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检索条件"机构=Department for Automation and Applied Informatics"

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Using Weka API for creating a custom classification application

Using Weka API for creating a custom classification applicat...

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International Symposium on applied Computational Intelligence and informatics ( SACI)

作者： Raul Robu Paul Arseni-Ailoi Dan Ungureanu-Anghel Department of Automation and Applied Informatics Faculty of Automation and Computers Politehnica University of Timisoara Timisoara Romania

In real world applications, classification models can be built by repeatedly going through the steps of data preprocessing, building classification models with different dedicated algorithms, testing the resulted models, until building a good enough classification model is achieved. The model built in this way can be used in order to perform predictions on new data, with a degree of trust resulted by testing the model. All the operations described above can be done with Weka, which is a very powerful machine learning tool. The authors consider that after going through the previous steps, for many real world applications, it would be beneficial to go through a supplementary step, of developing a custom application for data classification, specific to the realized study. The proposed application will use the Weka API, which will allow it to rebuild the selected classification model, save and load it in/from a binary file and then make predictions with the help of a user interface perfectly adapted to the data set used. The proposed application makes it easier to make predictions for a final beneficiary. The paper presents how such a custom classification application can be developed, using the Weka API and Java programming language. In order to validate the proposed solution, the authors have built a custom application for the classification of data of patients who may have heart diseases, starting from the Cleveland heart disease data set, obtained from the UCI Machine Learning Repository. The proposed application allows saving and loading the classification model through serialization and deserialization, so that building it in order to make predictions is necessary only once.

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Simplified DC-DC Converter Models for Interconnecting Loads to a DC Microgrid

Simplified DC-DC Converter Models for Interconnecting Loads ...

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International Symposium on applied Computational Intelligence and informatics ( SACI)

作者： Cezara-Liliana Rat Octavian Prostean Catalin Ichim-Burlacu Department of Electrical Engineering and Industrial Informatics PolitehnicaUniversity of Timisoara Timisoara Romania Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

This paper presents an alternative method of obtaining linear mathematical models for the Buck, the Boost and the Buck-Boost converters. The most common method of modelling DC-DC converters is state space averaging. State space averaged models provide the most information about the behaviour of the converters, but are usually non-linear. Scientific fields like automation, system control, system engineering, etc., which are at the forefront of microgrid development, require linear models. This makes it necessary to linearize the models around an operating point. The resulting model would be linear but for the price of lower accuracy. The proposed method can produce a linear model more directly, without requiring linearization. This method is based on state space averaging but it deviates from it by applying certain simplifying assumptions or mathematical artifices in the process of obtaining the differential equations, leading to a simpler model. These simplifying assumptions are based on the role of the converter within the microgrid, namely load side converters LSC. The simplified models obtained through this method have the advantage of preserving the essential characteristics of the system dynamics.

关键词： automation Accuracy System dynamics Computational modeling Microgrids DC-DC power converters Aerospace electronics

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Automotive Scenarios for Trajectory Tracking using Machine Learning Techniques and Image Processing

Automotive Scenarios for Trajectory Tracking using Machine L...

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International Symposium on applied Computational Intelligence and informatics ( SACI)

作者： Delia Moga Ioan Filip Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania

This paper presents a study on using innovative machine learning techniques that can be applied in automotive traffic scenarios to increase a vehicle’s level of autonomy. The overtaking traffic scenario is treated for predicting the vehicle trajectory when overtaking another vehicle and the data is obtained by image processing using a video camera. Two different methods are compared, first by using classic tracking methods and a Kalman filter (as an adaptive filter) and second by using a machine learning technique - Support Vector Machine. The present article uses as inputs the data received from the camera and focuses on tracking selected objects and estimating their position using mainly image processing in automotive scenarios. The main purpose of this work is to experiment and compare different tracking modes to determine those that have the best performances in terms of runtime, memory usage and prediction accuracy.

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Tuning of a Minimum Variance Control System Based on the Estimated Process Gain

Tuning of a Minimum Variance Control System Based on the Est...

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International Symposium on applied Computational Intelligence and informatics ( SACI)

作者： Ioan Filip Octavian Prostean Iosif Szeidert Dorin Bordeasu Cristian Vasar Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania

The control of a nonlinear process raises various problems, both in terms of the control law design and the controller tuning. This paper presents a tuning procedure of a minimum variance control system based on the analysis of the estimated gain of the controlled process. In this regard, the performed study shows that the settling-time of the estimated process gain can be used as a tuning criterion for the minimum variance controller, allowing the improvement of the control performance. The procedure involves closed-loop estimation of the process gain based on parameters estimates of a linearized model that approximates the nonlinear process functionality around an operating point. The basic idea is that, although the parameters estimates of the linearized model are different in closed-loop, respectively open-loop, the steady-state gain estimates are similar in both cases. Thus, the time dynamics of this estimated gain can be a useful indicator for the control system tuning. In order to validate the proposed procedure, an induction generator integrated into a wind energy conversion system was considered as a controlled process.

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Networked control of a Parrot Mambo drone

Networked control of a Parrot Mambo drone

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Alexandru Codrean Attila Kovács Octavian Stefan Zsófia Lendek Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Automation and Applied Informatics Politehnica University Timisoara Timisoara Romania

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

The current study proposes a network control structure for small low-cost drones like the Parrot Mambo mini-drone. The structure is composed of an inner loop running on the drone, and an outer loop running on a remote computer. The inner loop controls the attitude and altitude of the drone based on Kalman filter estimations from the onboard sensors. The outer loop ensures position tracking based on measurements from OptiTrack cameras. A time delay compensator is added to address the constraints imposed by wireless network communications between the drone and the remote computer. Experimental results using Parrot Mambo drones show good stability and tracking performances, despite model uncertainty and time delay.

关键词： Uncertainty Delay effects Computational modeling Wireless networks Position measurement Cameras Robustness

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Serious Gaming and Artificial Intelligence in Rehabilitation of Rheumatoid Arthritis

Serious Gaming and Artificial Intelligence in Rehabilitation...

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作者： Varga, Gabriela Stoicu-Tivadar, Lǎcrǎmioara Nicola, Stelian Politehnica University Timioara Department of Automation and Applied Informatics 2 Vasile Pârvan Blvd. Timioara300223 Romania

ISBN: (纸本)9781643682907

This paper presents a current situation of studies and applications which are using serious games and artificial intelligence (AI) in rehabilitation of rheumatoid arthritis, and possible future directions. The objectives of this paper are: to highlight the technologies used for recovery of patients with rheumatoid arthritis (RA), to summarize the state of the art of existing applications and to present the authors work, a software application that aims contributing to the recovery of the specific patients. At this stage the application was tested by a group of 10 patients from Medical Centre Sf. Mary of Timisoara. Most of the patients reported that the physical and psychical effort were between easy-very easy. The patients confirmed that they would use the application in their rehabilitation process and are very excited about this type of rehabilitation that stimulates curiosity and a state of wellbeing. The application works based on the leap motion device that proved to be the most suitable device in terms of precision and the manner of interaction in virtual reality games. © 2022 The authors and IOS Press.

关键词： Patient rehabilitation

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ECC Implementation and Performance Evaluation for Securing OPC UA Communication

ECC Implementation and Performance Evaluation for Securing O...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Alexandra Tidrea Adrian Korodi Department of Automation and Applied Informatics University Politehnica Timisoara Timisoara Romania

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Protecting critical infrastructures and manufacturing plants in the context of Industry 4.0 against cyber-attacks is a nowadays challenge due to lack or insufficient security mechanisms for the communication protocols. Even though new protocols are considering built-in security (e.g. OPC UA) there is still a struggle for assuring interoperability and interconnectivity in the IoT era while dealing with resource constrained devices. This paper attempts to implement and evaluate a solution for assuring the authenticity and integrity of the data transmitted through OPC UA protocol in a client- server communication based on ECC as an alternative to the existing implemented solution which uses RSA. We choose ECC since it can achieve similar level of security as RSA for smaller key size and in order to respond to the limited memory and resource constrained elements part of an industrial system. Furthermore, we aim to evaluate through measurements the performance of different ECC key sizes in respect to the latency introduced by each cryptographic operation.

关键词： Performance evaluation Protocols NIST Elliptic curve cryptography Error correction codes Computational efficiency Timing

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Generating Visually Evoked Potentials Using a Diffusion Probabilistic Model 14

Generating Visually Evoked Potentials Using a Diffusion Prob...

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14th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2023

作者： Torma, Szabolcs Tevesz, Judit Szegletes, Luca Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Telecommunications and Media Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

ISBN: (纸本)9798350325652

We present a diffusion probabilistic model (DPM) capable of generating high-quality electroencephalography (EEG) signals. In particular, we investigate the fidelity of synthesized visually evoked potentials and the performance of the novel class-conditioned continuous-time DPM that generates the signals. We carefully select our neural network architecture to prevent generated frequency artifacts in the multi-channel synthesized EEG signals. With progressive distillation, we are able to achieve a single-step diffusion model that still has a competitive performance. With generative metrics and statistical analysis, we show that using DPMs for brain signal generation is feasible. © 2023 IEEE.

关键词： Electroencephalography

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Comparison of optimization algorithms for installation error calibration of accelerometer arrays 23

Comparison of optimization algorithms for installation error...

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23rd IEEE International Symposium on Computational Intelligence and informatics, CINTI 2023

作者： Pesti, Richard Sarcevic, Peter Csik, Dominik Nagy, Istvan Odry, Akos Óbuda University Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary University of Szeged Department of Mechatronics and Automation Szeged Hungary Óbuda University Bánki Donát Faculty of Mechanical and Safety Engineering Budapest Hungary

ISBN: (纸本)9798350342949

Accelerometers play a crucial role in localization problems, but their accuracy depends on the precision of the calibration process. In this paper, a comparison of optimization algorithms is presented within the scope of between sensor error calibration. The Particle Swarm optimization (PSO) and Genetic Algorithm (GA) are proposed for the problem, and tested in three different setups. Moreover, the MATLAB built-in fmincon minimization algorithm is also evaluated for calibration parameter estimation. A custom fitness function is proposed to obtain the between sensor misalignment and bias errors, for two accelerometers. The analysis highlights that the algorithms can successfully determine the between sensor error parameters. The conducted comparison shows that fmincon reached an outstanding speed in terms of convergency, but in overall PSO has produced better results compared to GA and fmincon. PSO is more suitable for the calibration problem because of its robustness and stability characteristics. © 2023 IEEE.

关键词： Calibration

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Raman microscopic measurement of materials used on banknotes 26

Raman microscopic measurement of materials used on banknotes

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26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

作者： Tomaskova, Hana Vasek, Vladimir Department of Electronic and Measurements Faculty of Applied Informatics Tomas Bata University in Zlin Zlín Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Zlín Czech Republic

ISBN: (纸本)9781665481861

The successful verification of the authenticity of banknotes, or the detection of counterfeits, is based on the combination of an effective measuring system and computer technology. In this paper, a modern diagnostic method Raman microscopy together with an exploratory tool for processing and interpreting multi-dimensional datasets, and cluster analysis, are used to study structural differences between paper and orange ink used on genuine banknotes. Six currencies of European countries were selected for this study: Croatian kuna, Czech crown, euro, Great British Pound, Polish zloty, and Swiss franc. Raman microscopy offers non-destructive, rapid analysis without any sample preparation and pre-processing, with the potential to recognize structural modification of substances, together with the advantages of optical microscopy. Cotton fibres, TiO2 in two different modifications, and other additives are successfully identified within the spectra. The patterns found in mathematically processed Raman data, especially between the paper, indicate both, the similarities and differences across the various banknotes, even of the same currency. The results serve as a base of the spectral database for authenticity control of banknotes and classification of the materials used. © 2022 IEEE.

关键词： Cluster analysis

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