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Fuzzy Logic controller for the Chemotherapy of Brain Tumor

Fuzzy Logic Controller for the Chemotherapy of Brain Tumor

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

作者： Muhammad Zubair Daniela Iacoviello Iqra Shafeeq Mughal Dept. Computer Control and Management Engineering Sapienza University of Rome Rome Italy Dept. di Ingegneria Electrica Electronica e Informatica DIEEI University of Catania Catania Italy

An advanced Fuzzy Logic controller (FLC) that considers all the states of the brain tumor system is designed for the chemotherapy treatment. A Mamdani-type FLC is proposed for dynamically controlling the chemotherapy drug for the tumor system; the chemotherapy treatment of brain tumors requires advanced strategies which mainly depend upon the severity of the tumor. In this work, the advanced FLC designed aims both at determining the amount of chemotherapy to eliminate tumor cells, and at preserving the minimum amount of healthy and immune cells. The controller's performance is verified using MATLAB software based on different control parameters, showing its effectiveness in reducing the tumor cells. It has shown favorable results in terms of steady-state error, rate of convergence, and amount of drug consumed.

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A Framework Leveraging Robotics and Machine Learning Technologies for Early Disease and Pest Detection in Greenhouse Tomato Crops

A Framework Leveraging Robotics and Machine Learning Technol...

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International Conference on control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Nikolaos Kounalakis Emmanouil Kalykakis Dimitrios Kosmopoulos John Fasoulas Michael Sfakiotakis Control Systems and Robotics Laboratory (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework.

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Improvement of Protection Factor for a controlled Laboratory computer Network Using Artificial Intelligence

Improvement of Protection Factor for a Controlled Laboratory...

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engineering, Science and Advanced Technology (ICESAT), International Conference on

作者： Raid W. Daoud Enas F. Aziz Zaki M. Abdullah Ziyaad H. Saleh Electrical Tech. Dept. Northern Technical University Kirkuk Iraq Computer Systems Dept. Northern Technical University Kirkuk Iraq Petroleum Systems and Control Dept. College of Petroleum Processes Engineering Tikrit Iraq

computer networks provide exceptional privacy, primarily for testing and other educational activities. However, the security of computer networks is an exceptionally touchy subject, mainly when applied in labs and tests for educational purposes. Any software system created on a server typically requires a username and password to access a collection of computers on a particular network. The proposed work devised and implemented a neural network feedback network with four inputs (I.P. address, MAC address, user number, and time) and an output that represents the user's acceptance or rejection. A few instances of the data and numbers needed to train the neural network include the lab's address, the student's name, the academic stage's address, etc. Good results were obtained through the company's training and education, which was tested on more than 200 models, and the response aligned with the data. No user can access the network without first being recognized by the proposed network by comparing the pre-trained data to ensure they are authorized to take the exam or enter for any other reason.

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, engineering, Science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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Improving the Efficiency of a Multistage Evaporator Station for Sugar Production Using Neural Networks 4

Improving the Efficiency of a Multistage Evaporator Station ...

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4th IEEE International Conference on Modern Electrical and Energy System, MEES 2022

作者： Zaiets, Nataliia Lutska, Nataliia Vlasenko, Lidiia National University of Life and Environmental Sciences of Ukraine Det. of Automation and Robotic Systems Kyiv Ukraine National University of Food Technologies Dept. of Automation and Computer Technologies of Control Systems Kyiv Ukraine State University of Trade and Economics Dept. of Software Engineering and Cyber Security Kyiv Ukraine

ISBN: (纸本)9798350346831

The paper shows the process of developing a model of multistage evaporator station of a sugar factory based on a neural network. The neural network predicts the main performance indicators of the multistage evaporator station, such as the concentration of syrup at the output of the evaporator and the amount of evaporated water at the station. Unlike existing solutions, forecasting is performed in real time based on a set of indicators of the automation system (temperatures, flow rates, levels, pressure, density in the apparatus) and industrial laboratory (concentration of solids at the inlet to the evaporation station). The proposed neural network model has an MLP structure with 27 inputs, 2 outputs and one hidden layer with 20 neurons and predicts these indicators with an error of less than 5%. This allows to increase the informative support of the operator-technologist on the quality indicators of the enterprise without additional load on the industrial laboratory and without additional cost automatic quality devices, as well as to perform timely adjustment of the technological mode of the department. © 2022 IEEE.

关键词： Evaporation

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Executive Conference Chair Welcome

2023 IEEE Gaming, Entertainment, and Media Conference, GEM 2...

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2023 IEEE Gaming, Entertainment, and Media Conference, GEM 2023 2023年

作者： Hogue, Andrew Cannavo, Alberto Game Development & Interactive Media Ontario Tech University Oshawa Canada Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy

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A Novel Real-Time Redundant System For Aiding Drivers To Increase Their Attention Level

A Novel Real-Time Redundant System For Aiding Drivers To Inc...

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Smart World Congress (SWC), IEEE

作者： Jacopo Sini Luigi Pugliese Pietro D’Agostino Massimo Violante Riccardo Groppo Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Sleep Advice Technologies S.r.l Turin Italy

Road accidents are a major concern worldwide. Research of technological solutions to improve road safety is an open topic, considering this issue from various perspectives. As widely reported in the literature, driver distraction is one of the most common causes of collisions. Even if vehicles are becoming safer and safer over the years, pedestrians and cyclists are still exposed to severe accidents. Major concerns about driver distraction is mobile phone use and drowsy driving. This paper proposes a virtual buddy designed to help drivers, thanks to warning sound messages, improve their attention level. The main idea is to recognize, thanks to different sources (video camera, physiological data, and interior environmental conditions) interpreted by a data-fusion algorithm, whenever there is a distracted or drowsy behavior, recalling the driver to the road. The effectiveness of the data-fusion algorithm in detecting dangerous conditions has been verified thanks to a driving simulator experimentally, obtaining no false negatives from distraction from drowsiness, a sensitivity of about 85% for the distraction caused by mobile phone usage or other activities different from focusing on driving.

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Real-time Sleep Prediction Algorithm using Commercial Off the Shelf Wearable Devices

Real-time Sleep Prediction Algorithm using Commercial Off th...

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Smart World Congress (SWC), IEEE

作者： Luigi Pugliese Massimo Violante Riccardo Groppo Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Sleep Advice Technologies S.r.l. Turin Italy

As reported by the American National Highway Traffic Safety Administration (NHTSA), sleep while driving is one of the most influential factors in fatal vehicle crashes, along with excessive vehicle speed and alcohol consumption. Physiologically speaking, driving for more than two hours in a nocturnal environment produces a driving impairment like a blood alcohol concentration of 0.05%. In this work, we present an innovative and patented sleep prediction method based on the analysis of the Autonomic Nervous System (ANS) (and its subsystems) that monitors the actions happening during the transition from awake to sleep onset. The prediction method processes the Heart Rate (HR) and the Heart Rate Variability (HRV) as collected by a wearable device on the subject wrist. Using a sliding window approach that operates on 20 seconds of samples (acquired at 1 Hz), the trend of the variance of HR and HRV is used to classify the subject condition according to a reduced Karolinska Sleepiness Scale (rKSS) that comprises five stages: Calibration, Awake, Low Drowsiness level, Medium Drowsiness level, High Drowsiness level. The prediction method has been validated experimentally using a set of recordings acquired in a realistic environment (AVL dynamic car simulator, in Graz (AT)). During the experiments, 15 subjects performed several rounds of the Maintenance Wakefulness Test (MWT). Each subject was equipped with a wearable device and apolysomnography medical equipment to gather both the data processed by the proposed approach, and the data set that constituted the ground truth under the supervision of a sleep expert medical doctor. A further experimental section has been conducted, involving the Italian truck company Chrono Express. 15 different drivers have utilized the built-up system for more than 13000 km. The proposed method is sensor agnostic, as it has been proven through preliminary activities with contactless Radio Frequency (RF) sensors. The output produced by the propos

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Study of the Influence of Rolling Modes on the Operation of Interconnected Electric Drives of a Rolling Mill 4

Study of the Influence of Rolling Modes on the Operation of ...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Tytiuk, Valerii Busher, Victor Kalinin, Alexey Chornyi, Oleksii Druzhinin, Valeriy Halushko, Dmytro Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Dept. of Electrical Engineering and Electronics National University "Odessa Maritime Academy" Odessa Ukraine Department of Informative computer systems Abylkas Saginov Karaganda Technical University NPJSC Karaganda Kazakhstan Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Department of Power Engineering Karaganda Industrial University NPJSC Temirtau Kazakhstan Dept. of Electrical Engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

ISBN: (纸本)9798350395532

The paper is devoted to study of the influence of rolling modes on the performance of powerful interconnected electric drives of a hot rolling mill under the action of an electromagnetic coupling circuit between the electric drives of the roughing and finishing groups. The action of the electromagnetic coupling circuit manifests itself in the form of the influence of impact loads of synchronous electric drives on the angular velocity of direct current electric drives of the finishing group of the mill. The parameters of the electromagnetic coupling circuit are determined by the power supply scheme and equipment parameters. Values of impact loads applied to a synchronous motor depend on the rolling process parameters, in particular, the chemical composition of the rolled steel and the temperature of the ingot. The paper presents the results of calculating the rolling power for various rolling mode parameters. Using mathematical modeling in Simulink, numerical estimates of the influence of rolling modes on the magnitude of the voltage drop in the power supply unit and the drop in the angular velocity of the electric drive of the finishing group were obtained on the example of a wide-strip hot rolling mill 1700 of ArcelorMittal Temirtau JSC. © 2023 IEEE.

关键词： Hot rolling

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Real-Time Local Map Generation and Collision-Free Trajectory Planning for Autonomous Vehicles in Dynamic Environments

Real-Time Local Map Generation and Collision-Free Trajectory...

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International Conference on control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Aristeidis Geladaris Lampis Papakostas Athanasios Mastrogeorgiou Michael Sfakiotakis Panagiotis Polygerinos TWI-Hellas Athens Greece Mechanical Engineering Dept. Control Systems and Robotics Lab (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Crete Greece Control Systems Lab (CSL) School of Mechanical Engineering National Technical University of Athens Greece Electrical and Computer Engineering Dept. Control Systems and Robotics Lab (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Crete Greece

In this paper we propose a method for autonomous navigation in GPS-denied environments that can be deployed in all types of robotic vehicles requiring only a single RGB-D camera. Our algorithm is an integration of localization, mapping and trajectory planning software modules that can handle dynamic environments. dept. measurements and visual odometry are used to (a) create a robocentric Euclidean Signed Distance Fields (ESDF) map in real-time, (b) estimate the position of obstacles surrounding the robot, and (c) calculate the distance and gradient from them. Subsequently, we use an optimization algorithm to plan a collision-free trajectory. We show that a local map can be created faster than with the fixed-size array method used in current optimization methods. Our approach also allows for effective detection of dynamic obstacles by constantly updating the map. As a result, the robot deviates from its initial path only when necessary. We validate our results in simulation by deploying our algorithm in a skid steering rover and a hexacopter in an environment with static and dynamic obstacles.

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