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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Jezdimirovic, Jovana Pekez, Nenad Kovacevic, Jelena University of Novi Sad Faculty of Technical Sciences Computing and Control Engineering Department Novi Sad Serbia Systems LLC RT-RK Institute for Computer Based Novi Sad Serbia

ISBN: (纸本)9798350347722

The rapid development of digital technology has brought about the challenge of ensuring information security. Cryptography and steganography are among the various techniques available to address this challenge. These techniques come in different forms and provide reliable means of securing information and communication. Despite the existence of numerous options, new variations are still emerging. This paper concentrates on Least Significant Bit (LSB) coding, which is one of the most widely recognized and frequently utilized steganography techniques. The advantages of LSB-based coding methods are high capacity and low complexity. However, predictability is an issue. Audio files' sizes and data redundancy make audio data perfect for steganography, as it is possible to embed large amounts of secret information and easily transmit the signal via various communication channels. However, the use of LSB coding in audio steganography has a drawback due to the extreme sensitivity of the human auditory system (HAS). This means that any noise added to the audio with data embedded in the LSBs can be detected by the HAS, which is dependent on the number of LSBs used. This work presents an improvement of the LSB-based approach, the XORing of LSBs method, with an emphasis on enhanced security. The method achieves this by randomly picking the pairs of bits to be XOR'd while preserving the characteristics of classic LSB methods. To verify the method, it has been implemented on the Cirrus Logic DSP, proving that it may be efficiently used in a real-Time audio environment without interfering with HAS sensitivity levels. © 2023 IEEE.

关键词： Steganography

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FusionAraSA: Fusion-based Model for Accurate Arabic Sentiment Analysis

FusionAraSA: Fusion-based Model for Accurate Arabic Sentimen...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdulfattah E. Ba Alawi Ahmed N. Nusari Ferhat Bozkurt İbrahim Yücel Özbek Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen Electrical and Electronics Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Computer and Control Engineering Department Faculty of Engineering Sana’a University Sana’a Yemen Electrical and Electronics Department Faculty of Engineering Ataturk University Erzurum Turkey

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

The Arabic language is one of the most common spoken languages. Due to the complex structure and extensive range of potential meanings of Arabic texts, it is a challenging task to perform sentiment analysis using Natural Language Processing (NLP) approaches. Traditional methods of sentiment analysis often fail to perform Arabic sentiment analysis tasks. In this study, a fusion majority voting technique was employed to enhance the performance of Arabic sentiment analysis. The proposed method integrates four models (i.e. AraBERv1, MARBERT, Modified MARBERT, and AraBERv2 ) to analyze Arabic sentiments. Then, the outputs of these four models were forwarded to a fusion stage the perform majority voting and show the corresponding identified class. This technique is called FusionAraSA which relies on integrating four models and fusion to expand the application of pre-trained models. The FusionAraSA approach shows promising performance reaching more than 95% in terms of both accuracy and F1 Score utilizing two publicly available Arabic datasets. The results obtained using FusionAraSA illustrate the exceptional performance and the feasibility of this model in Arabic sentiment analysis. Additionally, the findings highlight the remarkable potential of the fusion model and underscore the necessity for further research to unravel the intricacies of Arabic dialects. Moreover, the FusionAraSA model represents a major step towards building more complex, culturally sensitive, and technologically advanced Arabic language analysis architecture.

关键词： Sentiment analysis Analytical models Accuracy Architecture Buildings Task analysis

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Comparison of YOLO Algorithms for Vehicle Accident Detection and Classification

Comparison of YOLO Algorithms for Vehicle Accident Detection...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Ahmed N. Nusari Abdulfattah E. Ba Alawi Ferhat Bozkurt İbrahim Yücel Özbek Electrical and Electronics Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Computer and Control Engineering Department Faculty of Engineering Sana’a University Sana’a Yemen Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen Electrical and Electronics Department Faculty of Engineering Ataturk University Erzurum Turkey

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Early detection of vehicle accidents is essential for immediate response and to decrease the severity of injuries while vehicle accidents occur. Among the advanced algorithms YOLOv6, YOLOv7, YOLOv8, and YOLOv9 are compared in this article to determine their performance in detecting vehicle accidents that are categorized as "severity" or "moderate." The study emphasizes how important deep learning is to enhancing accident detection systems. Out of all the models evaluated, YOLOv8m has the highest precision (0.979), and the highest recall (0.927) for YOLOv8n. Furthermore, YOLOv9c performs admirably in mAP50, receiving a score of 0.977, indicating its resilience in identifying accidents under a variety of circumstances. YOLOv9e is noteworthy for its better mAP50-95, which reaches a high of 0.941, demonstrating its ability to localize accident incidents accurately. These results provide valuable insight into how well particular algorithms perform in real-world situations. Through a close examination of their performance measures, this research aids in the advancement of more effective accident detection systems, which in turn improves emergency response operations and lessens the effects of accidents on people and communities. This comparison research emphasizes how crucial it is to use state-of-the-art technology to increase accident detection accuracy and enable timely and efficient response.

关键词： YOLO Deep learning Technological innovation Accuracy Computational modeling Scalability Emergency services

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H control for General Conformable Polynomial Fuzzy Models

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International Journal of Fuzzy Systems 2025年 1-10页

作者： Laajimi, Malek Gassara, Hamdi Rhaima, Mohamed Mchiri, Lassaad Makhlouf, Abdellatif Ben Laboratory of Sciences and Techniques of Automatic control & Computer Engineering National School of Engineering of Sfax Sfax Tunisia Department of Statistics and Operations Research College of Science King Saud University Riyadh Saudi Arabia Panthéon-Assas University Paris II Paris France Department of Mathematics Faculty of Sciences Sfax University Sfax Tunisia

This research focuses on exploring the exponential $$H_\infty $$ stability of general conformable nonlinear system. In order to address the nonlinearity inherent in the system, a polynomial fuzzy (PF) method is employed. Modeling a general conformable nonlinear system within the polynomial framework reduces the number of fuzzy rules compared to the classical Takagi–Sugeno fuzzy (TSF). Furthermore, controlling such a complex system, which accounts for perturbations, employs a PF model instead TSF model to describe its nonlinear dynamics, and incorporates a general conformable derivative instead of an integer-order one, is significantly more challenging, and remains unaddressed in previous studies. In this paper, a PF controller is designed in the form of sum of squares (SOS) to enhance the resilience against perturbations and ensure the exponential stability of the proposed model. The proposed SOS can be solved numerically, and partially symbolically, using the recently developed SOSTOOLS. In order to ensure the $$H_\infty $$ performance, a generalized criterion is defined for the general conformable nonlinear system. To demonstrate the effectiveness of the proposed method, a numerical example is provided.

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EQUILIBRIA AND STABILITY OF ONE MESSENGER RNA AND TWO MICRO RNA DYNAMICS

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

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2022年第4期84卷 3-8页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

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Cardiac Condition Detection Model Using Alexnet and Time-Frequency Representation of ECG Signals

Cardiac Condition Detection Model Using Alexnet and Time-Fre...

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E-Health and Bioengineering Conference (EHB)

作者： Mihai Aron Teofil Ilie Ursache Gladiola Petroiu Cristian Rotariu Dept. of Biomedical Sciences Grigore T. Popa University of Medicine and Pharmacy of Iasi Faculty of Medical Bioengineering Iaşi Romania Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University Faculty of Automatic Control and Computer Engineering Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Cardiac conditions are one of the leading causes of death worldwide. To address this, we designed a model that can detect cardiac conditions from a patient's electrocardiogram (ECG). This will convert the 1D ECG signal into a 2D scalogram using wavelet transforms with Morlet wavelets. With the help of a network based on the AlexNet convolutional neural network, it distinguishes between a normal ECG signal and one indicative of arrhythmia or congestive heart failure. The resulting model performs well, achieving a classification accuracy of 92.20% and providing a robust approach for detecting cardiac conditions.

关键词： Wavelet transforms Training Time-frequency analysis Accuracy Biological system modeling Electrocardiography Predictive models Congestive heart failure Convolutional neural networks Biomedical engineering

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Acquisition and Monitoring of Environmental Parameters from High-altitude UAV Flight

Acquisition and Monitoring of Environmental Parameters from ...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Marius Dima Dan Popescu Loretta Ichim Petrișor Valentin Pârvu Faculty of Automatic Control and Computer Science National University of Science and Technology Politehnica Bucharest Bucharest Romania Faculty of Aerospace Engineering National University of Science and Technology Politehnica Bucharest Bucharest Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

Unmanned aerial vehicles can improve short- term weather forecasting by acquiring information from weather sensors and other sensors. With this information, there is the possibility of making relevant maps like solar radiation, pollen, emissions, particles, and others. Another advantage of this acquisition system is the high rate of flights, compared to the classic measurements made with the weather balloon, which is launched twice a day. In addition to the advantages listed above, we discuss the multiplication factor of the acquired data, these systems being able to operate in various geographical locations.

关键词： Weather forecasting Data integration Autonomous aerial vehicles Prediction algorithms Particle measurements control systems Sensors Solar radiation Monitoring Payloads

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Upgrading and testing of the UPV/EHU Stellarator 13

Upgrading and testing of the UPV/EHU Stellarator

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Garrido, Aitor J. Marco, Aitor De La Sen, Manuel Oleagordia, Inigo Garrido, Izaskun University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao Po Rafael Moreno 3 Bilbao48013 Spain University of the Basque Country - UPV/EHU. Automatic Control Group - Ac Advanced Design and Analysis Department Idom Zarandoa Etorb. 23 Bilbao48015 Spain University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Electricity and Electronics Faculty of Science and Technology B° Sarriena s/n Leioa48080 Spain

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

This paper deals with the upgrade and testing of the of the Ultra-Low Iota Super Elongated Stellarator of the University of the Basque Country. The main upgrades affect to the coil system but also to the microwave source and the data acquisition system. Therefore, it is necessary to update its State-Space model. The updated model is validated by means of experimental output data showing an accurate matching with the real system. Then, in order to test the new model, a Model Predictive control-MPC scheme is successfully implemented both in simulation and experimentally using a real-time control platform. © 2022 IEEE.

关键词： Model predictive control

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MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media

arXiv

引用

arXiv 2023年

作者： Truică, Ciprian-Octavian Apostol, Elena-Simona Nicolescu, Radu-Cătălin Karras, Panagiotis Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest060042 Romania Department of Computer Science University of Copenhagen Copenhagen2100 Denmark

The widespread availability of internet access and handheld devices confers to social media a power similar to the one newspapers used to have. People seek affordable information on social media and can reach it within seconds. Yet this convenience comes with dangers;any user may freely post whatever they please and the content can stay online for a long period, regardless of its truthfulness. A need arises to detect untruthful information, also known as fake news. In this paper, we present an end-to-end solution that accurately detects fake news and immunizes network nodes that spread them in real-time. To detect fake news, we propose two new stack deep learning architectures that utilize convolutional and bidirectional LSTM layers. To mitigate the spread of fake news, we propose a real-time network-aware strategy that (1) constructs a minimum-cost weighted directed spanning tree for a detected node, and (2) immunizes nodes in that tree by scoring their harmfulness using a novel ranking function. We demonstrate the effectiveness of our solution on five real-world datasets. © 2023, CC BY-NC-ND.

关键词： Trees (mathematics)

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Optimizing High Resolution Wide Field of View Optical Design for Long Wave Infrared Objective

Optimizing High Resolution Wide Field of View Optical Design...

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Electrical engineering (ICEENG), 12th International Conference on

作者： Hossam Aboalia Sherif Hussein Alaaeldin Mahmoud Control Systems Department Optoelectronics and Automatic Military Technical College Cairo Egypt Artificial Intelligence Department Computer Engineering Military Technical College Cairo Egypt

ISBN: (数字)9798350343427

ISBN: (纸本)9798350343434

Optical system is a basic component of infrared (IR) imaging systems that affect the image quality of the observed field of view (FOV). Responsible for collecting IR radiation from the scene and projecting it onto detector pixels. The optical system's characteristics, such as lens material, focal length, and optical diameter, critically impact the amount of transmitted IR radiation. The design process aims to eliminate and limit aberrations to enhance performance. Increasing spatial resolution and widening the FOV are crucial for image quality improvement. In this study, we present a unique high-resolution wide FOV optical design for an infrared objective operating in the long-wave infrared (LWIR) band $(\mathbf{8}-\mathbf{12}\ \boldsymbol{\mu} \mathbf{m})$ . Utilizing the time-tested Cooke triplet structure as the foundation, we enhance its capabilities through the implementation of a splitting methodology. This approach allows for improved control over aberrations and enhances the optical design's overall performance. Ansys Zemax OpticStudio software was employed to optimize radii of curvatures and thicknesses based on the proposed merit function operands. Our concept makes use of a small pixel size $(\mathbf{15}\ \mu \mathbf{m})$ to achieve an expansive FOV of 18° along with a high spatial resolution of 31 cycles/mm. This makes the design a highly suitable candidate for diverse remote sensing observation applications.

关键词： Integrated optics Image quality Optical design Optical detectors Optical imaging Size measurement Software

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