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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Culita, Janetta Stefanoiu, Dan Nica, Andreea-Maria University 'Politehnica' of Bucharest Department of Automatic Control and Systems Engineering Romania University 'Politehnica' of Bucharest Faculty of Automatic Control and Computers Romania

ISBN: (纸本)9798350311402

The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classical ARMAX model by applying Hammerstein polynomials on input, output, and noise signals. Identification of models was performed by means of Multi-Step Least Squares Method, as described into the article. The simulations on a real-world plant, namely ASTANK2, a fluidic system with two inputs, two outputs and nonlinear static characteristic, have proven that the HARMAX model performs better than the BJ model and provides more accurate useful models to be integrated into closed loop configurations. © 2023 IEEE.

关键词： Optimization

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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第02期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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STGNN: a new self-trained generalized neural networks task space control for robot manipulators

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Neural Computing and Applications 2025年 1-26页

作者： Elmogy, Ahmed Elawady, Wael El-Ghaish, Hany Computer Engineering Department Prince Sattam Ibn Abdelaziz University Alkharj16273 Saudi Arabia Computers and Automatic Control Department Faculty of Engineering Tanta University Tanta31527 Egypt

The inherent uncertainties in the dynamic and kinematic parameters of robot manipulators pose significant challenges for their control in task space. This paper introduces an innovative adaptive sliding mode control strategy, leveraging self-trained generalized neural networks to enhance the precision and robustness of robot manipulator control. The proposed framework called STGNN integrates deep neural networks for the real-time estimation and adjustment of dynamics’ and kinematics’ parameters. Key contributions of this work include the development of semi-supervised learning models for adaptive dynamics and kinematics estimation. By training the generalized neural network on different trajectories, the same models can be utilized to operate on a variety of tasks, significantly improving the robustness, scalability, and adaptability of the control system. The STGNN approach allows the models to leverage both labeled and unlabeled data, incorporating a self-training mechanism that enhances their ability to generalize and adapt to diverse operational scenarios. This capability is particularly beneficial for real-time applications, where the ability to learn and adapt on the fly is crucial. Simulation results demonstrate the superior performance of the STGNN framework in controlling robot manipulators in operational space, showcasing its potential for real-world applications. The proposed method significantly advances the adaptability, accuracy, and efficiency of robot control systems, offering notable improvements over conventional approaches. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Self adjusting control systems

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Learning control laws in simulated environments for motion gestures of humanoid robots 24

Learning control laws in simulated environments for motion g...

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24th International Conference on control systems and Computer Science, CSCS 2023

作者： Mateescu, Andrei Stefan, Ioana-Livia Popescu, Dragos Constantin Sacala, Ioan Stefan Raileanu, Silviu University Politehnica of Bucharest Automatic Control and Systems Engineering Faculty of Automatic Control and Computers Splaiul Independentei No. 313 Bucharest060042 Romania University Politehnica of Bucharest Automation and Industrial Informatics Faculty of Automatic Control and Computers Splaiul Independentei No. 313 Bucharest060042 Romania

ISBN: (纸本)9798350313390

This article presents a way to implement a collection of fitness moves on an iCub (Cognitive Universal Body) robot, whose objective is to act as a fitness instructor and interact with humans. Due to the advantages of a simulation medium, the robot is simulated in the Gazebo simulator, on The Construct online platform. The control is done using Robot Operating System (ROS) with PID controllers for the robot joints, with the proportional, integral and derivative parameters tuned using a Genetic Algorithm. The scripts for the collection of moves and the algorithm used to tune the PID controllers are written in Python. © 2023 IEEE.

关键词： Python

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Pneumonia Detection from X-ray Images Using Convolutional Neural Networks 24

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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24th International Conference on control systems and Computer Science, CSCS 2023

作者： Dediu, Viorel Udrea, Andreea Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia. © 2023 IEEE.

关键词： Convolution

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Integrating Blockchain Technology in a Cyber Physical System to Secure Data 24

Integrating Blockchain Technology in a Cyber Physical System...

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24th International Conference on control systems and Computer Science, CSCS 2023

作者： Beatrix-May, Balaban Stefan, Sacala Ioan Alina-Claudia, Petrescu-Nita Razvan, Nita Politehnica University of Bucharest Faculty of Automatic Control and Computers Department of System Engineering Romania

ISBN: (纸本)9798350313390

Considering the constant growth and evolution of technology, being able to secure data is a challenge. This is why researchers find this a top research topic. Cyber-Physical systems are complex, large-scale systems that can be found in domains like healthcare, transportation, industrial controls systems or smart grids. Having many components that interact with each other, we can observe here the challenge in maintaining a secure environment for the data as data tampering or data extraction can occur, for example, in the actual transportation of data from one device to another. The main focus of this paper is to give an answer if blockchain technology provides a solution in building a secure network. We give a short review of the related work regarding blockchain integration in large-scale systems like Cyber-Physical systems. It was also briefly analyzed the layered structure of a blockchain and discussed some solutions for each layer. We then discussed about consensus algorithms for validation and authentication process. In general, consensus algorithms are implemented to assure the validation process of the nodes in a network. In this paper we tried to analyze and propose a model that offers an extra layer of security by adding the authentication step. In this way, the nodes that are validated are also considered trusted nodes in the network. © 2023 IEEE.

关键词： Blockchain

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Real-Time Notifier for Blockchain Events 22

Real-Time Notifier for Blockchain Events

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22nd RoEduNet Conference: Networking in Education and Research, RoEduNet 2023

作者： Tanase-Paris, Cristian Carabas, Costin Tapus, Nicolae University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (纸本)9798350393651

Blockchain technology gained much traction in the last few years. These decentralized databases offer security, immutability, and scalability across various applications. Decentralized applications generate vast amounts of data, known as events, that are recorded on the blockchain and are public to anyone. Some people may see opportunities for financial gains in these events and would like to know when they occur. This paper proposes a solution to process and deliver those events as real-time alerts to the users. It uses existing technologies such as message queues, multithreading, and asynchronous processing and integrates them into a scalable architecture. The results we achieved in this paper show that for an evenly distributed network traffic, which does not entirely consists of transaction bursts, the proposed solution offers reliability, efficiency, and a suitable delivery time to those wishing to integrate it into their projects. With time, this solution, or improved architectures, may form the basis of the following big-data architectures for processing blockchain events. © 2023 IEEE.

关键词： Blockchain

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A Distributed automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem 22

A Distributed Automatic Domain-Specific Multi-Word Term Reco...

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22nd International Symposium on Parallel and Distributed Computing, ISPDC 2023

作者： Truica, Ciprian-Octavian Istrate, Neculai-Ovidiu Apostol, Elena-Simona University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (纸本)9798350341270

automatic Term Recognition is used to extract domain-specific terms that belong to a given domain. In order to be accurate, these corpus and language-dependent methods require large volumes of textual data that need to be processed to extract candidate terms that are afterward scored according to a given metric. To improve text preprocessing and candidate terms extraction and scoring, we propose a distributed Spark-based architecture to automatically extract domain-specific terms. The main contributions are as follows: (1) propose a novel distributed automatic domain-specific multi-word term recognition architecture built on top of the Spark ecosystem;(2) perform an in-depth analysis of our architecture in terms of accuracy and scalability;(3) design an easy-to-integrate Python implementation that enables the use of Big Data processing in fields such as Computational Linguistics and Natural Language Processing. We prove empirically the feasibility of our architecture by performing experiments on two real-world datasets. © 2023 IEEE.

关键词： Ecosystems

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SEMANTIC PERCEPTION OF MEANING IN BRAIN

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2023年第3期85卷 37-48页

作者： Riciu, Ionela Dobrescu, Radu Faculty of Automatic Control and Computers Systems Engineering University of Bucharest Romania Systems Engineering field Faculty of Automatic Control and Computers University of Bucharest Romania

This paper highlights the relationship between the notions of meaning and respectively the semantic notion of qualia as they appear in cybersemiotic models of information transmission. The research work proposes a new way to model the perception of meaning in brain, based on an original cybernetic aproach of the relation between information structures and information messages at the level of brain’s neuronal networks. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Semantics

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control of Blood Glucose Level in Diabetics: A Simulation and Comparison Study 5th

Control of Blood Glucose Level in Diabetics: A Simulation an...

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5th International Conference on Electrical engineering and control Applications, ICEECA 2022

作者： Ikram, Touitou Salim, Ziani Faculty of Engineering University of Constantine 1 Constantine Algeria Laboratory of Automatic Robotic and Control Systems Constantine Algeria

ISBN: (纸本)9789819700448

The goal of this research is to determine how to lower blood glucose levels when the pancreas is unable to produce the insulin that plays a key part in lowering blood glucose levels. A Bergman’s model of type 1 diabetes was considered and implemented in MATLAB-SIMULINK environment. This study aims to create a monitoring system that can track glucose level. Fuzzy inference system of Mamdani type and a PID controller are utilized to optimize the control of blood glucose levels to normal levels. Initially, MATLAB is used to create the process mathematical model. Then, the system is controlled using PID and fuzzy logic controllers, respectively. Finally, the outcomes of simulations reveal that the fuzzy logic controller (FLC) outperforms the PID controller. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Three term control systems

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