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SSRN 2022年

作者： Bozlak, Çağatay Berke Yaşar, Claudia Fernanda Department of Control and Automation Engineering Yildiz Technical University Istanbul Turkey

In this paper, Python and TensorFlow were used to program SARIMAX, LSTM, and CNN-LSTM models for prediction and forecasting analyses. The performance of the models was assessed and compared using the MAE, RMSE, MAPE, and percentage accuracy. The research was based on historical data from the German electrical market. The effectiveness of the models in predicting dayahead electricity prices is assessed, the total-hourly electricity consumption is an exogenous variable used as a model input, and its impact on model performance is assessed. The electrical consumption is added as an exogenous input to this time-series analysis, which uses real electricity pricing. The CNN-LSTM model use CNN to extract valuable characteristics in order to automatically pick the best model, while the LSTM recognizes data dependency in time series. A variety of tests were carried out to verify our findings, examine the accuracy of the programmed models, and investigate the effect of introducing exogenous data. To compare forecasting methodologies, we use the Mean Absolute Error, Root-Mean Squared Error, Mean Absolute Percentage Error, and percentage accuracy. In terms of accuracy, simplicity, and time usage, the LSTM and CNN-LSTM data-driven models surpass the SARIMAX model. In terms of precision, the CNN-LSTM technique was the best. © 2022, The Authors. All rights reserved.

关键词： Long short-term memory

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Enhancing Pain Level Assessment in Post-Surgery Patients Using Artificial Intelligence Algorithms

Enhancing Pain Level Assessment in Post-Surgery Patients Usi...

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European control Conference (ECC)

作者： G. Ben Othman E. Yumuk D. Copot A. R. Ynineb H. Farbakhsh I. R. Birs C. I. Muresan R. De Keyser I. Chihi C. M. Ionescu M. Neckebroek Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Ghent University Gent Belgium Department of Control and Automation Engineering Istanbul Technical University Maslak Istanbul Turkey Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department Of Engineering Faculty of Science Technology and Medicine University of Luxembourg Kirchberg Luxembourg Department of Anesthesia Ghent University Hospital Ghent Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

control performance decreases significantly in the presence of uncertainty in variable availability, measurement noise, or instrumentation failure. In cluttered environments such as the Post Anesthesia Care Unit (PACU), clinical measures are often influenced by noise and artifacts. An important component in post-operative treatment is the assessment and management of pain levels. However, reliable information is critical for clinically relevant results and improved patient outcomes. From a control engineering point of view, variables are often estimated and interpolated to allow a suitable flow of feedback information to control loops for the optimization of drug dosages. In this context, Artificial Intelligence (AI) stands as a promising tool to augment pain level assessment. This study introduces and compares two AI-based approaches for predicting continuous Numerical Rating Scales (NRS) based on heart rate (HR) data. The first approach uses polynomial regression, lasso regression, and ridge regression, while the second employs an LSTM model. Notably, the AI prediction model, independent of traditional interpolation techniques, outperforms the approach relying on interpolation. The proposed AI-based method holds promise for continuous estimation and can serve as an estimator for model-based control. This proof of concept study underscores the potential of AI tools to enhance pain level assessment.

关键词： Heart rate Interpolation Uncertainty Pain Noise Numerical models Noise measurement

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Compensation of the Temperature Impact on the Characteristics of a Titania-Silica Thin Film Humidity Sensor Element

Compensation of the Temperature Impact on the Characteristic...

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Automatics and Informatics (ICAI), International Conference

作者： Stefan Ivanov Nedyu Nedev Zvezditza Nenova Department of Automation Information and Control Systems Technical University of Gabrovo Gabrovo Bulgaria Department of Fundamentals of Electrical and Power Engineering Technical University of Gabrovo Gabrovo Bulgaria

In the present work is investigated the impact of ambient temperature in the range of 20°C to 50°C under a change in relative humidity RH of 20% up to 92 % on the characteristics of a highly sensitive TiO 2 -SiO 2 -based thin-film impedance humidity sensor element doped with Ce and prepared by a sol-gel method. The variation of sensor impedance changes in a very wide range - about 4 orders of magnitude. The sensor element is connected in a measurement circuit based on an AC bridge, a variable gain amplifier, a precision rectifier, and a microcontroller with a built-in analog-to-digital converter. The use of artificial neural networks monitoring the ambient temperature and measured voltage is proposed for the realization of the temperature compensation of the characteristics. The proposed approach allows compensating the impact of temperature and performing measurements when connecting humidity sensing elements with a very wide range of impedance change.

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Consensus of Double Integrator Multiagent Systems under Nonuniform Sampling and Changing Topology

arXiv

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arXiv 2022年

作者： Sevim, Ufuk Goren-Sumer, Leyla Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey

This article considers consensus problem of multiagent systems with double integrator dynamics under nonuniform sampling. It is considered the maximum sampling time can be selected arbitrarily. Moreover, the communication graph can change to any possible topology as long as its associated graph Laplacian has eigenvalues in a given region, which can be selected arbitrarily. Existence of a controller that ensures consensus in this setting is shown when the changing topology graphs are balanced and has a spanning tree. Also, explicit bounds for controller parameters are given. A novel sufficient condition is given to solve the consensus problem based on making the closed loop system matrix a contraction using a particular coordinate system for general linear dynamics. It is shown that the given condition immediately generalizes to changing topology in the case of balanced topology graphs. This condition is applied to double integrator dynamics to obtain explicit bounds on the controller. © 2022, CC BY.

关键词： Multi agent systems

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Graph-Based Collision Avoidance Algorithm Among Swarm Agents

Graph-Based Collision Avoidance Algorithm Among Swarm Agents

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International Symposium on Electrical and Electronics engineering (ISEEE)

作者： Akif Durdu Mesut Tuncer Berat Yıldız Department of Electrical and Electronics Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkiye Department of Computer Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkiye Department of Electrical and Electronics Engineering Karamanoglu Mehmetbey University Karaman Turkiye

More than one homogenous or heterogenous type unmanned vehicle can work in a coordinated manner and perform large-scale swarm tasks (firefighting, search and rescue, mapping, and military operations, etc.) efficiently in a shorter time by sharing tasks. Collision of these vehicles is among the most significant problems encountered during their work. The crash of the vehicles causes the vehicles to be out of duty and, accordingly, to the mission’s failure. In this study, Quadrotor-type UAVs used as agents can go to any target point by receiving location, speed, and compass information with GPS and IMU sensors. In the application, the agents’ locations were kept and updated in a list in pairs, similar to the traversing process in the Optimized Bubble Sort Algorithm. The projections of the velocity vectors on the agents’ axis (local) on a single coordinate plane are taken to determine the collision situation between these two agents that are traveling instantaneously. These global velocity vectors, whose projections are taken, are re-projected to the edge formed by these two agents in the graph and then subtracted from each other. Suppose the size of the vector is greater than the distance between two agents obtained by any GPS distance algorithm (Pythagoras, Haversine, etc.). In this case, collision is detected, and the separation process is activated. Separation is the process of advancing one agent in the opposite direction of the other until a minimum safe distance is achieved, where one agent entered by the user will not affect the other. Once the separation is complete, the agent moves to the final destination point.

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RRT Based Frontier Point Detection for 2D Autonomous Exploration

RRT Based Frontier Point Detection for 2D Autonomous Explora...

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International Conference on Robotics and automation engineering (ICRAE)

作者： Ecem Sumer Hakan Temeltas Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey

The ability to explore an unknown environment and create a representation is a must-have for a fully autonomous robot. Autonomous exploration is a multifaceted problem and requires solutions to a combination of sub-problems such as Simultaneous Localization and Mapping (SLAM), path planning and following, detecting potential navigation target points and evaluating them to select a target. This study implements a frontier point based approach to identify potential navigation targets. Permanent and temporary RRT-based tree structures are used to search the existing map and detect frontier points. Permanent tree is rooted from the initial position of the robot and is never reset. Temporary trees are reset when they hit a frontier point or reach a certain number of branches. Two types of temporary trees are used, starting from the robot's current location and starting from the frontier points that lose their frontier point characteristics as the region they lie is mapped. A revenue function considering path cost, heading cost, and information gain is used to evaluate the frontier points and select a target among them.

关键词： Costs Simultaneous localization and mapping automation Navigation Path planning Autonomous robots

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IoT and Machine Learning Based Affordable Smart Farming 8

IoT and Machine Learning Based Affordable Smart Farming

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8th IEEE International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Thirumagal, P.G. Abdulwahid, Aqeel Hadi Hadiabdulwahid, Ali Kholiya, Deepak Rajan, Raji Gupta, Monika Vistas School of Management Studies Tamil Nadu Chennai India University of Basrah College of Agricultural Department of Horticulture Iraq Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Graphic Era Hill University School of Agriculture Uttarakhand Dehradun India School of Commerce Studies Bangalore560069 India Chitkara University Chitkara Business School Punjab India

ISBN: (纸本)9798350347791

An breakthrough technology called the Internet of Things (IoT) provides workable and dependable solutions for the modernization of a few locations. Systems based on the Internet of Things are being created to monitor and maintain horticulture farms with the least amount of human intervention. The proposed model is a framework for a smart water system that predicts how much water will be needed for a harvest using machine learning analysis. The three most crucial factors to consider when estimating how much water will be present in a given farming area are wetness, temperature, and moistness. Agriculture is one of the most important factors in the economic development of any country. In many non-industrialized nations, horticulture plays a significant and critical role in the development of their economies. India, one of the world's top producers of vast quantities of various harvests, genuinely employs conventional agricultural methods. Ranchers must increasingly produce more food of the highest quality while simultaneously coping with challenges associated to climate change adaptation. IoT-based and machine learning-based smart horticulture would help ranchers by continuously monitoring their crops and providing advice on harvesting and composting. This study's major objective is to provide a Smart Agribusiness framework based on the Internet of Things (IoT) that would help ranchers by providing recommendations based on a variety of variables, such as temperature, pH, wetness, and precipitation. © 2023 IEEE.

关键词： Horticulture

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A fractional order impedance model for heterogeneous drug distribution in obese patients during general anesthesia ⁎

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IFAC-PapersOnLine 2024年第12期58卷 61-66页

作者： Amani R. Ynineb Erhan Yumuk Hamed Farbakhsh Ghada Ben Othman Dana Copot Isabela R. Birs Cristina I. Muresan Robin De Keyser Samir Ladaci Clara M. Ionescu Martine Neckebroek Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde 9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Maslak 34469 Istanbul Turkey Technical University of Cluj Napoca Romania Department of Automation Memorandumului Street 20 Cluj Romania National Polytechnic School Department of Automatics and Control Engineering 10 Rue des Fréres OUDEK El Harrach 16200 Algiers Algeria Ghent University Hospital Department of Anesthesia Corneel Heymanslaan 10 Ghent 9000 Belgium

Personalised pharmacokinetic models imply stepping away from the classical assumption of homogeneous drug mixing in various tissue compartments in the body, with a particular impact on obese patients. In this work, the pharmacokinetic compartmental model structure is revisited to account for non-uniform distribution of uptake/clearance time constants in patients as a nonlinear function of body mass index. Simulations are confirming expected patterns of drug distribution in the body and can account for post-anesthesia side effects up to 72 hours. We apply spectroscopy to extract the complex impedance in fat tissue samples. The data is modelled by a Cole-Cole model, where parameters of the fractional order impedance model are optimized using a genetic algorithm. The findings suggest that fat tissue will exhibit anomalous diffusion when drug uptake and clearance are present.

关键词： fractional order impedance model Cole-Cole model bioimpedance compartmental modelling general anesthesia frequency domain spectroscopy

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Design and Implementation of an Image Processing-Based Ping Pong Training Robot

Design and Implementation of an Image Processing-Based Ping ...

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Innovations in Intelligent Systems and Applications Conference

作者： Mert Aydın Sezercan Bektaş Ahmet Ajam Ahmet Kağızman Volkan Sezer Department of Mechatronics Engineering Istanbul Technical University Istanbul Turkey Department of Institute of Science Smart and Autonomous System Laboratory (SASlab) Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Smart and Autonomous System Laboratory (SASlab) Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

This study aims to develop an image-processing-based ping-pong training robot to facilitate effective practice for ping-pong players. In the developed system, the image of the ping-pong player is processed from the camera integrated into the robot, the player's position is determined and the ball is directed to areas that are difficult for the player to reach. The reason for launching the ball into difficult areas is to improve the players' physical and strategic abilities. In the process of throwing the ball, the ball is placed in the hopper, driven from the hopper to the launch point with the help of a servo motor, and launched with the help of two DC motors. Experimental results confirm that the robot accurately detects the player's position and successfully directs the ball to the intended target area. Furthermore, the findings demonstrate that this system, which integrates image processing and robotic control technologies, provides a robust and adaptable training tool for ping-pong players.

关键词： Training Technological innovation Image processing Robot vision systems Process control DC motors Cameras Servomotors Intelligent systems Robots

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Design. Implementation, and control of a Novel Automated Manual Transmission (AMT) System for Manual Transmission Bicycles

Design. Implementation, and Control of a Novel Automated Man...

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Innovations in Intelligent Systems and Applications Conference

作者： Fehmi Can Ay Bengisu Kılınç Talha Enes Ercan Ahmet Kağızman Volkan Sezer Department of Mechatronics Engineering Istanbul Technical University Istanbul Turkey Department of Institute of Science Smart and Autonomous System Laboratory (SASlab) Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Smart and Autonomous System Laboratory (SASlab) Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

In recent years, the bicycle industry has undergone continuous transformation through the introduction of novel technologies and innovations. Automated Manual Transmission (AMT) system, which is widely used in motor vehicles and defined as automating the traditional manual gearbox through electronic components and actuators, has an important place in the automotive industry due to its advantages such as fuel efficiency, low cost, and driver comfort. However, a similar system is not yet available on bicycles. This article describes developing a new gear-shifting system that enables the manual gear-shifting mechanism in bicycles to be automated with an intelligence-based system. The developed system automatically performs the most appropriate gear change by processing the data received from the sensors, such as inclination, wheel, and pedal cadence, thus providing a more efficient and comfortable driving experience that does not require effort. The system has been tested by integrating it into a bicycle with manual transmission and it has been confirmed that automatic gear shifts were successful.

关键词： Industries Technological innovation Gears Wheels Manuals Bicycles Sensor systems Intelligent systems Intelligent sensors Vehicles

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