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E-Health and Bioengineering Conference (EHB)

作者： Ligia-Gabriela Boazu Marian-Alexandru Petraru Otilia Zvorișteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iași Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Retinal blood vessel segmentation is an essential component in the diagnosis and monitoring of various ophthalmological conditions, such as diabetic retinopathy, glaucoma or macular degeneration, providing valuable information about the state of blood vessels and ocular blood circulation. Traditional methods for segmenting blood vessels from retinal images present certain limitations in terms of accuracy and robustness, especially under variable lighting conditions, the presence of artifacts or low-quality images. However, current techniques based on convolutional neural networks have demonstrated the ability to achieve precise and robust segmentations in a variety of conditions, outperforming traditional methods. Nevertheless, neural networks face challenges regarding the limited availability of retinal image datasets necessary for training and evaluating these solutions. In this paper we describe a solution for retinal blood vessel segmentation using the U-Net architecture. This neural network achieves impressive results even with very small datasets, demonstrating the efficiency and robustness of the U-Net architecture for retinal blood vessel segmentation.

关键词： Training Macular degeneration Image segmentation Neural networks Blood vessels Network architecture Retina Robustness Monitoring Biomedical imaging

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Addressing Misinformation in Bengali Media: A Hybrid Deep Learning Solution

Addressing Misinformation in Bengali Media: A Hybrid Deep Le...

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International Conference on computer and Information Technology (ICCIT)

作者： Fuad Ibne Jashim Farhad Shah Imran Md Mehedi Hasan Santo Mahbub Khan Anamul Sakib Md Shahidur Rahman Md Ariful Islam Rezaul Haque Shafiur Rahman Dept. of Information Technology CQ University Australia Dept. of Computer Science and Engineering BRAC University Bangladesh Dept. of Management Information System Pacific State University USA Dept. of Business Administration International American University USA Dept. of Engineering Management Westcliff University USA Dept. of Computer Science and Engineering East West University Bangladesh Dept. of Software Engineering Daffodil International University Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

The spread of fake news poses significant threats to society, democracy, and public discourse. This is especially true in Bengali-speaking communities where digital literacy and language-specific resources are limited. To address this issue, we urgently need effective ways to detect and mitigate fake news in the Bengali language. This paper highlights the unique challenges associated with linguistic diversity and misinformation prevalence. Our research introduces a hybrid deep learning algorithm specifically designed to classify fake and authentic Bengali news articles. The methodology involves extensive data collection, rigorous preprocessing to improve textual quality, and the use of advanced feature extraction methods. We combined and trained CNN and LSTM/BiLSTM models to handle the nuances of Bengali text. Our proposed algorithm significantly outperforms existing models, with a high accuracy of 98.45% in distinguishing between fake and authentic news and reducing false positives. Additionally, we developed a user-friendly web application that allows general public to input news articles and obtain predictions on their authenticity in real-time. This study not only advances the field of fake news detection but also provides essential tools for journalists, policymakers, and the general public to combat misinformation in Bengali media. Our findings have broader implications, promoting informed public discourse and supporting the development of resilient digital ecosystems. This underscores the need for ongoing research and adaptation of such models to combat the global challenge of fake news in various languages and contexts.

关键词： Deep learning Machine learning algorithms Social networking (online) Biological system modeling Scalability Ecosystems Text categorization Classification algorithms Cultural differences Fake news

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Enhancing Learning and Therapy for Children with Autism: Innovative Activities with the NAO Robot

Enhancing Learning and Therapy for Children with Autism: Inn...

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E-Health and Bioengineering Conference (EHB)

作者： Iustina-Bianca Bulai Otilia Zvorişteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Worldwide, autism affects 1 in 100 children, with diagnoses steadily rising since the 2000s. Romania lacks official statistics on autism prevalence, but global estimates suggest similarity. Children with autism struggle with social interactions and verbal communication, prompting interest in social robots for therapy and education. Tailored robot-assisted sessions offer potential for cognitive development, vocabulary enhancement, social interaction, and behavioral stimulation like concentration and attention. The NAO robot's user-friendly design, technical capabilities, and integrated features make it well-suited for these purposes. This paper presents activities that exemplify the concept of “learning through play,” allowing children to engage in exploration, experimentation, and effective learning in an enjoyable manner.

关键词： Autism Vocabulary Hospitals Social robots Education Biomedical engineering

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Is the Computing Continuum Already Here?

arXiv

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arXiv 2023年

作者： Marino, Jacopo Risso, Fulvio Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy

—The computing continuum, a novel paradigm that extends beyond the current silos of cloud and edge computing, can enable the seamless and dynamic deployment of applications across diverse infrastructures. By utilizing the cloud-native features and scalability of Kubernetes, this concept promotes deployment transparency, communication transparency, and resource availability transparency. Key features of this paradigm include intent-driven policies, a decentralized architecture, multiownership, and a fluid topology. Integral to the computing continuum are the building blocks of dynamic discovery and peering, hierarchical resource continuum, resource and service reflection, network continuum, and storage and data continuum. The implementation of these principles allows organizations to foster an efficient, dynamic, and seamless computing environment, thereby facilitating the deployment of complex distributed applications across varying infrastructures. © 2023, CC BY.

关键词： Transparency

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Modeling and Simulation of Thermal Faults in Batteries for Enhanced Safety

Modeling and Simulation of Thermal Faults in Batteries for E...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Francesco Tosoni Sara Vinco Franco Fummi Department of Engineering IM University of Verona Verona Italy Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798331528010

ISBN: (纸本)9798331528027

Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the system itself and helps extend the device’s life. The battery temperature is one of the most delicate aspects of these devices since some dangerous scenarios, like thermal runaway, could occur due to variable conditions. This paper uses a battery model of an electric vehicle from the automotive area as a case study to simulate the thermal response to normal usage. Then, thermal fault scenarios are modeled within equivalent circuital device descriptions and analyzed regarding state-of-charge, temperature, and voltage output. The findings presented offer a valuable starting point for improving the design phase of the batteries in multiple fields by testing fault scenarios already during simulation.

关键词： Temperature sensors Voltage Electric vehicles Sensor systems Batteries Thermal analysis Sensors Circuit faults Integrated circuit modeling Testing

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Exploring the Feasibility of Sleep Quality Evaluation with a Reduced Parameter Set

Exploring the Feasibility of Sleep Quality Evaluation with a...

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Smart World Congress (SWC), IEEE

作者： Michele Guagnano Sara Groppo Luigi Pugliese Massimo Violante Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy

Sleep covers approximately one-third of life, providing the necessary recovery to fundamental body functions. Sleep deprivation and poor sleep quality cause several side effects in everyday life; among others, the efficiency of the immune system progressively decreases, enhancing the arise of pathologies. Therefore, the evaluation of sleep quality is crucial for providing information about personal health status. However, a uniform and robust method for the assessment of sleep quality is still missing. In this preliminary study, Obstructive Sleep Apneas (OSAs), sleep macro pattern and sleep micro pattern are identified and then combined to provide a comprehensive sleep evaluation. For this purpose, a subset of physiological variables (HR, HRV, SpO 2 , body movements) is derived from Polysomnography (PSG) and exploited for the development of rule-based algorithms. This reduced parameter set is selected considering further implementations on wearable off-the-shelf commercial devices.

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High-Performance File Searching with Rust: Parallelized Indexing for Enhanced Computational Efficiency

High-Performance File Searching with Rust: Parallelized Inde...

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Interdisciplinary Approaches in Technology and management for Social Innovation (IATMSI), IEEE Conference on

作者： Snehil Sinha Prabir Kalwani Aayush Shah Jesleena Gonsalves Dept. of Computer Engineering Mukesh Patel School of Technology Management and Engineering SVKM’s NMIMS University Mumbai India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Conventional file explorer tools have many limitations, from sluggish performance to cluttered user interfaces. The Windows File Explorer is often criticized for its slow performance, taking an exorbitant amount of time to load search results, especially for extensive file collections. In contrast, the Rust-based file searcher employs parallelization to rapidly parse the file system and build a comprehensive index. This index is stored in memory using a HashMap data structure, providing constant-time lookups. This study presents a high-performance alternative using the Rust programming language to address these shortcomings. The study shows the advantages of parallelization of search in Rust and then compares file search using Rust and traditional Windows file explorer on multiple parameters, including Search time, CPU usage, and Memory usage. The Rust-Based File Searcher provides faster results at around 80 to 180 milliseconds compared to 4-16 seconds using Windows File Search.

关键词： Technological innovation computer languages File systems User interfaces Programming Data structures Computational efficiency Indexing

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SignUp: A Sign Language Recognition Web App

SignUp: A Sign Language Recognition Web App

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Interdisciplinary Approaches in Technology and management for Social Innovation (IATMSI), IEEE Conference on

作者： Shloka Kanodia Ananya Joshi Neha Gadgil Hiral Modi Dept. of Computer Engineering Mukesh Patel School of Technology Management and Engineering SVKM’s NMIMS University Mumbai India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

"SignUp" is a web application designed to address the communication challenges faced by the deaf and mute community by providing a web application that allows real-time Indian Sign Language (ISL) recognition and translation to facilitate communication between the deaf and dumb and the people who aren’t proficient in sign language. This research paper is focusing on the app’s real-time sign language recognition capabilities, text and speech output features, and the educational module for learning ISL.

关键词： Sign language Technological innovation Accuracy Translation Text recognition Speech recognition Tutorials Real-time systems Long short term memory Testing

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Closed-Loop System Identification of an Unstable Nonlinear System Using Koopman Operator

Closed-Loop System Identification of an Unstable Nonlinear S...

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First International Symposium on Instrumentation, control, Artificial Intelligence, and Robotics (ICA-SYMP)

作者： Benjaset Maneeloke Sudchai Boonto Peerayot Sanposh Yodyium Tipsuwan Natthawut Chinthaned Warit Tanaprasitpattana Dept. of Electrical Engineering Kasetsart University Bangkok Thailand Dept. of Control Systems and Instrumentation Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Dept. of Computer Engineering Kasetsart University Bangkok Thailand

ISBN: (数字)9798331505400

ISBN: (纸本)9798331505417

This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlights the critical role of selecting appropriate observable functions to develop accurate and efficient Koopman models. We demonstrate that the resulting Koopman models exhibit excellent fitting and validation properties and retain the stabilizability of the original nonlinear systems. These models are verified through time and frequency responses under closed-loop control using a Linear Quadratic Regulator (LQR), confirming their effectiveness. Future work will extend this framework to more complex systems and incorporate machine learning techniques to refine the selection of observable functions. This approach aims further to enhance the adaptability and robustness of Koopman-based control strategies.

关键词： Time-frequency analysis Adaptation models Regulators Accuracy Fitting Machine learning Robustness Closed loop systems Complex systems Frequency control

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Kernel-based multi-step predictors for data-driven analysis and control of nonlinear systems through the velocity form

arXiv

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arXiv 2024年

作者： Verhoek, Chris Tóth, Roland The Control Systems group The Dept. of Electrical Engineering The Eindhoven University of Technology Netherlands The Institute for Computer Science and Control Budapest Hungary

We propose kernel-based approaches for the construction of a single-step and multi-step predictor of the velocity form of nonlinear (NL) systems, which describes the time-difference dynamics of the corresponding NL system and admits a highly structured representation. The predictors in turn allow to formulate completely data-driven representations of the velocity form. The kernel-based formulation that we derive, inherently respects the structured quasi-linear and specific time-dependent relationship of the velocity form. This results in an efficient multi-step predictor for the velocity form and hence for nonlinear systems. Moreover, by using the velocity form, our methods open the door for data-driven behavioral analysis and control of nonlinear systems with global stability and performance guarantees. © 2024, CC BY-NC-SA.

关键词： Nonlinear simulations

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