDTS typically generate unbalanced momentum, resulting in noticeable line-of-sight jitters (LOSJs) and wavefront aberrations (WFAs) of the beam. However, the characteristics of multidisciplinary coupling and multibody system dynamics bring challenges to the measurement of LOSJ and WFA. To address this challenge, this paper proposes a modeling method for the opto-mechanical coupling problems of PDTS during dynamic processes. Firstly, a flexible multibody system dynamics model of PDTS is constructed to assess its kinematics, dynamics, and mechanics performance. The reaction moments and their effect on deformation and equivalent stress are obtained. Secondly, an optical model is developed to make the mechanical data available in optical analysis. The LOSJ and WFA are computed by using homogeneous coordinate transformation and ray tracing. Then, an engineering experiment and a numerical experiment are carried out to validate the accuracy of the model. The results show that the average relative error of LOSJ is 4.452%, the R2 of WFA is greater than 0.991, and the RMSE is less than 6.921 x 10-3, which verifies the accuracy and reliability of the proposed method. Finally, the multidisciplinary performance of PDTS under a dynamic condition is analyzed and discussed. The causes of LOSJ and WFA are clarified, and mitigation strategies for these phenomena are proposed. The proposed method and coupling analysis results have reference significance for the multidisciplinary design optimization and optoelectronic control of PDTS.
The ability to assess the surface quality quickly and accurately is of immense importance in manufacturing system. Modern metrology system along with machine learning is great at classification but requires more time....
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The ability to assess the surface quality quickly and accurately is of immense importance in manufacturing system. Modern metrology system along with machine learning is great at classification but requires more time. Traditionally accessing surface roughness is a time-consuming process. The progress in manufacturing technology necessitates improved approaches for quality control, specifically in the categorization of surface roughness, which has a substantial impact on the performance of materials. This research study introduces a novel method for classifying surface roughness by combining image data and point cloud data to create a comprehensive model. It then compares the performance of this model with a model that just relies on image data. A comprehensive analysis is conducted in this study, where image and point cloud data is collected and analysed. Multilinear principal component analysis (MPCA) along with random forest classifier is employed to create a model that classifies the surface texture. The primary goal is to showcase the enhanced precision and comprehensive understanding offered by the fused data model compared to the model that solely relies on images. Furthermore, the work presents a pragmatic approach for developing this enhanced model offline and applying it online in real-time production environments, with a particular focus on using only image data. This strategy is in line with the objectives of Industry 4.0, which seeks to achieve more intelligent and data-driven manufacturing processes. Subsequent investigations will prioritize expanding the model's suitability to various manufacturing settings, particularly highlighting its capacity to ensure quality in manufacturing lines through the utilization of images.
The paper examines issues of modeling and analysis of self-organized decentralized wireless sensor networks (WSN) and attacks on them. The object of the study is a WSN with decentralized functioning based on the roles...
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Accurate and distinct modeling of process and controller dynamics arises in cases where a system may be operating in closed-loop and only closed-loop data are available for identification or if an open-loop model of t...
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ISBN:
(数字)9781624107115
ISBN:
(纸本)9781624107115
Accurate and distinct modeling of process and controller dynamics arises in cases where a system may be operating in closed-loop and only closed-loop data are available for identification or if an open-loop model of the system is required to be identified from closed-loop data for the purpose of structural analysis or controller re-design. This paper introduces a method for identification of a closed-loop linear time-varying (LTV) system and observer/controller dynamics from experimental data only. Generalized observer/controller Markov parameters are computed from the given set of excitation signal, feedback control signal, and closed-loop response data. The system, observer gain, and controller gain Markov parameters are recovered from the identified observer/controller Markov parameters and a state-space model of the system as well as the corresponding observer and controller gains are identified using a statespace identification method such as the time-varying eigensystem realization algorithm. In the absence of noise, the open-loop system and the full-state feedback gain can be identified exactly. Modal parameters including frequencies, dampings, mode shapes at the sensor locations are then recovered from the open-loop system matrices. Two numerical examples are considered to demonstrate the applicability of this framework for guidance, navigation and control applications.
As the core of HVDC (High Voltage Direct Current) project, the control and protection program is the key to the engineering upgrade and transformation process. The lack of a visual analysis and description method for ...
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ISBN:
(纸本)9798350349009;9798350349016
As the core of HVDC (High Voltage Direct Current) project, the control and protection program is the key to the engineering upgrade and transformation process. The lack of a visual analysis and description method for differences before and after page modification in program. Modification can only be verified through program modification form filled out by engineering personnel, which can easily lead to inconsistencies such as omissions and errors. This article is based on the HCM3000 DC control and protection platform, and designs a analysis algorithm for different programs of the control and protection. By parsing the application files of the control and protection program, a class multiple linked list is generated, and dataprocessing is performed to generate a binary decomposition tree structure. Then, node matching is performed on the data structure chain based on the binary decomposition tree to ultimately achieve differential information comparison and ensure the accuracy of the control and protection program on the engineering site. The developed software has been applied in HVDC projects, greatly improving the reliability of project operation.
The proceedings contain 185 papers. The topics discussed include: the evolution of original ERP customization: a systematic literature review of technical possibilities;data-driven processanalysis of logistics system...
ISBN:
(纸本)9789897586927
The proceedings contain 185 papers. The topics discussed include: the evolution of original ERP customization: a systematic literature review of technical possibilities;data-driven processanalysis of logistics systems: implementation process of a knowledge-based approach;a performance analysis for efficient schema design in cloud-based distributed data warehouses;quantitative analysis of the relationship between master data quality and process quality;analyzing sepsis treatment variations in subpopulations with process mining;balancing autonomy and control: an adaptive approach for security governance in large-scale agile development;project management in large-scale with international settings: challenges faced with multiculturalism;on the integration of privacy-enhancing technologies in the process of software engineering;and software engineers engagement and job satisfaction: a survey with practitioners working remotely in a public organization.
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