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Deployment of Safety Predictive Analytics to Prevent Workplace Incidents and Promote Event Reduction: A Machine Learning Approach Towards a data-Driven Safety System

Deployment of Safety Predictive Analytics to Prevent Workpla...

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International conference on Digital data processing (DDP)

作者： Ait Lamkademe Hajar Naddami Ahmed Choukri Karim Laboratory of Advanced Research in Industrial and Logistics Engineering National Higher School of Electricity and Mechanics Hassan II University Casablanca Morocco EEIS Laboratory ENSET Mohammedia Hassan II University Casablanca Morocco

With the ongoing era of digitization and the ability to bring together huge data sets, there is enormous potential for many industries and business functions to take advantage of their “big data” sets by performing advanced analytics, allowing managers to make business decisions. When applied correctly, predictive analytics allow organizations to gain deep insight into their business and deploy their scarce resources in an optimal way (Predictive Solutions, 2012). Thus, improving safety in workplaces is no exception to using predictive analysis to predict and prevent events in real-time. Increasing process safety entails lowering the likelihood that hazardous environments may have negative effects. Unfortunately, it is impossible to measure the probability factor directly. The absence of an accident does not provide helpful information because Target Zero cannot be accomplished until the hazard is eliminated. On the other hand, numerous cause elements that could have been better monitored and controlled are discovered after a significant accident occurs. In this paper, we advocate for a proactive, dynamic system by embedding predictive analysis into two process stages. At the design stage, we suggest a predictive modeling process: 1. Define goals 2. Collect and preprocess data 3. Address missing data through data imputation 4. Build candidate predictive models 5. Train, test and cross-validate candidate models 6. Select “the best” models based on multiple evaluation metrics 7. At runtime, consume the predictions from selected predictive models using the end-user interface. Depending on the data input and the time it takes for learning algorithms to learn, we claim the system can predict future potential input variables for the system in a single model and proactively adjust to meet intermediate and longterm goals and safety needs. A subset of data supports the proposal through in-sample validation. The validation through simulation was done based on actual data extr

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Model of Dependence of Zone Gain from Technological Parameters of Multizone Heating Furnace Using Regression and Neural networks

Model of Dependence of Zone Gain from Technological Paramete...

引用

International conference on control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Andrey Fomin Nikita Savostin Petr Zhukov Automated and Information Control Systems Department Stary Oskol Technological Institute n.a. A.A. Ugarov (Branch) NUST "MISIS" Stary Oskol Russia

The general purpose of this study is to investigate the technological data collected during the operation of a multizone heating furnace by an automated control system (ACS). The certain aim is to develop a mathematical model that reflects the dependence of the gain of a multizone furnace zone on a number of other technological parameters collected during the operation of the plant. Among such parameters we consider: the position of the fume exhauster damper, underpressure in the breeching pipe of the fume exhauster, the average time that the billets spend in the furnace zones and others. It is found that the data taken from the operating process facilities have a shifted asymmetric unimodal distribution with a "heavy" tail. This distribution is characterized by a large number of values, which are considered as outlier values by parametric methods of analysis. This fact does not allow applying parametric regression models and estimating their accuracy. Then we studied the applicability of neural networks to design the required model. A promising result is obtained using classical neural networks.

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An Improved PID control Method Based on the Kalman Filter Algorithm

An Improved PID Control Method Based on the Kalman Filter Al...

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Advances in Electrical Engineering and Computer Applications( AEECA), 2020 IEEE International conference on

作者： Jihong Yan Wentao Wang Zhongyi Gou Yizhan Huang Mengxu Ren Zhihao Yan Xuechao Wang Jianping Meng Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350355260

With the increasing demand for high-tech equipment, the need for reliable power supplies has grown, making the stability and accuracy of power supplies particularly critical. In the industrial sector, PID (Proportional-Integral-Derivative) control is the most commonly used method. However, white noise in the power supply and overshoot during system startup can cause instability in traditional PID controllers. To address this issue, this paper proposes a method to enhance the stability and accuracy of power supply output voltage by combining PID controllers with the Kalman filtering algorithm. The Kalman filter is used to process input errors by filtering. Based on the system’s dynamic and measurement models, the Kalman filter provides an optimal estimate of the system state through predictions and updates of measurement data. Simulation results demonstrate that the Kalman filtering algorithm effectively reduces measurement errors and noise, mitigating output instability caused by process noise and significantly improving the performance and stability of the PID controller.

关键词： PI control Accuracy Power supplies Computational modeling Filtering algorithms White noise Stability analysis Kalman filters PD control Voltage control

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Research on Dynamic Calculation of Passenger Flow in Urban Rail Network Basd on the Coupling Model of Passenger Flow and Train Operation*

Research on Dynamic Calculation of Passenger Flow in Urban R...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Wenqi Ying Liang Ma Xi Li School of Information Science & Technology Southwest Jiaotong University Chengdu China Sichuan Engineering Research Centre of Train Operation Control Technology Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In the operation process of urban rail transit network, it is necessary to grasp the dynamic changes in passenger flow and calculate the real-time passenger flow of the line network during future operation periods, so as to provide real-time passenger flow data support for dynamic operation management and control. In order to better describe the interaction between train operation and passenger flow, the weighted-edge network topology diagram of urban rail network is established firstly. Based on the data of automatic fare collection system (AFC), a dynamic Origin-Destination(OD, the starting and ending points of a passenger's journey) matrix is built, and the Dijkstra algorithm is used to simulate the path selection process of the passengers, the link relationship, and the OD decomposition of passenger flow is carried out based on the train operation. Then, dynamic analysis is conducted on the platform passenger flow and cross-section passenger flow to obtain the dynamic change patterns of inbound passenger flow, outbound passenger flow. Then the dynamic analysis of platform passenger flow and cross-section passenger flow is carried out to obtain relationship between micro indicators such as inbound passenger flow, outbound passenger flow, boarding passenger flow, dewll passenger flow and alighting passenger flow. Based on the interactive relationship between passengers and train operation, the dynamic calculation model of passenger flow of rail transit network is constructed based on the coupling model between passenger flow and train operation, and the platform passenger flow and cross-section passenger flow are calculated. Finally, the feasibility of the model is verified using an actual subway network of China as an example.

关键词： Rails Couplings Heuristic algorithms Computational modeling Urban areas process control Predictive models data models Real-time systems Public transportation

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Performance simulation analysis of new train control system safety communication protocol based on Matlab/SimEvents 5

Performance simulation analysis of new train control system ...

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2022 5th International conference on Power Electronics and control Engineering, ICPECE 2022

作者： Jing, Zhiqiang Li, Kaicheng Wei, Guodong Liu, Yu School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Collaborative Innovation Center of Railway Traffic Safety National Engineering Research Center of Rail Transit Operation Control System Beijing Jiaotong University Beijing100044 China

The vehicle-ground safety communication of the New Train control System adopts a brand-new underlying network and a communication mechanism of safe and reliable transmission. Based on the GPRS packet switching network, the data link layer adopts the PPP protocol, and the TCP protocol is adopted in the transmission layer to provide reliable transmission services. According to the GPRS network service quality index and the retransmission mechanism of the TCP protocol in the transport layer, this paper adopts the Matlab/SimEvents discrete event simulation method and uses the entity as the communication carrier to conduct a hierarchical and modular system-level modeling of New Train control System vehicle-ground communication protocol. It simulates the communication process of the message from the application layer, the security layer to the transport layer, and finally transmitted on the GPRS network channel with random delay and packet loss probability. From the quantitative point of view, this paper analyzes the safety connection establishment time and success rate of the new train control system vehicle-ground wireless communication under different channel conditions, the timeliness of the non-periodic message receiving a reply to complete the specific scene function, and the reliability of the periodic message receiving delay. The analysis results show that the new train control system vehicle-ground wireless communication adopts GPRS network and TCP protocol retransmission mechanism to improve the real-time and reliability of communication. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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Privacy risk analysis and metrics in capturing and storing network traffic

Privacy risk analysis and metrics in capturing and storing n...

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International conference on control Systems and Computer Science (CSCS)

作者： Michele Mastroianni Francesco Palmieri Massimo Ficco Rafał Kozik Michał Choraś Dipartimento di Informatica Universitá degli Studi di Salerno Via Giovanni Paolo II Fisciano (SA) Italy Bydgoszcz University of Science and Technology Bydgoszcz Poland

Network traffic analysis is a process of paramount importance to monitor network availability and operational activity, identify anomalies, maximize performance, find threats, and detect attacks. Due to this fact, in everyday work network managers need to capture, analyze and store a tremendous amount of data which can definitely be classified as ”Big data”. On the other side, it is crucial to point out that the captured network traffic has significant privacy implications, in particular in the territorial scope of GDPR or other similar regulations because, according to GDPR, not only the payload but also the IP address of the sender and the receiver of packets have to be considered personal data. This paper deals with the privacy issues related to network traffic capture/processing/storage, the risks, and the associated mitigation techniques. As a conclusion of the work, a privacy risk analysis using PIA, together with the methodology developed by the French data Protection Authority (CNIL) is discussed. The analysis performed highlights the effect of the use of some well-known anonymization and pseudonymization techniques on the severity and likelihood of risk.

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Design and Realization of Spacecraft Test data analysis Platform 4

Design and Realization of Spacecraft Test Data Analysis Plat...

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4th IEEE Advanced Information Management, Communicates, Electronic and Automation control conference, IMCEC 2021

作者： Li, Zhongwen Liu, Ling Shen, Tiantian Hunan Normal University College of Information Science and Engineering Changsha China Hunan Normal University College of Engineering and Design Changsha China

ISBN: (纸本)9781728185347

Aiming at the characteristics of the various test data storage formats and various test data query methods in the process of spacecraft automated testing, this paper proposes a test data query and analysis platform implementation plan based on MVC, including the design of platform architecture, data query analysis modeling. The scheme can realize the decoupling of test data and query analysis business to the greatest extent, and realize the openness and flexibility of the platform. The design scheme has been implemented in actual projects, and the application effect is good. © 2021 IEEE.

关键词： Digital storage

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Enhancing Software Vulnerability Detection Using Code Property Graphs and Convolutional Neural Networks

Enhancing Software Vulnerability Detection Using Code Proper...

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Computational, Communication and Information Technology (ICCCIT), International conference on

作者： Amanpreet Singh Saimbhi

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

The increasing complexity of modern software sys- tems has led to a rise in vulnerabilities that malicious actors can exploit. Traditional methods of vulnerability detection, such as static and dynamic analysis, have limitations in scalability and automation. This paper proposes a novel approach to detecting software vulnerabilities using a combination of code property graphs and machine learning techniques. By leveraging code property graphs, which integrate abstract syntax trees, control flow graphs, and program dependency graphs, we achieve a detailed representation of software code that enhances the accuracy and granularity of vulnerability detection. We intro- duce various neural network models, including convolutional neural networks adapted for graph data, to process these rep- resentations. Our approach provides a scalable and automated solution for vulnerability detection, addressing the shortcomings of existing methods. We also present a newly generated dataset labeled with function-level vulnerability types sourced from open- source repositories. Our contributions include a methodology for transforming software code into code property graphs, the implementation of a convolutional neural network model for graph data, and the creation of a comprehensive dataset for training and evaluation. This work lays the foundation for more effective and efficient vulnerability detection in complex software systems.

关键词： Training Codes Sensitivity Computational modeling Static analysis Syntactics Software systems Software data models Convolutional neural networks

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Integrating Emotion Detection with Sentiment analysis for Enhanced Text Interpretation

Integrating Emotion Detection with Sentiment Analysis for En...

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International conference on Inventive Computing and Informatics (ICICI)

作者： Arpan Ghosh Naimish Pandey C. AshokKumar Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

The analysis of public sentiment on various social media platforms has become more important.. However, conventional sentiment analysis often struggle to capture intricate emotional nuances present in textual data.. This study proposes an innovative approach by integrating emotion detection with sentiment analysis to improve the interpretation of text.. A novel algorithm "BERT-DeepEmo" is proposed, combining the strong contextual modeling capabilities of Bidirectional Encoder Representations from Transformers (BERT) with a deep learning-based emotion recognition model (DeepEmo). Simulation analyses were performed to evaluate the effectiveness of the proposed algorithm compared to established approaches like BiLSTM-ECNN and RoBERTa-EDTA. Evaluation metrics including accuracy, precision, and mean absolute error were employed for comparison purposes. The results confirmed that BERT-DeepEmo enhances the overall quality of sentiment analysis while considering the emotional nuances in text. These findings highlight the proposed approach's potential to offer a more holistic and effective sentiment analysis framework, thereby facilitating informed decision-making and deeper insights across various applications. Future research work may explore into further integration with alternate process of emotional data, such as speech or visual inputs, to broaden the framework's applicability and efficacy.

关键词： Sentiment analysis Emotion recognition Adaptation models Visualization Accuracy Social networking (online) Bidirectional control

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45th Vibration Institute Annual Training conference 2022, VIATC 2022 and Society for Machinery Failure Prevention Technology Annual conference 2022, SMFPT 2022

45th Vibration Institute Annual Training Conference 2022, VI...

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45th Vibration Institute Annual Training conference 2022, VIATC 2022 and Society for Machinery Failure Prevention Technology Annual conference 2022, SMFPT 2022

ISBN: (纸本)9781713860570

The proceedings contain 22 papers. The topics discussed include: the practical application of signal processing;examination of the FFT batch process with calculation of the rms energy;measuring accelerance and deriving all other frequency response functions;pump curve and performance;vertical pump resonance practical finite element modeling;vibration issues when operating centrifugal pumps at off-design conditions;electrical signature analysis applications in windpower and solar update;motor faults that vibration data doesn't always detect;gas turbine vibration case study - rotor shaft crack examples;transient vibration control for condensing steam turbine using force reduction increasing damping techniques;wireless vibration monitoring as a compliment to monthly vibration rounds;and implementing industry 4.0 wireless vibration to identify rotating equipment issues, improve reliability and reduce unplanned outages.

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