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A Web-Based Interface That Leverages Machine Learning to Assess an Individual’s Vulnerability to Brain Stroke

IEEE Access 2025年 13卷 87950-87964页

作者： Bhandari, Divyansh Agarwal, Arnav Reena Roy, R. Priyatharshini, Rajaram Rivero Cristian, Rodriguez Vellore Institute of Technology School of Electronics Engineering Tamil Nadu Chennai600127 India Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Chennai600127 India Cardiff Metropolitan University Centre for Engineering Research in Intelligent Sensors and Systems Cardiff School of Technologies CardiffCF5 2YB United Kingdom Cardiff Metropolitan University Cardiff School of Technologies CardiffCF5 2YB United Kingdom Universitat Politècnica de Catalunya Department of Mining Industrial and ICT Systems Engineering Barcelona08034 Spain

Cerebral stroke is a major global health issue, contributing to high mortality and long-term disability. Early identification of individuals at high risk of stroke can significantly improve preventive care outcomes. We present a web-based stroke risk assessment tool that uniquely combines an accessible user interface with robust machine learning modeling. The proposed platform leverages a novel combination of SMOTE oversampling and logistic regression to address class imbalance in patient health records, improving the detection of stroke risk factors over existing methods. We compare a range of algorithms-including traditional classifiers and deep learning models-and report comprehensive performance metrics (accuracy, precision, recall, F1-score, and AUC-ROC) for each. Our best model (logistic regression with SMOTE and standard scaling) achieves 93.2% accuracy with a substantially higher F1-score for the stroke-positive class than other models, indicating improved sensitivity to stroke cases. To bridge the gap between complex predictive models and end-users, we deploy this model in an intuitive web interface (built with Streamlit) that non-technical individuals and healthcare providers can easily use. This interface requires no specialized knowledge, preserves user privacy by avoiding any data storage, and provides clear explanations of results. By offering a practical and transparent tool for stroke risk screening, our work advances health informatics with an emphasis on accessibility, interpretability, and early intervention. Potential applications range from personal health self-assessment to integration in clinical workflows for preventive care, ultimately aiming to improve public health outcomes through early detection and intervention in stroke. © 2013 IEEE.

关键词： Health insurance

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A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 169-178页

作者： Mohammad Al-Sharman David Murdoch Dongpu Cao Chen Lv Yahya Zweiri Derek Rayside William Melek the Department of Electrical and Computer Engineering University of WaterlooWaterloo N2L 3G1Canada the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterloo N2L 3G1Canada the Cognitive Autonomous Driving Lab University of WaterlooWaterloo N2L 3G1Canada the School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 999002Singapore the Faculty of Science Engineering and ComputingKingston University LondonLondon SW153DWUK the Khalifa University Center for Autonomous Robotic Systems Department of Aerospace EngineeringKhalifa UniversityAbu Dhabi 127788UAE

In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the *** a typical CPS,the braking system is crucial for the vehicle design and safe ***,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of *** this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified *** techniques are utilized to obtain more accurate model for brake pressure state estimation *** proposed model is trained using real experimental training data which were collected via conducting real vehicle *** vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving *** on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated *** results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa.

关键词： Brake pressure state estimation cyber-physical system(CPS) deep learning dropout regularization approach

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A fast and accurate tube diameter visualization method for digestive system medical images

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2021年第9期141卷 982-991页

作者： Ueda, Mitsuru Kondo, Masafumi Kayano, Isao Sejima, Yoshihiro Yokogawa, Tomoyuki Sato, Yoichiro Sugihara, Yuusaku Matsumoto, Kazuyuki Graduate School of Computer Science and Systems Engineering Okayama Prefectural University 111 Kuboki Soja Okayama719-1197 Japan Faculty of Health Science and Technology Kawasaki University of Medical Welfare 288 Matsushima Kurashiki Okayama701-0193 Japan Faculty of Informatics Kansai University 2-1-1 Ryozenji-cho Osaka Takatsuki569-1095 Japan Department of Gastroenterology Okayama University Hospital 2-5-1 Shikata-cho Kita-ku Okayama700-8558 Japan

Although the tube diameter and stenosis rate are important observations in the diagnosis using medical images of digestive organ, such as digestive systems, the diagnosis is based on the physician’s subjective evaluation. On the other hand, automatic measurement of tube diameters by image processing has been used for blood vessels, which are tubular tissues similar to digestive systems, and it is also possible to visualize the vessel diameter by assigning pseudo-colors according to the length of the vessel. However, it is difficult to apply the existing diameter visualization methods directly to digestive system medical images due to the processing time and accuracy problems because the tubes are large and tortuous, unlike blood vessels. In this paper, we propose a method to measure the tube diameter quickly by dynamically calculating the next featured pixel using the history of the midpoints of the tube diameter line. Furthermore, we derive an approximate curve corresponding to the centerline of the tube from the history of the featured pixels and measure the tube diameter with high accuracy. We applied the proposed method to various types of digestive system medical images and confirmed that the proposed method could accurately measure and visualize the tube diameter along the shape of the tube and reduce the processing time by up to 99%. 2021 The Institute of Electrical Engineers of Japan.

关键词： Pixels

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Optics for terawatt-scale photovoltaics: review and perspectives

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Advances in Optics and Photonics 2025年第1期17卷 185-294页

作者： Jäger, Klaus Aeberhard, Urs Llado, Esther Alarcon Bläsi, Benedikt Burger, Sven Ehrler, Bruno Favre, Wilfried Fejfar, Antonín Gageot, Tristan Gordon, Ivan Helmers, Henning Höhn, Oliver Isabella, Olindo Jošt, Marko Ledinský, Martin Mandal, Jyotirmoy Manley, Phillip Muñoz, Delfina Omair, Zunaid Lizcano, Juan Camilo Ortiz Paetzold, Ulrich W. Raman, Aaswath P. Sai, Hitoshi Saive, Rebecca Schmid, Martina Yablonovitch, Eli Becker, Christiane Department Optics for Solar Energy Helmholtz-Zentrum Berlin für Materialien und Energie Kekuléstraße 5 Berlin12489 Germany Computational Nano Optics Zuse Institute Berlin Takustraße 7 Berlin14195 Germany Fluxim AG Katharina-Sulzer-Platz 2 Winterthur8400 Switzerland LMPV-Sustainable Energy Materials Department AMOLF Science Park 104 Amsterdam1098 XG Netherlands Fraunhofer Institute for Solar Energy Systems ISE Heidenhofstraße 2 Freiburg79100 Germany JCMwave GmbH Bolivarallee 22 Berlin14050 Germany Université Grenoble Alpes CEA LITEN Campus INES 50 avenue du Lac Léman Le Bourget-du-Lac73375 France FZU - Institute of Physics The Czech Academy of Sciences Na Slovance 1999/2 Prague 8182 00 Czech Republic IMEC/Energyville Thor Park 8320 Genk3600 Belgium Hasselt University Martelarenlaan 42 Hasselt3500 Belgium Photovoltaic Materials and Devices Laboratory Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands University of Freiburg Emmy-Noether-Str.2 Freiburg79110 Germany Faculty of Electrical Engineering University of Ljubljana Tržaška 25 Ljubljana1000 Slovenia Department of Civil and Environmental Engineering Princeton University E209A Engineering Quadrangle PrincetonNJ08544 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Institute of Microstructure Technology Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Light Technology Institute Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Materials Science and Engineering University of California Los AngelesCA90095 United States Ibaraki Tsukuba305-8568 Japan MESA+ Institute for Nanotechnology Inorganic Materials Science University of Twente NB Enschede7522 Netherlands University of Duisburg-Essen Forsthausweg 2 Duisburg47057 Germany Faculty 1 School of Engineering – Energy and Information Hochschule für Technik und Wirtschaft Berlin

In this section, we described the various device architectures in production for crystalline-silicon PV as well as the various absorber materials being used and developed for thin-film PV. We also explained why multijunction PV technology is considered the future of PV technology. We identified four major technological challenges (Fig. 1) for future mass production and deployment of PV technology in order to achieve the goal of climate neutrality and indicated how optics could help resolve these challenges. The four main challenges (Fig. 1) are: • Sustainable production of PV systems;• Higher energy conversion efficiencies;• Higher energy output and operational lifetime;• Integration of PV systems in their environment. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Energy conversion efficiency

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Implementation of a Scalable Platform for Real-Time Monitoring of Machine Tools

SSRN

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SSRN 2024年

作者： Tapia, Endika Lopez-Novoa, Unai Sastoque-Pinilla, Leonardo López-De-Lacalle, Luis Norberto Aeronautics Advanced Manufacturing Center University of the Basque Country Bizkaia Science and Technology Park 202 Zamudio48170 Spain Department of Computer Languages and Systems University of the Basque Country Rafael Moreno pasealekua 2-3 Bilbao48013 Spain Department of Mechanical Engineering University of the Basque Country Torres Quevedo enparantza s/n Bilbao48013 Spain

In the new hyper connected factories, data gathering, and prediction models are key to keeping both productivity and piece quality. This paper presents a software platform that monitors and detects outliers in an industrial manufacturing process using scalable software tools. The platform collects data from a machine, processes it, and displays visualizations in a dashboard along with the results. A statistical method is used to detect outliers in the manufacturing process. The performance of the platform is assessed in two ways: firstly by monitoring a five-axis milling machine and secondly, using simulated tests. Former tests prove the suitability of the platform and reveal the issues that arise in a real environment, and latter tests prove the scalability of the platform with higher data processing needs than the previous ones. © 2024, The Authors. All rights reserved.

关键词： Machine tools

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Significance of Single Interval Discrete Attributes: Case Study on 2-Level Discretisation

SSRN

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SSRN 2022年

作者： Stańczyk, Urszula Zielosko, Beata Baron, Grzegorz Department of Computer Graphics Vision and Digital Systems Silesian University of Technology Akademicka 2A Gliwice44-100 Poland Institute of Computer Science University of Silesia in Katowice Bȩdzińska 39 Sosnowiec41-200 Poland

Supervised discretisation is widely considered as far more advantageous form of transformation than unsupervised processing of attributes. When evaluating candidate cut-points for splitting the ranges of values of discretised features, the supervised methods help to preserve informative content of a variable, which is useful for classification. After a discretisation process, based on employed criteria, some attributes can be found as irrelevant, with all their values represented in discrete domain by a single interval. In consequence, such variables are removed from considerations, and no knowledge is mined from them. The paper presents research works focused on extended 2-level transformations of attributes values, with combining supervised with unsupervised discretisation strategies. For all variables with single intervals returned from supervised algorithms, the ranges of values were divided by unsupervised methods with varying numbers of bins. Resulting variants of data were subjected to selected data mining techniques and performance of chosen classifiers evaluated and compared. The experiments were performed on stylometric task of authorship attribution. © 2022, The Authors. All rights reserved.

关键词： Pattern recognition

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Controlling Unknown Quantum States via Data-Driven State Representations

arXiv

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arXiv 2024年

作者： Zhu, Yan Xiao, Tailong Zeng, Guihua Chiribella, Giulio Wu, Ya-Dong QICI Quantum Information and Computation Initiative Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong State Key Laboratory of Advanced Optical Communication Systems and Networks Institute for Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Hefei National Laboratory Hefei230088 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Department of Computer Science Parks Road OxfordOX1 3QD United Kingdom Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai200240 China

Accurate control of quantum states is crucial for quantum computing and other quantum technologies. In the basic scenario, the task is to steer a quantum system towards a target state through a sequence of control operations. Determining the appropriate operations, however, generally requires information about the initial state of the system. Gathering this information becomes increasingly challenging when the initial state is not a priori known and the system’s size grows large. To address this problem, we develop a machine-learning algorithm that uses a small amount of measurement data to construct its internal representation of the system’s state. The algorithm compares this data-driven representation with a representation of the target state, and uses reinforcement learning to output the appropriate control operations. We illustrate the effectiveness of the algorithm showing that it achieves accurate control of unknown many-body quantum states and non-Gaussian continuous-variable states using data from a limited set of quantum measurements. © 2024, CC BY-NC-SA.

关键词： Reinforcement learning

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Toward Mixture-of-Experts Enabled Trustworthy Semantic Communication for 6G Networks

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IEEE Network 2024年

作者： He, Jiayi Luo, Xiaofeng Kang, Jiawen Du, Hongyang Xiong, Zehui Chen, Ci Niyato, Dusit Shen, Xuemin Guangdong University of Technology School of Automation Guangzhou510006 China Nanyang Technological University College of Computing and Data Science Singapore639798 Singapore Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore487372 Singapore University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Through nonlinear mapping of semantic representations, Deep Learning (DL)-based semantic communications further enhance communication efficiency. However, the vulnerability of DL models to security threats, such as adversarial attacks, poses significant challenges for practical applications of SemCom systems. These vulnerabilities allow attackers to tamper with messages and eavesdrop on private information, especially in wireless communication scenarios. Although existing defenses attempt to address specific threats, they often fail to simultaneously handle multiple heterogeneous attacks. To overcome this limitation, we propose a novel Mixture-of-Experts (MoE)-based SemCom system, comprising a gating network and multiple experts, each specializing in different security challenges. The gating network adaptively selects suitable experts to counter heterogeneous attacks based on user-defined security requirements. Multiple experts collaborate to accomplish semantic communication tasks while meeting the security requirements of users. A case study in vehicular networks demonstrates the efficacy of the MoE-based SemCom system. Simulation results show that the proposed MoE-based SemCom system effectively mitigates concurrent heterogeneous attacks, with minimal impact on downstream task accuracy. © 1986-2012 IEEE.

关键词： Vehicular ad hoc networks

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Novel symmetric numerical methods for solving symmetric mathematical problems

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International Journal of Circuits, systems and Signal Processing 2021年 15卷 1545-1557页

作者： Ibrahimov, V.R. Mehdiyeva, G.Y.U. Yue, Xiao-Guang Kaabar, Mohammed K.A. Noeiaghdam, Samad Juraev, Davron Aslonqulovich Institute of Control Systems named after Academician A.Huseynov BakuAZ1141 Azerbaijan Computational mathematics Baku State University BakuAZ1148 Azerbaijan Department of Computer Science and Engineering School of Sciences European University Cyprus Nicosia1516 Cyprus Institute of Mathematical Sciences Faculty of Science University of Malaya Kuala Lumpur50603 Malaysia Department of Mathematics and Statistics Washington State University PullmanWA99163 United States Industrial Mathematics Laboratory Baikal School of BRICS Irkutsk National Research Technical University Irkutsk664074 Russia Department of Applied Mathematics and Programming South Ural State University Lenin Prospect 76 Chelyabinsk454080 Russia Department of Natural Science Disciplines Higher Military Aviation School of the Republic of Uzbekistan Karshi City180100 Uzbekistan

—The mathematical model for many problems is arising in different industries of natural science, basically formulated using differential, integral and integro-differential equations. The investigation of these equations is conducted with the help of numerical integration theory. It is commonly known that a class of problems can be solved by applying numerical integration. The construction of the quadrature formula has a direct relation with the computation of definite integrals. The theory of definite integrals is used in geometry, physics, mechanics and in other related subjects of science. In this work, the existence and uniqueness of the solution of above-mentioned equations are investigated. By this way, the domain has been defined in which the solution of these problems is equivalent. All proposed four problems can be solved using one and the same methods. We define some domains in which the solution of one of these problems is also the solution of the other problems. Some stable methods with the degree p © 2021, North Atlantic University Union NAUN. All rights reserved.

关键词： Integrodifferential equations

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Coordinated control design for steering and torque-vectoring in Model-Free Control structure*

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IFAC-PapersOnLine 2022年第6期55卷 496-501页

作者： Tamás Hegedűs Dániel Fényes Balázs Németh Zoltán Szabó Péter Gáspár Institute for Computer Science and Control (SZTAKI) Eötvös Loránd Research Network (ELKH) Budapest Hungary Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Stoczek u. 2 H-1111 Budapest Hungary

Model-Free Control (MFC) approach is a novel technique to handle nonlinearities and uncertainties in control systems in order to provide enhanced performance level. The design of MFC is based on an ultra-local model, which is an approximation of the dynamics of the controlled system for a short period of time. This structure also involves a model-based robust control, which guarantees the accurate tracking performance of the closed-loop system. In this paper, a novel technique is proposed for designing the robust control for taking into account the varying characteristics of the ultra-local model. A novel modeling method is presented, which combines the original plant of the controlled system and the ultra-local model. Then, a robust control design is proposed, by which the tracking performance and the robustness of the closed-loop system can be guaranteed. The design steps and effectiveness of the proposed control strategy is demonstrated through a vehicle-oriented control problem using the high-fidelity simulation software, CarMaker.

关键词： model-free control torque vectoring automated vehicles robust control

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