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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Boesso, Simone Farina, Lorenzo Petti, Manuela Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350386226

Radiomics represents a specialized branch of medical imaging where quantitative features are extracted from images. Performing a classification using radiomics means solving two common problems: the imbalanced setting, and the large number of features that would increase the risk of overfitting. Moreover, since its main application and impact are in clinical field, there is the need of interpretable models for explaining their results. The aim of this study is to compare two modelling approaches: one based on a logistic regression model, known for its simplicity and interpretability, and RUSBoost, an ensemble method designed to handle class imbalance with potentially higher complexity, in order to answer the question whether higher complexity and lower interpretability are justified when dealing with radiomics data. Additionally, due to the large literature suggesting it, we analyze the impact of a feature selection step applied to these two classifiers. Test performances measured across 20 repeated splits on two datasets show how the RUSBoost approach is able to capture more detailed patterns of the data but this is highly dependent on the dataset at hand. © 2024 IEEE.

关键词： Logistic regression

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Closed-Loop System Identification of an Unstable Nonlinear System Using Koopman Operator 4

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

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4th International Symposium on Instrumentation, control, Artificial Intelligence, and Robotics, ICA-SYMP 2025

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

ISBN: (纸本)9798331505400

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. © 2025 IEEE.

关键词： Dynamic mode decomposition

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Exploring the Feasibility of Sleep Quality Evaluation with a Reduced Parameter Set 9

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

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9th IEEE Smart World Congress, SWC 2023

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

ISBN: (纸本)9798350319804

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, SpO2, 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. © 2023 IEEE.

关键词： ECG Hypopnea IOT Obstructive Sleep Apnea Obstructive Sleep Apnea Syndrome Sleep Sleep Macro Pattern Sleep Micro Pattern Sleep Quality Smartwatch SpO2

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Challenges in AI-supported Process Analysis in the Italian Judicial System: what After Digitalization?

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Digital Government: Research and Practice 2024年第1期5卷 1-10页

作者： Bianchini, Devis Bono, Carlo Campi, Alessandro Cappiello, Cinzia Ceri, Stefano De Luzi, Francesca Mecella, Massimo Pernici, Barbara Plebani, Pierluigi Dept. of Computer Science University of Brescia Via Branze 38 Brescia25123 Italy Dept. of Electronics Information and Bioengineering Politecnico di Milano Piazza Leonardo da Vinci 32 Milan20133 Italy Dept. of Computer Control and Management Engineering Sapienza Universitá di Roma Via Ariosto 25 Roma00185 Italy

In this commentary article, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges' workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification. Copyright © 2024 held by the owner/author(s).

关键词： Process monitoring

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Optimal control Strategy to Reduce HIV-1 Infection in the Brain 9

Optimal Control Strategy to Reduce HIV-1 Infection in the Br...

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Baiocchi, Sofia Blengini, Federica Caleno, Francesca Di Giamberardino, Paolo Iacoviello, Daniela Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350311402

The study of Human Immunodeficiency Virus (HIV) and of its progression to Acquired Immune Deficiency Syndrome (AIDS) has been a challenge by scientists since the early 1980s;the improvements in the knowledge of its transmission and of the evolution of the disease have strongly reduced the mortality, even if up to know an effective vaccine is not available. Nevertheless, the Highly Active Antiretroviral Therapy (HAART) allows a high life expectancy. Some of the mechanisms of HIV reproduction are under investigation and recent observations are suggesting the existence of virus reservoir in the brain, the liver, the lungs and the gut. In particular, due to untreated amounts of virus, neurocognitive disorders as well as motor nerves diseases and weakness in muscles are improved in patients already weakened. In this paper it is considered a mathematical modelling to study the within-host viral dynamics, analysing the dynamics of the CD4-T cells, of the macrophages both inside and outside the brain, uninfected and infected, along with the virions carrying on the infection. An optimal control strategy is proposed and implemented,aiming at maximizing the number of healthy cells, while reducing the number of infected ones, scheduling suitably the therapy. © 2023 IEEE.

关键词： Diseases

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A PID control Algorithm for Path Tracking of a Nonholonomic Car-Like Robot 1

A PID Control Algorithm for Path Tracking of a Nonholonomic ...

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1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Siradjuddin, Indrazno Prayoga, Dimas Adi Wibowo, Sapto Syaifudin, Yan Watequlis Wicaksono, Rendi Pambudi Achmadiah, Mas Nurul State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Madiun Dept. of Computer Control Engineering Madiun Indonesia

ISBN: (纸本)9798350365191

A car-like robot with an Ackermann steering system is a type of nonholonomic which is characterised by a set of first-order differential constraints on its configuration variables, which are not integrable. This distinctive characteristic gives rise to complex issues in the construction of feedback controllers. This research proposes reactive control using a feedback controller using PID algorithm for a car-like robot navigation. The proposed method controls the steering angle of the car-like robot to follow the prescribed path with a constant longitudinal robot velocity. The open-loop car-like dynamical system has been formulated in the form of state-space model. Two PID controllers in parallel computed the lateral position error and the yaw angle error. The summation of the two outputs from the PID controllers was inputted into the state-space model. The PID controller parameters were selected based on trial and error. The simulation results confirm the effectiveness of the proposed control algorithm. © 2024 IEEE.

关键词： Three term control systems

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Fast and Accurate LSTM Meta-modeling of TNF-induced Tumor Resistance In Vitro

Fast and Accurate LSTM Meta-modeling of TNF-induced Tumor Re...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Abrate, Marco P. Smeriglio, Riccardo Bardini, Roberta Savino, Alessandro Di Carlo, Stefanoi University College London Dept. of Cell and Developmental Biology London United Kingdom Politecnico di Torino Dept. of Control and Computer Engineering Turin Italy

ISBN: (纸本)9798350386226

Multi-level, hybrid models and simulations, among other methods, are essential to enable predictions and hypothesis generation in systems biology research. However, the computational complexity of these models poses a bottleneck, limiting the applicability of methodologies relying on large number of simulations, such as the Optimization via Simulation (OvS) of complex biological processes. Meta-models based on approximate surrogate models simplify multi-level simulations, maintaining accuracy while reducing computational costs. Among Artificial Neural Networks (ANNs), Long Short-Term Memory (LSTM) networks are well suited to handle sequential data, which often characterizes biological simulations. This paper presents an LSTM-based surrogate modeling approach for multi-level simulations of complex biological processes. Validation relies on the simulation of Tumor Necrosis Factor (TNF) administration to a 3T3 mouse fibroblasts tumor spheroid based on PhysiBoSS 2.0, a hybrid agent-based multi-level modeling framework. Results show that the proposed LSTM meta-model is accurate and fast compared with the simulator. In fact, it infers simulated behavior with an average relative error of 7.5%. Moreover, it is at least five orders of magnitude faster. Even considering the cost of training, this approach provides a faster, more accurate, and reusable surrogate of multi-scale simulations in computationally complex tasks, such as model-based OvS of biological processes. © 2024 IEEE.

关键词： Tumors

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Effectiveness of computer-based e-Learning and Virtual Reality Training System for the Preparatory Phase of a Training on Maintenance Procedure

Effectiveness of Computer-based e-Learning and Virtual Reali...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Prattico, Filippo Gabriele Di Cosmo, Debora Piviotti, Matteo La Rosa, Giuseppe Lamberti, Fabrizio Politecnico di Torino Dept. of Control and Computer Engineering Turin Italy Leonardo S.p.a Turin Italy

ISBN: (纸本)9798350324136

This work investigates the effectiveness of two training systems based on consumer hardware technologies, a first one using computer-Based Learning (CBL) and the other exploiting Virtual Reality (VR). A user study was executed in order to compare the two training and analyze the most suitable approach for the learning of preparatory material in the context of an industrial assembly and maintenance (IMA) procedure. The results highlighted that, although trainees using VR experienced higher levels of cognitive processing and attention, the knowledge gain of CBL was comparable to that of VR for the preliminary phase training. Nonetheless, VR was still able to provide better learning gains in terms of procedural skills compared to CBL. © 2024 IEEE.

关键词： asynchronous distance learning computer aided training industrial assembly and maintenance preparatory material

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High Efficiency and High Gain Hybrid DC-DC Converter with Switched Capacitor 8

High Efficiency and High Gain Hybrid DC-DC Converter with Sw...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Rodrigues, Brenna Theodora MacHado Matos Moura, Mauricio Albuquerque Sá, Edilson Mineiro De Sousa, Kleber Cesar Alves Dept. Electrical and Computer Engineering Sobral Brazil Federal Institute of Caera Dept. Control and Industrial Processes Sobral Brazil

ISBN: (纸本)9798350321128

This work presents the study and development of a high-gain hybrid DC-DC converter with switched capacitor for photovoltaic energy applications. Qualitative analyzes and quantitative values of the converter are proposed. The proposed converter is based on the converter boost integrated into switched capacitive cells with the addition of a small inductor resonant. A mathematical modeling of the converter was developed to determine the value of the resonant inductance, where the converter was analyzed for inductance values of 1uH at 2uH. This proposal presented some advantages: such as extended static gain, reduction of voltage stress in semiconductors and reduction of current peaks in switches. A 200 W prototype was developed and its respective results are presented. Maximum efficiency obtained was 97.1% for a voltage gain of 10. © 2023 IEEE.

关键词： boost converter efficiency high gain converter hybrid DC-DC converter switched capacitor

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Robotic Arm Dataset (RoAD): A Dataset to Support the Design and Test of Machine Learning-Driven Anomaly Detection in a Production Line 49

Robotic Arm Dataset (RoAD): A Dataset to Support the Design ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Mascolini, Alessio Gaiardelli, Sebastiano Ponzio, Francesco Dall'ora, Nicola MacIi, Enrico Vinco, Sara Di Cataldo, Santa Fummi, Franco Polytechnic of Turin Dept. of Control and Computer Engineering Italy University of Verona Dept. of Engineering for Innovation Medicine Italy Polytechnic of Turin Dept. of Regional and Urban Studies and Planning Italy

ISBN: (纸本)9798350331820

The early detection of anomalous behaviors from a production line is a fundamental aspect of Industry 4.0, facilitated by the collection of massive amounts of data enabled by the Industrial Internet of Things. Nonetheless, the design and validation of anomaly detection algorithms, mostly based on sophisticated Machine Learning models, heavily rely on the availability of annotated datasets of realistic anomalies, which is very difficult to obtain in a real production line. To address this problem, we introduce the Robotic Arm Dataset (RoAD), specifically designed to support the development and validation of Multivariate Time Series Anomaly Detection (MTSAD) algorithms. We collect and annotate a large number of data and metadata to characterize the motion and energy consumption of a collaborative robotic arm in a full-fledged production line and annotate a comprehensive set of healthy as well as realistic anomalies scenarios. To prove the significance of RoAD and encourage future developments, we benchmark several state-of-the-art anomaly detection algorithms on our newly introduced dataset, and we freely release it to the scientific community. © 2023 IEEE.

关键词： Process monitoring

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