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Spatial modeling and analysis of Human Traffic and Infectious Virus Spread in Community Networks 43

Spatial Modeling and Analysis of Human Traffic and Infectiou...

引用

43rd Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (IEEE EMBC)

作者： Zhang, Siqi Yang, Hui Penn State Univ Complex Syst Monitoring Modeling & Control Lab University Pk PA 16802 USA

ISBN: (纸本)9781728111797

The use of network models to study the spread of infectious diseases is gaining increasing interests. They allow the flexibility to represent epidemic systems as networks of components with complex and interconnected structures. However, most of previous studies are based on networks of individuals as nodes and their social relationships (e.g., friendship, workplace connections) as links during the virus spread process. Notably, the transmission and spread of infectious viruses are more pertinent to human dynamics (e.g., their movements and interactions with others) in the spatial environment. This paper presents a novel network-based simulation model of human traffic and virus spread in community networks. We represent spatial points of interests (POI) as nodes where human subjects interact and perform activities, while edges connect these POIs to form a community network. Specifically, we derive the spatial network from the geographical information systems (GIS) data to provide a detailed representation of the underlying community network, on which human subjects perform activities and form traffics that impact the process of virus transmission and spread. The proposed framework is evaluated and validated in a community of university campus. Experimental results showed that the proposed simulation model is capable of describing interactive human activities at an individual level, as well as capturing the spread dynamics of infectious diseases. This framework can be extended to a wide variety of infectious diseases and shows strong potentials to aid the design of intervention policies for epidemic control.

关键词： Epidemiology network modeling spatial network human traffic infectious disease COVID-19

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Prediction and analysis of Customer Churn of Automobile Dealers Based on BI

Prediction and Analysis of Customer Churn of Automobile Deal...

引用

IEEE Information Technology, Networking, Electronic and Automation control conference

作者： Deqing Zhang Cuoling Zhang Chun Zheng School of Computer Engineering Anhui Sanlian University Hefei China College of Computing and Information Technologies National University Manila Philippine

Customer resource is an important lifeline for the survival and development of enterprises. In the context of the rapid expansion of China’s automobile sales market, with the deepening and refinement of enterprise marketing concepts, it is crucial for automobile enterprises to fully use customer consumption behavior data to mine valuable information and customize retention measures for potential lost customers. This paper takes the open dataset of auto dealer customer churn as the research object, and analyzes and models it from the perspective of business intelligence. First, data analysis (DA) and visualization methods are used to analyze and process the dataset; Then, for the problem of sample imbalance, authors use 6 sampling techniques to balance, such as SMOTE oversampling and SMOTEENN, SMOTETomek comprehensive sampling techniques to deal with it, and uses machine learning models, such as Decision Tree, Logical Regression, XGBoost, AdaBoost and other algorithms for modeling and analysis. The authors compare the models according to Recall and AUC values, and concludes that XGBoost is the optimal prediction model. The results show that the Recall and AUC of the model prediction results based on this dataset reach 0.926 and 0.842 respectively, which can help automobile enterprises effectively identify the lost customers. On the other hand, this study can also help auto enterprises customize retention measures for potential lost customers.

关键词： Analytical models Machine learning algorithms data visualization Machine learning Predictive models Prediction algorithms Loss measurement

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modeling and control of PANTHERA Self-Reconfigurable Pavement Sweeping Robot under Actuator Constraints

Modeling and Control of PANTHERA Self-Reconfigurable Pavemen...

引用

IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Rayguru, Madan Mohan Elara, M. R. Hayat, A. A. Ramalingana, B. Roy, Spandan Delhi Technol Univ Dept Elect Engn Delhi India Singapore Univ Technol & Design Engn Prod Dev Pillar Singapore Singapore Int Inst Informat Technol Hyderabad IIIT H Robot Res Ctr Hyderabad India

ISBN: (纸本)9781665417143

The focus of this paper is (i) to derive a suitable dynamic model for a self-reconfigurable pavement sweeping robot PANTHERA and (ii) to design a robust controller for the same to tackle uncertainties stemming from the reconfiguration process, external disturbances and from actuator saturation. To meet the first objective, an Euler-Lagrangian dynamic model is proposed to incorporate the effects of configuration changes on the system dynamics. Based on this model, the second objective is met via designing a singular perturbation based robust controller which can tackle the aforementioned uncertainties without violating the actuation limits. To circumvent the vulnerability toward actuator saturation, the proposed controller is built on contraction theory, which, compared to a conventional Lyapunov theory based design, allows to improve closed-loop tracking performance without reducing the singular perturbation parameter. Experimental results on the PANTHERA reconfigurable robot validate the effectiveness of the proposed controller over the state of the art.

关键词： Actuators Uncertainty System dynamics Perturbation methods process control Stability analysis Mobile robots

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analysis of Various Machine Learning Approaches for Predicting Sun Irradiation Levels

Analysis of Various Machine Learning Approaches for Predicti...

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IEEE International conference on Power Electronics, Intelligent control and Energy Systems (ICPEICES)

作者： Priyanshu Tomar Anurag Yadav Samiksha Bhatt Priyanka Sharma Department of Mathematics School of Allied Science Dev Bhoomi Uttarakhand University Dehradun

ISBN: (数字)9798350387193

ISBN: (纸本)9798350387209

The present paper examines how well various machine learning approaches predict solar irradiation levels. Applications like solar energy generation and climate modeling rely on accurate predictions of sun irradiation. Several machine learning approaches, such as Gaussian process Regression (GPR), Artificial Neural Network (ANN), Decision Tree (DT), Linear Regression (LR), and Support Vector Machine (SVM), are investigated and compared in the present study. The investigation entails comparing the approaches' predicted accuracy and assessing their effectiveness using historical data on solar irradiation for the Dehradun region of India (30°19'27.95"N, 78°2'2.11 “E). Also, this shows how well each method scales and how efficient it is computationally, with reference to the lower error in sun irradiance prediction, especially for the GPR technique, as the root mean square error (0.797098637), mean square error (0.635366237), mean absolute error (0.430421925), and regression value (0.999992228).

关键词： Support vector machines Radiation effects Analytical models Accuracy Machine learning Artificial neural networks Predictive models Sun Forecasting Meteorology

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Hierarchical Deep Learning for Intention Estimation of Teleoperation Manipulation in Assembly Tasks

Hierarchical Deep Learning for Intention Estimation of Teleo...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Mingyu Cai Karankumar Patel Soshi Iba Songpo Li Department of Mechanical Engineering University of California Riverside CA USA Honda Research Institute San Jose CA USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In human-robot collaboration, shared control presents an opportunity to teleoperate robotic manipulation to improve the efficiency of manufacturing and assembly processes. Robots are expected to assist in executing the user’s intentions. To this end, robust and prompt intention estimation is needed, relying on behavioral observations. The framework presents an intention estimation technique at hierarchical levels i.e., low-level actions and high-level tasks, by incorporating multi-scale hierarchical information in neural networks. Technically, we employ hierarchical dependency loss to boost overall accuracy. Furthermore, we propose a multi-window method that assigns proper hierarchical prediction windows of input data. An analysis of the predictive power with various inputs demonstrates the predominance of the deep hierarchical model in the sense of prediction accuracy and early intention identification. We implement the algorithm on a virtual reality (VR) setup to teleoperate robotic hands in a simulation with various assembly tasks to show the effectiveness of online estimation. Video demonstration is available at: https://***/CMYDgcI4j1g.

关键词： Solid modeling Accuracy Estimation process control Virtual reality Predictive models Robot sensing systems

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analysis and design of graduation design management system based on des encryption algorithm 4

Analysis and design of graduation design management system b...

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4th International conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2021

作者： Guangyong, Liu Ruolan, Li Tianjin University of Technology and Education School of Information Technology and Engineering Tianjin China Tianjin University of Technology and Education College of Foreign Languages Tianjin China

ISBN: (纸本)9781665415965

This paper focuses on the analysis of the System Use Case Model and business process logic by using software engineering methods and UML modeling tools. In the system design stage, role-based access control (RBAC) is introduced to associate roles and permissions with the full consideration of the system's compatibility and scalability. In terms of security design, by consulting the DES encryption process, the extended permutation and S-box transformation function in the Feistel algorithm are used to encrypt and decrypt sensitive system data. © 2021 IEEE.

关键词： Cryptography

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1st conference of the European Association on Quality control of Bridges and Structures, EUROSTRUCT 2021

1st Conference of the European Association on Quality Contro...

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1st conference of the European Association on Quality control of Bridges and Structures, EUROSTRUCT 2021

ISBN: (纸本)9783030918767

The proceedings contain 161 papers. The special focus in this conference is on European Association on Quality control of Bridges and Structures. The topics include: Monitoring-Based Decision Support System for Risk Management of Bridge Scour;BIM Solutions for Existing Bridges Management;derivation of Fragility Curves for the Seismic Vulnerability Assessment of Railway Masonry Arch Bridges;analytical Modelling of Transmission and Anchorage Length in Corroded Pre-Tensioned Concrete Elements;zinc Spray Galvanizing: Technological Improvement in the Arc-Spray Technology, New Zn Alloys. Thermal Spraying process for a Long-Lasting Life of Steel Against Corrosion;Innovative Technologies for Structural Health Monitoring of SFTs: Combination of InfraRed Thermography with Mixed Reality;KPI for Bridge Management. A First Step for Bridge Digitation;technical Risks and, Intervention and Mitigation Actions in Bridges. A Technical Management Strategy;digitalization processes and Bridge Information modeling for Existing Bridges;On-Site Corrosion Characterization of 50-Year-Old PC Deck Beams;diagnostics and Evaluation of Bridge Structures on Cogwheel Railway;probabilistic and Semi-probabilistic Analyses of Bridge Structures - Multi-level Modelling Based Assessment of Existing Structures;Field Investigation on the Reinforcing Steel Corrosion of RC Infrastructures in Abruzzo;virtual Investigation of Masonry Arch Bridges: Digital Procedures for Inspection, Diagnostics, and data Management;The Role of Non-linear Finite Element Modelling in Practical Safety Assessments of Structures and Suitable Safety Formats for NLFEM;Residual Structural Performance of Existing PC Bridges: Recent Advances of the BRIDGE|50 Research Project;Nonlinear Structural analysis of PC Bridge Deck Beams;Non Destructive Testing and Model Validation of Corroded PC Bridge Deck Beams.

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2021 25th International conference on Methods and Models in Automation and Robotics, MMAR 2021

2021 25th International Conference on Methods and Models in ...

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25th International conference on Methods and Models in Automation and Robotics, MMAR 2021

ISBN: (纸本)9781728173801

The proceedings contain 67 papers. The topics discussed include: the use of counting peaks method for the purpose of smoothing filtering efficiency assessment in analysis of electroencephalography data;incremental 3D maps server based on feature matching for multi-robot systems;internal model-based lateral and longitudinal control for autonomous electric vehicles;analysis of microphone use for perception of autonomous vehicles;traffic lane-changing modeling and scheduling with game theoretical strategy;continuous-time model predictive control with disturbances compensation for a glass forehearth;accuracy analysis of the fractional order, positive, state space model of heat transfer process;and generalized proportional integral observer approach for trajectory tracking control of autonomous underwater vehicles.

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Macroscopic Dynamic modeling of Metabolic Shift to Lactate Consumption of Mammalian Cell Batch Cultures

Macroscopic Dynamic Modeling of Metabolic Shift to Lactate C...

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International conference on control, Decision and Information Technologies (CoDIT)

作者： Guilherme A. Pimentel Laurent Dewasme Fernando N. Santos-Navarro Adrien Boes François Côte Patrice Filée Alain Vande Wouwer Systems Estimation Control and Optimization Group University of Mons Mons Belgium Biotechnology Department CER Groupe Aye Belgium

A macroscopic model that considers the shift to lactate consumption is proposed to simulate the therapeutic proteins produced by mammalian cells using human embryonic kidney 293 cells (HEK293-6E) cultures. The macroscopic model contains four macroscopic reactions: (i) substrate consumption and lactate production, (ii) lactate consumption, (iii) biomass death, and (iv) viable biomass maintenance. The maximum likelihood principal component analysis has been used to extract the number of reactions from experimental data collected in four batch experiments. The model parameters and confidence intervals are obtained via nonlinear least-squares identification. The model successfully predicts the dynamic behavior of cell growth and death, substrate consumption (glucose and glutamine), lactate production and consumption, and protein production. In addition, the proposed model structure is also validated as a generalized representation of the mammalian cell cultures that do not present lactate consumption.

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Investigation on Human-Centric Security Based on Understanding the Role of User Behavior in Information Security

Investigation on Human-Centric Security Based on Understandi...

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Electronics and Devices, Computational Science (ICEDCS), International conference on

作者： Lihua Wang Dongying Vocational Institute Dongying China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

Human Health Information Exchange (HHIE) provides significant benefits to patient assistance, including faster coordinated treatment and higher-quality healthcare. The Office of the National Coordinator (ONC) for Health Information Technology is looking for patient-centric HHIE ideas that can assist shift ownership of information from suppliers to patient. The current system confronts significant challenges to patient-centric HHIE, including privacy and security issues, inaccurate data, and delayed access to relevant records across several medical centres. To ensure accountability and integrity, we suggested a decentralised EMR management (DPEM) Structure based on methods of blockchain. With the following objectives in mind, we suggest a four-layer layout for DPEM: data preparation, data exchange, data storage, and access control/security. (i) We suggest a new elliptic curve-based content extraction signature (EC-CES) that allows patients to filter out sensitive EMR data, hence eliminating privacy information leakage during the data sharing process and ensuring privacy in DPEM. (ii) Blockchain smart contracts are utilised to specify the patients' specified Permissions for access, enabling safe data sharing. (iii) In order to provide secure storage, we store the actual EMRs in a cloud facility. The corresponding indexes of the EMRs are stored on consortium blockchain, which simultaneously optimises data leakage from the EMRs and ensures the integrity of the EMRs. (iv) We created a ciphertext-policy attribute-based encryption (CP-ABE) access control strategy to allow data owners to protect cloud storage while granting access to authorised people via an encrypted link to the cloud for storage with restricted access rules disabled. This enabled control of entry in data sharing. Finally, the security study demonstrates that DPEM is the most effective method of achieving safe data exchange for EMR. We carried out a thorough simulation of this patient-centered HHIE procedu

关键词： data privacy Cloud computing Technological innovation Smart contracts Medical services Stability analysis Robustness data models Blockchains Secure storage

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