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Real-Time Cyber-Physical Risk Management Leveraging Advanced Security Technologies 9th

Real-Time Cyber-Physical Risk Management Leveraging Advanced...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Poonia, Ramesh Chandra Upreti, Kamal Alapatt, Bosco Paul Jafri, Samreen Christ Univ Dept Comp Sci Ghaziabad India Imam Abdulrahman Bin Faisal Univ Adm Sci Dept Dammam Saudi Arabia

ISBN: (纸本)9789819745807;9789819745814

Conducting an in-depth study on algorithms addressing the interaction problem in the fields of machine learning and IoT security involves a meticulous evaluation of performance measures to ensure global reliability. The study examines key metrics such as accuracy, precision, recall, and F-1 scores across ten scenarios. The highly competitive algorithms showcase accuracy rates ranging from 95.5 to 98.2%, demonstrating their ability to perform accurately in various situations. Precision and recall measurements yield similar information about the model's capabilities. The achieved balance between accuracy and recovery, as determined by the F1 tests ranging from 95.2 to 98.0%, emphasizes the practical importance of data transfer in the proposed method. Numerical evaluation, in addition to an analysis of overall performance metrics, provides a comprehensive understanding of the algorithm's performance and identifies potential areas for improvement. This research leads to advancements in the theoretical vision of machine learning for IoT protection. It offers real-world insights into the practical use of robust models in dynamically changing situations. As the Internet of Things environment continues to evolve, the study's results serve as crucial guides, laying the foundation for developing strong and effective security systems in the realm of interaction between virtual and material reality.

关键词： Machine learning IoT security Performance metrics Accuracy Precision

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Control of Respiratory Ventilators Using Boussignac Valve 12th

Control of Respiratory Ventilators Using Boussignac Valve

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Szkulmowski, Zbigniew Grzelak, Slawomir Joachimiak, Michal Meszynski, Sebastian Schiller, Marcin Sokolov, Oleksandr Home Ventilat Ctr Specialized Med Care Bydgoszcz Poland Nicolaus Copernicus Univ Torun Poland Antoni Jurasz Univ Hosp 1 Bydgoszcz Poland

ISBN: (纸本)9783031602177;9783031602184

The aim of this study was modelling and computer simulation of the ventilator control system in the pressure-controlled ventilation (PCV) model with the use of the Boussignac valve and the construction of a prototype of such a ventilator. The simulation model was based on Matlab/Simulink model of Medical Ventilator with Lung Model. This model is a nonlinear systemwith a fuzzy Takagi-Sugeno rule base model. A program interface was developed for simulating the operation of ventilator in the PCV mode on-line and to change the mechanical parameters of the lung - resistance and compliance.

关键词： lung simulation Boussignac control fuzzy logic

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Quantum Annealing as a Chemical Kinetics Solver for Pollutant Transport Models 16th

Quantum Annealing as a Chemical Kinetics Solver for Pollutan...

引用

16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Rodriguez Garrido, Juan de Dios Pujante Perez, Alejandro Illueca Fernandez, Eduardo Jara Valera, Antonio J. Libelium Lab SL Murcia 30006 Spain

ISBN: (纸本)9783031775703;9783031775710

In the past years, quantum computing has been proved to have a huge potential in a wide range of applications, such as cryptography, finance and material science, although its applicability in the world of ambient intelligence and smart cities is still under study. This paper aims to shed light on this, specifically, regarding its application in the current models for air quality and dispersion of contaminants used in pollution monitoring, which typically imply large computational costs. Among all the procedures and techniques in the field, the quantum annealing paradigm is the one that has shown a more mature state of development and seems to be the most promising solution for industrial applications at the moment, particularly excelling in optimization problems. For this reason, quantum annealing was chosen to test its capability in solving chemical kinetic problems, which usually consist in sets of coupled differential equations whose linearity depends on the complexity of the system. A simple chemical system was proposed and solved by a quantum annealer, comparing its solution to one obtained by classical methods in terms of precision, time and scalability. The study shows that these problems can be already solved by quantum computers to a certain degree of accuracy but they lack some key features to be a viable substitute for classical methods at the moment. Quantum annealing is thus positioned as a promising tool due to its scalability, only awaiting suitable hardware that enables the proper treatment of these problems.

关键词： Quantum Annealing Chemical Kinetics Air Quality Modelling Numerical Methods

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Application of Dung Beetle Optimizer Algorithm for Solving Optimization Problem in Smart Residential Power Grid 7th

Application of Dung Beetle Optimizer Algorithm for Solving O...

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7th International Conference on Green Technology and Sustainable Development

作者： Vy, Huynh Tuyet Anh, Ho Pham Huy Ind Univ Ho Chi Minh City Ho Chi Minh City Vietnam Ho Chi Minh City Univ Technol HCMUT VNU HCM Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh City VNU HCM Linh Trung Ward Ho Chi Minh City Vietnam

ISBN: (纸本)9783031762314;9783031762321

Stochastic optimization techniques have become very popular in literature. The renewable energy-connected power grid of a residential area can be considered a stochastic environment due to the intermittent nature of the renewable energy. This paper applies the dung beetle optimizer (DBO) and evaluates its effect on the energy management system (EMS) of the home power grid system. In order to improve accuracy and speed, instead of using the random method, we utilize the good node-set (GNS) method to generate the initial population for the applied algorithm. From the simulation results, the case with GNS initialization method has better performance than random method while the case of GNS method with a special candidate gives the best performance with the least cost. However, all the cases effectively meet the battery's charging and recharging needs to optimize the operating cost.

关键词： dung beetle optimizer (DBO) good node-set method energy management system (EMS) renewable energy smart-grid

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A New Model for the Arabic Language Based on the Semantic Representation of Words and Sentences 1

引用

Intelligent systems Conference (IntelliSys)

作者： Awajan, Arafat A. Princess Sumaya Univ Technol King Hussein Sch Comp Sci Amman Jordan

ISBN: (数字)9783031477188

ISBN: (纸本)9783031477171;9783031477188

We addressed, in this work, the problem of developing a new computerized model for the Arabic language. Language modeling is crucial in modern NLP applications as natural language modeling could help a machine to grasp a high understanding of human language. The proposed model is based on the contextual and semantic representation of words in this language. It is a new and robust version of Word2Vec that aims to feed NLP applications with rich word representation, which is done using three main additions to the basic Wrod2Vec model: it is built on a labeled dataset instead of using unlabeled text data, named entities are detected and then represented as independent entities from their constituents, and the context window is defined to include only the other words in the same sentence that are linked with the target word by dependency relations regardless their position in the sentence. The proposed model was tested and evaluated by assessing the similarity of semantics between the words using a dataset collected and annotated by a homemade system developed for this purpose.

关键词： Natural language modeling Semantic representation Arabic language processing and understanding

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A Nonsingular Terminal Sliding Mode Control for a 6DOF Manipulator with Unknown Payloads 7th

A Nonsingular Terminal Sliding Mode Control for a 6DOF Manip...

引用

7th International Conference on Green Technology and Sustainable Development

作者： Hai Ninh Tong Minh Huy Nguyen Hoang Lam Le Minh Tam Nguyen Duc Thien Tran Ho Chi Minh City Univ Technol & Educ Dept Automat Control Ho Chi Minh City 700000 Vietnam Ho Chi Minh Univ Technol & Educ Dept Elect & Elect Engn Ho Chi Minh City 700000 Vietnam

ISBN: (纸本)9783031762314;9783031762321

This paper presents a nonsingular terminal sliding mode control (NTSMC) for a 6-DOF manipulator with the prior unknown payloads. Firstly, the sliding mode control (SMC) is a robust nonlinear controller used to eliminate the nonlinear components and deal with uncertainties. However, the SMC gives a slow convergence time when the state variables reach the equilibrium points;therefore, a terminal sliding mode (TSM) surface is established to deal with the convergence time in finite time. On the other hand, the singularity point is the issue that existed on the TSM manifold. Hence, a nonsingular terminal sliding mode (NTSM) surface is proposed to solve the singularity phenomenon, enhance the tracking precision, and allow the system to converge in a finite time. Furthermore, the Lyapunov theory is applied to analyse and prove the stability of the proposed control. Finally, the simulation results verify the effectiveness and robustness of the proposed control algorithm against the Proportional Derivate (PD) and conventional SMC via MATLAB Simulink.

关键词： Nonsingular Terminal Sliding Mode 6-DOF Manipulator Unknown Payloads

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Review of the Deep Learning Models for Anomaly Detection-Based Video Scrutiny System 1

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4th Congress on Intelligent systems (CIS)

作者： Kukade, Jyoti Panse, Prashant Medi Caps Univ Indore India

ISBN: (数字)9789819990405

ISBN: (纸本)9789819990399;9789819990405

Video anomaly detection is a fast-growing computer vision field. Alertness and asset protection explain this. It takes a long time and may yield incorrect results to search surveillance film for illicit activity like a brawl, robbery, or wrong U-turn. High-tech, computer-controlled video surveillance systems are needed for safety. Surveillance cameras regularly capture inexplicable events. This study examines oddities using typical and uncommon video examples. We recommend using the fusion deep learning model to detect abnormalities in weakly tagged training films. Thus, training labels (anomalous or normal) are video-level, not clip-level. This saves people's time from manually marking training video oddities. We use multiple instances learning to automatically develop a deep anomaly ranking model that predicts high anomaly scores for strange video segments. Our method learns a deep anomaly ranking model that predicts high anomaly scores for video segments that deviate from the norm (fusion deep learning model). To help identify anomalies, we add sparsity and temporal smoothness constraints to the ranking loss function during training. We did this to improve data ranking. Their method can be applied in a near-real-time context. Our methodology works for anomaly detection-based video surveillance.

关键词： Deep learning Anomaly detection Video surveillance system

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A Graph-Based Approach for Searching and Visualizing of Resources and Concepts in Data Science 12th

A Graph-Based Approach for Searching and Visualizing of Reso...

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Morales-Quezada, David Chicaiza, Janneth Univ Tecn Particular Loja Dept Ciencias Computac Loja Ecuador

ISBN: (纸本)9783031602207;9783031602214

The paper presents a resource search and visualization approach for learning data science fundamentals. We implement a web prototype that uses a knowledge graph built from the topics of the domain and a metadata repository of resources related to these topics. The application allows the graphical and interactive visualization of the graph and its semantic relationships, as well as the exploration, search, and visualization of concepts and resources. The results of the preliminary validation show its potential to improve the understanding of data science topics and promote free access to educational resources such as datasets, notebooks, and multimedia material.

关键词： Learning data science knowledge graphs search engine visualization of educational resources

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The Impact of Islamic Resilience on Student Spirituality While Engaging in Digital Activities 9th

The Impact of Islamic Resilience on Student Spirituality Whi...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Suud, Fitriah M. Salsabillah, Wahyu Thalia Univ Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9789819735587;9789819735594

Islamic resilience in digital activities is the ability of endurance and toughness that is inherent in a person's spirituality to be able to overcome challenges in digital activities and be resistant to the influence of social media. This research aims to examine the Islamic resilience of high school students to protect themselves during digital activities. The method for collecting data is carried out through in-depth interviews with previously determined respondents, observing digital activities and Islamic resilience activities of students, as well as collecting data through track records of activities through documentation. The informants in this research were students, teachers, and school principals. The research results show that in digital activities, students use their gadgets more to search for the latest information, play online games, and use them to search for learning materials. To protect themselves from the tendency to be involved in negative digital activities, students carry out prayer activities, recite, and listen to the Qur'an. Teachers also take on the role of helping students strengthen their Islamic resilience through digital activities and positive activities at school. This research finds the connection between digital resilience elements and increasing Islamic resilience for digital Muslim teenagers.

关键词： Islamic resilience Digital resilience Digital activities School Student

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Comparative Analysis of Neural networks and Data Processing Techniques for Parkinson's Gait Classification

Comparative Analysis of Neural Networks and Data Processing ...

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Intelligent systems Conference

作者： Reyes, Israel Andaluz, Francis Troya, Kerly Zhinin-Vera, Luis Almeida-Galarraga, Diego Cadena-Morejon, Carolina Tirado-Espin, Andres Villalba-Meneses, Santiago Guevara, Cesar Yachay Tech Univ Sch Biol Sci & Engn Urcuqui 100119 Ecuador Univ Castilla La Mancha LoUISE Res Grp Albacete 02071 Spain Yachay Tech Univ Sch Math & Computat Sci Urcuqui 100650 Ecuador Univ Int La Rioja Sch Engn & Technol Logrono 26006 Spain Univ Tecnol Indoamer Ctr Invest Mecatron & Sistemas Interact MIST Quito 170103 Ecuador MIND Res Grp Model Intelligent Networks Dev Urcuqui Ecuador

ISBN: (纸本)9783031663352;9783031663369

Parkinson's disease (PD) is an advancing neurodegenerative condition characterized by motor symptoms, including disturbances in gait and varying degrees of severity, typically assessed using the Hoehn and Yahr stages. Precise classification of PD gait patterns and severity levels is of paramount importance for efficient diagnosis and continuous treatment monitoring. This research article presents a comprehensive assessment of the performance of three distinct Artificial Neural Network (ANN) models integrated with diverse data processing techniques, encompassing segmentation, filtration, and noise reduction, in the context of classifying PD severity. The classification is based on the vertical ground reaction force (VGRF) measurements obtained from both healthy individuals and those afflicted by Parkinson's disease, sourced from a well-established database (GaitPDB, Physio Net). The study provides a comparative analysis of the efficacy of these models in accurately discriminating between various gait patterns and stages of disease severity, underscoring their potential to enhance clinical decision-making and patient care. Additionally, the study offers valuable insights into the impact of data processing methodologies on classification performance.

关键词： Parkinson's disease Gait analysis Artificial Neural Network Classification Hoehn Yahr

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