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Towards hybrid approach based SVM and Radiomics features for COVID-19 classification and segmentation

International Journal of Hybrid Intelligent systems 2024年第PRE-PRESS期Pre-press卷 1-20页

作者： Azizi, Ridha Sakly, Houneida Wajdi, Abdallah Ahmed Hmida, Alaa Eddinne Ben Bouhlel, Med Salim Research Lab: Smart systems for Engineering and E-health based on Technologies of Image and Telecomunications (SETIT) ISBS Sfax University Tunisia Center for Research on Microelectronics and Nanotechnology (CRMN) Sousse Technopole Sahloul Sousse Tunisia RIADI Laboratory ENSI Manouba University Campus Universitaire de la Manouba La Manouba Tunisia Department IT Higher Institute of Computer Science and Mathematics of Monastir Tunisia Department IT Higher Institute of Computer Science and Mathematics of Monastir Tunisia

In the battle against the COVID-19 pneumonia outbreak, which is brought on by the coronavirus strain SARS-Cov-2, radiological chest exams, such as chest X-rays, are crucial. In order to understand the unique radiographic characteristics of COVID-19, this research looks into classification models to distinguish chest X-ray images based on Radiomics features. This study is performed with datasets composed of 136 segmented chest X-rays, which were used to train and test the categorization algorithms. First and second-order statistical texture characteristics were extracted from the right (R), left (L), superior, middle, and bottom lung zones for each lung side using the Pyradiomics collection. Data was divided into training (80%) and test (20%) groups for feature selection. After assessing the respective feature significance and confirmation accuracy, the most pertinent Radiomics features were chosen. A model of lung segmentation based grey level pixels was used to evaluate support vector machines (SVM) as possible classifiers (AUC = 83.7%). Our research reveals a preference for the upper lung zone and a preponderance of Radiomics feature selection in the right lung. Our future research will concentrate on COVID-19 categorization and segmentation for more precise forecast using a hybrid method based on SVM and Radiogenomics features.

关键词： COVID-19 radiomics pyradiomics classifiers segmentation SVM radiogenomics

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Bayesian hypergame approach to equilibrium stability and robustness in moving target defense

Bayesian hypergame approach to equilibrium stability and rob...

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IEEE Conference on Decision and Control

作者： Hanzheng Zhang Zhaoyang Cheng Guanpu Chen Karl Henrik Johansson Shanghai Research Institute for Autonomous Intelligent Systems Tongji University Shanghai China Academy of Mathematics and System Science Chinese Academy of Science University of Chinese Academy of Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and the Digital Futures Stockholm Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelberg game model for incomplete information and then employ a hypergame reformulation to address asymmetric cognition. With the core concept of the hyper Bayesian Nash equilibrium (HBNE), a condition for achieving both the strategic and cognitive stability in equilibria can be realized by solving linear equations. Moreover, to deal with players’ underlying perturbed knowledge, we study the equilibrium robustness by presenting a condition of robust HBNE under the given configuration. Experiments evaluate our theoretical results.

关键词： Games Nash equilibrium Stability analysis Robustness Mathematical models Cognition Bayes methods

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Bayesian hypergame approach to equilibrium stability and robustness in moving target defense

arXiv

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arXiv 2024年

作者： Zhang, Hanzheng Cheng, Zhaoyang Chen, Guanpu Johansson, Karl Henrik Shanghai Research Institute for Autonomous Intelligent Systems Tongji University Shanghai China Academy of Mathematics and System Science Chinese Academy of Science University of Chinese Academy of Science Beijing China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology The Digital Futures Stockholm Sweden

关键词： Nash equilibrium

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Cache-It: A Distributed Architecture for Proactive Edge Caching in Heterogeneous Iot Scenarios

SSRN

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SSRN 2023年

作者： Zyrianoff, Ivan Gigli, Lorenzo Montori, Federico Sciullo, Luca Kamienski, Carlos Di Felice, Marco Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic Systems "Ercole De Castro" University of Bologna Italy SP Santo André Brazil

The Cloud-to-Things (C2T) continuum combines the proximity of edge infrastructure to the devices with cloud resources to optimize data processing and response time in the Internet of Things (IoT). Proactive edge caching is a potential solution for meeting latency constraints in C2T environments, enabling efficient data processing and storage while reducing redundant computation and cost. However, while 5G/6G infrastructural aspects and caching strategies are extensively studied, no frameworks facilitate the design and deployment of caching strategies or addresses IoT unique requirements. This paper proposes CACHE-IT, a proactive edge caching framework that decouples the caching strategy algorithm from the underlying architecture, enabling customization based on application-specific requirements. Through extensive simulations, we analyzed the impact of different configurations on system metrics and verified that the CACHE-IT positively impacts the system latency and hit rate. By implementing a scenario-specific caching strategy, we illustrate the CACHE-IT deployment in a real-world Structure Health Monitoring (SHM) system. The evaluation demonstrates that it CACHE-IT custom strategy outperforms traditional caching mechanisms. © 2023, The Authors. All rights reserved.

关键词： Internet of things

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Non-Hermitian chiral degeneracy of gated graphene metasurfaces

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Light(science & Applications) 2023年第5期12卷 766-775页

作者： Soojeong Baek Sang Hyun Park Donghak Oh Kanghee Lee Sangha Lee Hosub Lim Taewoo Ha Hyun Sung Park Shuang Zhang Lan Yang Bumki Min Teun-Teun Kim Department of Mechanical Engineering Korea Advanced Institute of Science and Technology(KAIST)Daehak-ro 291Daejeon 34141Republic of Korea Department of Electrical and Computer Engineering University of Minnesota200 Union street SEMinneapolisMN 55455USA Harvard Institute of Medicine Harvard Medical SchoolHarvard UniversityBrigham and Women's Hospital25 Shattuck StreetBostonMA 02215USA Center for Integrated Nanostructure Physics Institute for Basic Science(IBS)Sungkyunkwan UniversitySeobu-ro 2066Suwon 16419Republic of Korea Samsung Advanced Institute of Technology Samsung ElectronicsSamsung-roSuwon 16678Republic of Korea Department of Physics The University of Hong KongPokfulam RoadHong Kong Special Administrative RegionChina Department of Electrical and Systems Engineering Washington University1 Brookings DriveSaint LouisMO 63130USA Department of Physics Korea Advanced Institute of Science and Technology(KAIST)Daehak-ro 291Daejeon 34141Republic of Korea Department of Physics University of UlsanDaehakroUlsan 44610Republic of Korea Korea Research Institute of Standards and Science(KRISS) Gajeong-ro 267Daejeon 34113Republic of Korea

Non-Hermitian degeneracies,also known as exceptional points(EPs),have been the focus of much attention due to their singular eigenvalue surface ***,as pertaining to a non-Hermitian metasurface platform,the reduction of an eigenspace dimensionality at the EP has been investigated mostly in a passive repetitive ***,we propose an electrical and spectral way of resolving chiral EPs and clarifying the consequences of chiral mode collapsing of a non-Hermitian gated graphene *** specifically,the measured non-Hermitian Jones matrix in parameter space enables the quantification of nonorthogonality of polarisation eigenstates and half-integer topological charges associated with a chiral ***,the output polarisation state can be made orthogonal to the coalesced polarisation eigenstate of the metasurface,revealing the missing dimension at the chiral *** addition,the maximal nonorthogonality at the chiral EP leads to a blocking of one of the cross-polarised transmission pathways and,consequently,the observation of enhanced asymmetric polarisation *** anticipate that electrically controllable non-Hermitian metasurface platforms can serve as an interesting framework for the investigation of rich non-Hermitian polarisation dynamics around chiral EPs.

关键词： structure chiral integer

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Challenges and Limitations in Speech Recognition Technology:A Critical Review of Speech Signal Processing Algorithms,Tools and systems

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computer Modeling in engineering & sciences 2023年第5期135卷 1053-1089页

作者： Sneha Basak Himanshi Agrawal Shreya Jena Shilpa Gite Mrinal Bachute Biswajeet Pradhan Mazen Assiri Computer Science and Information Technology Department Symbiosis Institute of TechnologySymbiosis International(Deemed University)Pune412115India Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)Pune412115India Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNew South Wales2007Australia Center of Excellence for Climate Change Research King Abdulaziz UniversityJeddah21589Saudi Arabia Earth Observation Centre Institute of Climate ChangeUniversity Kebangsaan MalaysiaBangiSelangor43600Malaysia

Speech recognition systems have become a unique human-computer interaction(HCI)*** is one of the most naturally developed human abilities;speech signal processing opens up a transparent and hand-free computation *** paper aims to present a retrospective yet modern approach to the world of speech recognition *** development journey of ASR(Automatic Speech Recognition)has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper.A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented,along with a brief discussion of various modern-day developments and applications in this *** review paper aims to summarize and provide a beginning point for those starting in the vast field of speech signal *** speech recognition has a vast potential in various industries like telecommunication,emotion recognition,healthcare,etc.,this review would be helpful to researchers who aim at exploring more applications that society can quickly adopt in future years of evolution.

关键词： Speech recognition automatic speech recognition(ASR) mel-frequency cepstral coefficients(MFCC) hidden Markov model(HMM) artificial neural network(ANN)

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Leveraging Artificial Intelligence for Advancements in Mental Disorders: A Short Review 16

Leveraging Artificial Intelligence for Advancements in Menta...

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16th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Kasereka, Selain K. Tshibangu, Kenny N. Nyembo, Myriam M. Tshitenge, Lionel K. Muzindusi, Marina K. Ilunga, Godwill W.K. Amor, Soufian Ben Bope, Christian D. Tashev, Tasho Kyamakya, Kyandoghere Mathematics Statistics and Computer Science Department University of Kinshasa Kinshasa Democratic Republic Congo Faculty of English Engineering Studies Technical University of Sofia Sofia Bulgaria ABIL Research Center Kinshasa Democratic Republic Congo Faculty of Computer Science Université Nouveaux Horizons Lubumbashi Democratic Republic Congo LI-PaRAD Université de Versailles-Saint-Quentin-en-Yvelines France Institute of Smart Systems Technologies University of Klagenfurt Klagenfurt Austria Polytechnic Faculty University of Kinshasa Kinshasa Democratic Republic Congo

This study explores the expanding influence of artificial intelligence (AI) on the comprehension and management of mental disorders conditions. By analyzing recent advancements, this article highlights how AI technologies are being applied to diagnose, model, predict, and treat conditions, such as depression, anxiety, and bipolar disorder. It examines innovative approaches, including AI-powered mental wellness apps, that enable users to monitor their symptoms and access personalized support. Additionally, it discusses research on advanced algorithms designed to analyze online social interactions to identify early signs of psychological distress and to facilitate timely interventions. The paper also addresses the challenges involved in integrating AI into mental healthcare and highlights ethical and legal concerns that should be addressed when developing AI mental health models. © 2025 Elsevier B.V.. All rights reserved.

关键词： Backpropagation

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Tan, Qingshan Li, Changhe Zeng, Sanyou Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

ISBN: (纸本)9798350314588

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front. © 2023 IEEE.

关键词： Multiobjective optimization

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Modular Multilevel DC-DC Converter with Inherent Bipolar Operation Capability for Resilient Bipolar MVDC Grids

Modular Multilevel DC-DC Converter with Inherent Bipolar Ope...

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作者： Zhao, Shanshan Chen, Yu Cui, Shenghui Hu, Jingxin State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology China Seoul National University Department of Electrical and Computer Engineering Korea Republic of Institute for Power Generation and Storage Systems E. on Energy Research Center RWTH Aachen University Germany

Bipolar medium-voltage dc (MVDC) distribution systems are of great interests nowadays due to its high availability and reliability. A bipolar MVDC grid can be established by the installation of power-balancers or directly by converters with inherent bipolar operation capability to avoid the extra cost and volume. Therefore, this paper proposes a modular multilevel dc-dc converter (MMDC) with inherent bipolar operation capability for the interconnection of bipolar MVDC grids and LVDC girds. Considering that the MMDC is normally only capable of operating with monopole MVDC distribution systems due to the symmetric structure and operation scheme, a center-Tapped high-frequency interface transformer is employed on the MV side of the MMDC. Based on the concept of the flux dc-bias cancellation, a dedicated operation method is proposed, whereby the power flows of the two MVDC poles can be regulated independently with a simple control scheme, and no penalty of increased current rating is imposed on the semiconductor devices or the interface transformer compared to the conventional MMDC with monopole operation. Additionally, the MMDC can realize single-pole operation in case one pole is faulty and deliver at least 50% of the rated power capacity, which significantly enhance the reliability and availability of the power delivery. The validity of the proposed bipolar operation scheme of the MMDC has been verified by both simulations and experiments with a down-scale prototype. © 2017 CPSS.

关键词： Poles

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State-space models are accurate and efficient neural operators for dynamical systems

arXiv

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arXiv 2024年

作者： Hu, Zheyuan Daryakenari, Nazanin Ahmadi Shen, Qianli Kawaguchi, Kenji Em Karniadakis, George Department of Computer Science National University of Singapore Singapore119077 Singapore Center for Biomedical Engineering School of Engineering Brown University ProvidenceRI02912 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory RichlandWA United States

Physics-informed machine learning (PIML) has emerged as a promising alternative to classical methods for predicting dynamical systems, offering faster and more generalizable solutions. However, existing models, including recurrent neural networks (RNNs), transformers, and neural operators, face challenges such as long-time integration, long-range dependencies, chaotic dynamics, and extrapolation, to name a few. To this end, this paper introduces state-space models implemented in Mamba for accurate and efficient dynamical system operator learning. Mamba addresses the limitations of existing architectures by dynamically capturing long-range dependencies and enhancing computational efficiency through reparameterization techniques. To extensively test Mamba and compare against another 11 baselines, we introduce several strict extrapolation testbeds that go beyond the standard interpolation benchmarks. We demonstrate Mamba’s superior performance in both interpolation and challenging extrapolation tasks. Mamba consistently ranks among the top models while maintaining the lowest computational cost and exceptional extrapolation capabilities. Moreover, we demonstrate the good performance of Mamba for a real-world application in quantitative systems pharmacology for assessing the efficacy of drugs in tumor growth under limited data scenarios. Taken together, our findings highlight Mamba’s potential as a powerful tool for advancing scientific machine learning in dynamical systems modeling. (The code will be available at https://***/zheyuanhu01/State_ Space_Model_Neural_Operator upon acceptance.) © 2024, CC BY.

关键词： Recurrent neural networks

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