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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Cruz, Ernesto Monroy Carrillo, Luis Rodolfo Garcia Quesada, Eduardo Steed Espinoza Hidalgo Mexico New Mexico State University Klipsch School of Electrical and Computer Engineering New Mexico United States Center of Research and Advanced Studies of the National Polytechnic Institute Mexico National Council of Humanities Science and Technology Mexico

ISBN: (纸本)9798350335446

The task of enabling a multi-agent system for entrapping and escorting static/dynamic targets in the context of cluster space control is addressed. The proposed methodology consists of two main strategies. On one hand, the entrapping and escorting problems are specified in terms of cluster parameter trajectories, resulting in individual robot motions capable of satisfying the required multi-agent formation behavior. On the other hand, a fuzzy logic controller is designed in order to deal with the uncertainty in the model of the platform used in laboratory tests. Experimental results showing a team of three ground mobile robots entrapping a static target, as well as escorting a dynamic target demonstrate the effectiveness of the proposed control scheme. © 2023 IEEE.

关键词： Multi agent systems

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A Stable Discontinuous Galerkin Time-Domain Method for Simulation of Thin Conductive Layers

A Stable Discontinuous Galerkin Time-Domain Method for Simul...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2022

作者： Özakin, M. Burak Chen, Liang Ahmed, Shehab Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955 Saudi Arabia Ali I. Al-Naimi Petroleum Engineering Research Center Thuwal23955 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A conductive layer that is much thinner than the skin depth is often incorporated into electromagnetic solvers as a resistive boundary condition (RBC) to avoid fine meshes (and consequently small time steps for time-domain methods). When the discontinuous Galerkin time-domain (DGTD) method, which relies on an explicit Runge-Kutta (RK) scheme for time integration, is used in a simulation involving an RBC surface with high conductivity, the solution becomes unstable. In this work, to circumvent this bottleneck, a locally-implicit time marching scheme is developed. The proposed method uses implicit Euler backward and explicit Euler forward schemes to discretize the time derivatives in local DG equations associated with the elements that "touch"and do not "touch"the RBC surface, respectively. This yields a locally-implicit Euler (LIME) time marching scheme that maintains its stability in the presence of a highly conductive layer. Indeed, numerical results demonstrate that LIME-DGTD is more stable than RK-DGTD for a transmission problem involving a thin metal sheet. © 2022 IEEE.

关键词： Lime

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Cyberattack Aware Load Frequency Control in Power Systems 58

Cyberattack Aware Load Frequency Control in Power Systems

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Fahim, Shahriar Rahman Atat, Rachad Kececi, Cihat Takiddin, Abdulrahman Ismail, Muhammad Davis, Katherine R. Serpedin, Erchin Texas A&m University Electrical & Computer Engineering Department College StationTX77843 United States Lebanese American University Department of Computer Science & Mathematics Beirut Lebanon Florida State University Department of Electrical & Computer Engineering TallahasseeFL32310 United States Research and Outreach Center Tennessee Tech University Department of Cybersecurity Education CookevilleTN38505 United States

ISBN: (纸本)9798350354058

The load frequency control (LFC) is crucial for stabilizing the frequency of the power grid in the intermittency of renewable energy sources. Modern LFC systems utilize open communication and automation networks that expose power systems to potential cyberattacks, which could lead to frequency instability throughout the network. Current research often treats frequency control and cybersecurity independently, which could lead to ineffective solutions and increased system instability. This paper introduces a cyber-resilient LFC strategy that improves both control performance and security. We employ reinforcement learning for adaptive frequency control and integrate it with a graph convolutional neural network to enhance control responses during a cyberattack event. Our strategy also includes a graph auto encoder-based attack detector that is trained in various scenarios and has shown more than 92% in detection rate while tested on the Iberian power system topology, which includes 486 buses. This highlights the robustness and reliability of our approach in ensuring resilience against cyberattacks within the realm of frequency control in power systems. © 2024 IEEE.

关键词： Graph neural networks

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Stability and Hopf bifurcation of TB-COVID-19 coinfection model with impact of time delay

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SeMA Journal 2024年 1-41页

作者： Verma, V.S. Kaushik, Harshita Singh, Ram Jain, Sonal Akgül, Ali Department of Mathematics and Statistics Deen Dayal Upadhayaya Gorakhpur University Uttar Pradesh Gorakhpur 273009 India Departmental of Mathematical Science Baba Ghulam Shah Badshah University Jammu & Kashmir Rajouri 185234 India School of Technology Woxsen University Telangana Hyderabad 502345 India Art and Science Faculty Department of Mathematics Siirt University Siirt 56100 Turkey Department of Computer Engineering Biruni University Topkapı Istanbul 34010 Turkey Mathematics Research Center Department of Mathematics Near East Boulevard Near East Boulevard Nicosia/Mersin 10 99138 Turkey

In this work, a compartmental approach used for modelling and surveillance of dynamics of Tuberculosis and COVID-19 coinfection by considering the post-infection and molecular variants compartments in addition to existing compartments. We have tried to explain how variants can affect the infection rate and its severity. Also, the post-infection compartment is studied to understand the impact after recovery from the disease and the consequences of the post-infection period. We highlight the conceptual idea and mathematical tools and techniques needed for such co-infection disease modelling. We investigate the basic properties of the co-infectious disease model, including the local and global stability of the equilibria for the delayed and non-delayed systems, and calculate the points of equilibria and the basic reproduction number of the suggested model. It is proved that when the time delay caused by the latent phase of tuberculosis exceeds the threshold value, the constructed model undergoes a Hopf bifurcation around the tuberculosis existence. The center manifold theory is used to study the direction and stability of the Hopf bifurcation which is essential to study the delayed system. Both delayed and non-delayed systems differ significantly and we have conducted numerical analyses to verify the efficacy of the deduced outcomes. © The Author(s), under exclusive licence to Sociedad Española de Matemática Aplicada 2024.

关键词： 34D23 34K18 34K20 Centre manifold theory COVID-19 Hopf bifurcation TB Time delay Vaccination

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CRANE: A Genuine Framework based on Verifiable Searchable Encryption Security and Resource Constraints Balancing on Client Side

CRANE: A Genuine Framework based on Verifiable Searchable En...

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International Conference on Smart Communications and Networking (SmartNets)

作者： Marius Iulian Mihailescu Stefania Loredana Nita Valentina Marascu Faculty of Engineering and Computer Science Scientific Research Center in Mathematics and Computer Science SPIRU HARET University Bucharest Romania Department of Computer and Cybernetic Security Military Technical Academy “Ferdinand I” Bucharest Romania

ISBN: (数字)9798350385328

ISBN: (纸本)9798350385335

This paper introduces an authentic framework that relies on verifiable searchable encryption security and a mechanism for managing resource limitations on the client-side. The framework is specifically designed to tackle the difficulty of achieving a high level of data security while minimizing the storage requirements on the client-side. The framework combines a symmetric key encryption technique with a Searchable Encryption Index (SEI) to allow for efficient searches while maintaining data secrecy. One important aspect is the utilization of cryptographic verification tokens, which enable clients to verify the integrity and validity of search results while keeping a consistently small storage space requirement. This is accomplished by exclusively storing crucial keys and tokens on the client's end. Our framework incorporates advanced security measures such as key rotation, auditing systems, and end-to-end encryption. This ensures a strong and efficient solution for safe data searches, making it especially suitable for contexts with limited client-side resources. The practical usefulness of searchable encryption is validated through rigorous testing and third-party audits, ensuring a balance between security, efficiency, and scalability.

关键词： Smart cities Scalability Keyword search Education Encryption Security Indexes

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Experimental demonstration of a flexible-grid 1×(2×3)mode-and wavelength-selective switch using silicon microring resonators and counter-tapered couplers

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Chinese Optics Letters 2024年第1期22卷 52-58页

作者：孔德军鲁昊汪鹏君符强戴世勋陈伟伟王栎沣张波豪马凌霄李军戴庭舸杨建义 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China College of Science and Technology Ningbo UniversityNingbo 315300China Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Department of Information Science and Electronics Engineering and Cyrus Tang Center for Sensor Materials and Applications Zhejiang UniversityHangzhou 310027China

A flexible-grid 1×(2×3)mode-and wavelength-selective switch which comprises counter-tapered couplers and silicon microring resonators has been proposed,optimized,and demonstrated experimentally in this *** carefully thermally tuning phase shifters and silicon microring resonators,mode and wavelength signals can be independently and flexibly conveyed to any one of the output ports,and different bandwidths can be generated as *** particle swarm optimization algorithm and finite difference time-domain method are employed to optimize structural parameters of the twomode(de)multiplexer and crossing *** bandwidth-tunable wavelength-selective optical router composed of12 microring resonators is studied by taking advantage of the transfer matrix *** results show that,for the fabricated module,cross talk less than-10.18 dB,an extinction ratio larger than 17.41 d B,an in-band ripple lower than0.79 dB,and a 3-dB bandwidth changing from 0.38 to 1.05 nm are obtained,as the wavelength-channel spacing is 0.40 *** corresponding response time is measured to be 13.64μs.

关键词： integrated optics optical waveguide mode-and wavelength-selective switch

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AI Dynamics: Revolutionizing Organizational Skills and Contributing to Enhanced Business in Morocco 9th

AI Dynamics: Revolutionizing Organizational Skills and Contr...

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9th International Conference on Smart City Applications, SCA 2024

作者： Chegri, Badre Eddine Aiche, Karim Berhich, Asmae Mettiti, Abderrahman El Rhajbal, Zineb Saadane, Rachid Chehri, Abdellah Mohammed V University in Rabat Rabat Morocco AMIPS Research Team E3S Research Center Computer Science Department EMI Mohammed V University in Rabat Rabat Morocco LRIT-GSCM Faculty of Sciences University Mohammed V Rabat Morocco Laboratory Engineering System SIRC/LAGeS EHTP Casablanca Morocco Department of Mathematics and Computer Science Royal Military College Kingston Canada

ISBN: (纸本)9783031886522

This study investigates the transformative effects of Artificial Intelligence (AI) on organizational skills within the Moroccan context. Utilizing a mixed-methods approach, combining qualitative interviews and a quantitative survey across diverse industries, the research explores AI's impact on crucial competencies like adaptability, communication, decision-making, and collaboration. The findings reveal a nuanced picture of both positive and challenging aspects of AI adoption, emphasizing the need for strategic planning and skill development. Focused on Morocco, this research contributes unique insights into the socio-economic implications of AI in a developing economy. The study's outcomes provide actionable recommendations for policymakers, business leaders, and educators, highlighting the imperative of fostering an environment that maximizes the potential of AI for organizational skills enhancement, ultimately bolstering overall competitiveness. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Strategic planning

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Driving Activity Classification Using Deep Residual Networks Based on Smart Glasses Sensors

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Intelligent Automation & Soft Computing 2023年第11期38卷 139-151页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering Image Information and Intelligence LaboratoryFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayaoThailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road *** a result,reckless driving behaviour can cause congestion and *** vision and multimodal sensors have been used to study driving behaviour categorization to lessen this *** research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s *** the other hand,driving a car is a complicated action that requires a wide range of body *** this work,we proposed a ResNet-SE model,an efﬁcient deep learning classiﬁer for driving activity clas-siﬁcation based on signal data obtained in real-world trafﬁc conditions using smart ***-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning *** data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this *** performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LSTMs)to demonstrate its *** to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.

关键词： Smart glasses human activity recognition deep learning wearable sensors driving activity

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Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction

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General Psychiatry 2023年第4期36卷 303-311页

作者： Qiujian Meng Ying Zhu Ye Yuan Li Yang Jiafang Liu Xiaochu Zhang Junjie Bu Department of Intelligent Medical Engineering School of Biomedical EngineeringAnhui Medical UniversityHefeiAnhuiChina Department of Psychology School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhuiChina Department of Psychology School of Humanities&Social ScienceUniversity of Science&Technology of ChinaHefeiAnhuiChina Department of Radiology the First Affiliated Hospital of USTCHefei National Research Center for Physical Sciences at the Microscale and School of Life ScienceDivision of Life Science and MedicineUniversity of Science&Technology of ChinaHefeiAnhuiChina Application Technology Center of Physical Therapy to Brain Disorders Institute of Advanced TechnologyUniversity of Science&Technology of ChinaHefeiAnhuiChina Institute of Health and Medicine Hefei Comprehensive Science CenterHefeiAnhuiChina

Background The high rate of long-term relapse is a major cause of smoking cessation ***,neurofeedback training has been widely used in the treatment of nicotine addiction;however,approximately 30%of subjects fail to benefit from this *** previous randomised clinical trial(RCT)examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month ***,significant individual differences were observed in the 4-month follow-up effects of decreased cigarette ***,it is critical to identify who will benefit from *** We examined whether the resting-state electroencephalography(EEG)characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible *** This was a double-blind RCT.A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback *** underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions.A follow-up assessment was conducted after 4 *** The frontal resting-state theta power spectral density(PSD)was significantly altered in the real-feedback group after two neurofeedback *** theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month *** reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback.A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month ***,source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal *** Our study demonstrated changes in the resting-state theta PSD

关键词： nicotine addiction treatment

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RAPIDEST: A Framework for Obstructive Sleep Apnea Detection

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IEEE Transactions on Neural Systems and Rehabilitation engineering 2023年 31卷 387-397页

作者： Lin, Xin-Xue Lin, Phone Yeh, En-Hau Liu, Gi-Ren Lien, Wan-Ching Fang, Yuguang National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Graduate Institute of Networking and Multimedia Institute of Medical Device and Imaging National Taiwan University Internet of Things Research Center Department of Computer Science and Information Engineering Taipei10617 Taiwan National Cheng Kung University Department of Mathematics Tainan City701 Taiwan National Taiwan University Hospital Department of Emergency Medicine Taipei100229 Taiwan College of Medicine National Taiwan University Department of Emergency Medicine Taipei10617 Taiwan City University of HongKong Department of Computer Science HongKong Hong Kong

The traditional polysomnography (PSG) examination for Obstructive Sleep Apnea (OSA) diagnosis needs to measure several signals, such as EEG, ECG, EMG, EOG and the oxygen level in blood, of a patient who may have to wear many sensors during sleep. After the PSG examination, the Apnea-Hypopnea Index (AHI) is calculated based on the measured data to evaluate the severity of apnea and hypopnea for the patient. This process is obviously complicated and inconvenient. In this paper, we propose an AI-based framework, called RAre Pattern Identification and DEtection for Sleep-stage Transitions (RAPIDEST), to detect OSA based on the sequence of sleep stages from which a novel rarity score is defined to capture the unusualness of the sequence of sleep stages. More importantly, under this framework, we only need EEG signals, thus significantly simplifying the signal collection process and reducing the complexity of the severity determination of apnea and hypopnea. We have conducted extensive experiments to verify the relationship between the rarity score and AHI and demonstrate the effectiveness of our proposed approach. © 2001-2011 IEEE.

关键词： Electrocardiograms

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