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On Some Novel Fixed Point Results for Generalized F-Contractions in b-Metric-Like Spaces with Application

computer Modeling in engineering & Sciences 2023年第4期135卷 673-686页

作者： Kastriot Zoto Ilir Vardhami Dusan Bajovic Zoran D.Mitrovic Stojan Radenovic Department of Mathematics and Computer Sciences Faculty of Natural SciencesUniversity of GjirokastraGjirokastra6001Albania Department of Mathematics Faculty of Natural SciencesUniversity of TiranaTirana1001Albania Faculty of Electrical Engineering University of Banja LukaBanja Luka78000Bosnia and Herzegovina Department of Mathematics Faculty of Mechanical EngineeringUniversity of BelgradeBeograd11120Serbia

The focusofourwork is on themost recent results infixedpoint theoryrelated *** variants of(s,q,φ,F)-contractions that expand,supplement and unify an important work widely discussed in the literature,based on existing classes of interpolative and *** particular,a large class of contractions in terms of s,q,φand F for both linear and nonlinear contractions are defined in the framework of b-metric-like *** main result in our paper is that(s,q,φ,F)-g-weak contractions have a fixed point in b-metric-like spaces if function F or the specified contraction is *** an application of our results,we have shown the existence and uniqueness of solutions of some classes of nonlinear integral equations.

关键词： (φ,F)-contraction (s,q,φ,F)-contraction b-metric-like space fixed point

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Retinal Blood Vessel Tracking and Diameter Estimation via Gaussian Process With Rider Optimization Algorithm

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IEEE Journal of Biomedical and Health Informatics 2024年第3期28卷 1173-1184页

作者： Ahmad, Nehal Lai, Kuan-Ting Tanveer, M. Indian Institute of Technology Indore Simrol Department of Mathematics Indore453552 India National Taipei University of Technology Department of International Program of Electrical Engineering and Computer Science Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan

Retinal blood vessels structure analysis is an important step in the detection of ocular diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and estimation of retinal blood vessels in terms of their diameter remains a major challenge in retinal structure analysis. In this research, we develop a rider-based Gaussian approach for accurate tracking and diameter estimation of retinal blood vessels. The diameter and curvature of the blood vessel are assumed as the Gaussian processes. The features are determined for training the Gaussian process using Radon transform. The kernel hyperparameter of Gaussian processes is optimized using Rider Optimization Algorithm for evaluating the direction of the vessel. Multiple Gaussian processes are used for detecting the bifurcations and the difference in the prediction direction is quantified. The performance of the proposed Rider-based Gaussian process is evaluated with mean and standard deviation. Our method achieved high performance with the standard deviation of 0.2499 and mean average of 0.0147, which outperformed the state-of-the-art method by 6.32%. Although the proposed model outperformed the state-of-the-art method in normal blood vessels, in future research, one can include tortuous blood vessels of different retinopathy patients, which would be more challenging due to large angle variations. We used Rider-based Gaussian process for tracking blood vessels to obtain the diameter of retinal blood vessels, and the method performed well on the 'STrutred Analysis of the REtina (STARE) Database' accessed on Oct. 2020 (https://***/~ahoover/stare/). To the best of our knowledge, this experiment is one of the most recent analysis using this type of algorithm. © 2013 IEEE.

关键词： Blood vessels

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Statistical mechanics and pressure of composite optical systems

Statistical mechanics and pressure of composite optical syst...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Efremidis, Nikolaos K. Christodoulides, Demetrios N. Department of Applied Mathematics University of Crete Heraklion71409 Greece Institute of Applied and Computational Mathematics FORTH Crete Heraklion70013 Greece Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States

We develop a thermodynamic theory that takes into account the synergistic action of multiple components. We compute the optomechanical pressure and find that the type of the nonlinearity involved can lead to different... 详细信息

ISBN: (纸本)9781957171395

关键词： Electro-optical waveguides Laser theory Lasers and electrooptics Thermodynamics

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Towards Early Diagnosis and Intervention: An Ensemble Voting Model for Precise Vital Sign Prediction in Respiratory Disease

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IEEE Journal of Biomedical and Health Informatics 2023年 PP卷 1-13页

作者： Ahmed, Usman Lin, Jerry Chun-Wei Srivastava, Gautam Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen Norway Dept. of Math and Computer Science Brandon University Canada

Worldwide, cardiovascular and chronic respiratory diseases account for approximately 19 million deaths annually. Evidence indicates that the ongoing COVID-19 pandemic directly contributes to increased blood pressure, cholesterol, as well as blood glucose levels. Timely screening of critical physiological vital signs benefits both healthcare providers and individuals by detecting potential health issues. This study aims to implement a machine learning-based prediction and classification system to forecast vital signs associated with cardiovascular and chronic respiratory diseases. The system predicts patients' health status and notifies caregivers and medical professionals when necessary. Utilizing real-world data, a linear regression model inspired by the Facebook Prophet model was developed to predict vital signs for the upcoming 180 seconds. With 180 seconds of lead time, caregivers can potentially save patients' lives through early diagnosis of their health conditions. For this purpose, a Naïve Bayes classification model, a Support Vector Machine model, a Random Forest model, and genetic programming-based hyper tunning were employed. The proposed model outdoes previous attempts at vital sign prediction. Compared with alternative methods, the Facebook Prophet model has the best mean square in predicting vital signs. A hyperparameter-tuning is utilized to refine the model, yielding improved short- and long-term outcomes for each and every vital sign. Furthermore, the F-measure for the proposed classification model is 0.98 with an increase of 0.21. The incorporation of additional elements, such as momentum indicators, could increase the model's flexibility with calibration. The findings of this study demonstrate that the proposed model is more accurate in predicting vital signs and trends. IEEE

关键词： Decision trees

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Fuzzy-Deep Learning-Based Artificial Intelligence for Edge Computing and Real-Time Decision-Making in Uncertain IoT Environments 1

Fuzzy-Deep Learning-Based Artificial Intelligence for Edge C...

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1st International Conference on Advances in computer Science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Joshi, B.P. Singh, Akhilesh Kumar, Nagendra Rautela, Siddharth Graphic Era Hill University Department of Mathematics Department of Computer Science & Engineering India VMSB UTU Department of Electrical Engineering Campus Pithoragarh India GL Bajaj Institute of Technology & Management Department of Electrical & Electronics Engineering Greater Noida201306 India Central Board of Secondary Education Department of Mathematics Uttarakhand Bhimtal India

ISBN: (纸本)9798331518578

Owing to the Internet of Vehicles (IoV) quick growth, both academics and the sector have paid close emphasis to vehicular edge computation (VEC). Nevertheless, because of the unbalanced congestion and the strict delay requirements, task offloading in various junction situations continues to struggle from inefficient resource allocated and poor operation implementation standards. This study proposes a task-offloading technique using a fuzzy decision-making method to deal with ambiguity and uncertainties to solve these problems. Roadside Utilities (RSUs) placed alongside remote roadways typically have limited energy resources, thus they must offer energy-effective planning assistance with the distribution of duties to VEC. However, planning decisions for regional task execution incur computational costs, and assigning duties to edge automobiles incurs transmission costs, making energy usage management difficult. Task data transmission to edge automobiles results in increased RSU power usage even while task offloading lowers response delay. To meet task schedule and supply restrictions, this study proposes an energy-effective automobile planning issue for offloading functions to mobile edge units. This study develops a planning technique depending on on-policy deep reinforcement learning (DRL) and a fuzzy-based DRL to address the extremely complex problem brought on by a rise in the number of automobiles under RSU service. When contrasted to the Q-learning method, this FRL not only speeds up the learning procedure but also enhances long-term payoff. © 2025 IEEE.

关键词： Energy utilization

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Optimal Second-Order Rates for Quantum Soft Covering and Privacy Amplification

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IEEE Transactions on Information Theory 2024年第7期70卷 5077-5091页

作者： Shen, Yu-Chen Gao, Li Cheng, Hao-Chung National Taiwan University Department of Electrical Engineering Taipei10617 Taiwan University of Houston Department of Mathematics HoustonTX77204 United States Graduate Institute of Communication Engineering Department of Mathematics Institute of Applied Mathematical Sciences Center for Quantum Science and Engineering National Taiwan University Department of Electrical Engineering Taipei10617 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan Quantum Computing Center New Taipei City23678 Taiwan

We study quantum soft covering and privacy amplification against quantum side information. The former task aims to approximate a quantum state by sampling from a prior distribution and querying a quantum channel. The latter task aims to extract uniform and independent randomness against quantum adversaries. For both tasks, we use trace distance to measure the closeness between the processed state and the ideal target state. We show that the minimal amount of samples for achieving an \varepsilon -covering is given by the (1-\varepsilon ) -hypothesis testing information (with additional logarithmic additive terms), while the maximal extractable randomness for an \varepsilon -secret extractor is characterized by the conditional (1-\varepsilon ) -hypothesis testing entropy. When performing independent and identical repetitions of the tasks, our one-shot characterizations lead to tight asymptotic expansions of the above-mentioned operational quantities. We establish their second-order rates given by the quantum mutual information variance and the quantum conditional information variance, respectively. Moreover, our results extend to the moderate deviation regime, which are the optimal asymptotic rates when the trace distances vanish at sub-exponential speed. Our proof technique is direct analysis of trace distance without smoothing. © 1963-2012 IEEE.

关键词： Hash functions

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Learning Posterior Distributions in Underdetermined Inverse Problems 9th

Learning Posterior Distributions in Underdetermined Inverse...

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9th International Conference on Scale Space and Variational Methods in computer Vision, SSVM 2023

作者： Runkel, Christina Moeller, Michael Schönlieb, Carola-Bibiane Etmann, Christian Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom Department of Electrical Engineering and Computer Science University of Siegen Siegen Germany

ISBN: (纸本)9783031319747

In recent years, classical knowledge-driven approaches for inverse problems have been complemented by data-driven methods exploiting the power of machine and especially deep learning. Purely data-driven methods, however, come with the drawback of disregarding prior knowledge of the problem even though it has shown to be beneficial to incorporate this knowledge into the problem-solving process. We thus introduce an unpaired learning approach for learning posterior distributions of underdetermined inverse problems. It combines advantages of deep generative modeling with established ideas of knowledge-driven approaches by incorporating prior information about the inverse problem. We develop a new neural network architecture ’UnDimFlow’ (short for Unequal Dimensionality Flow) consisting of two normalizing flows, one from the data to the latent, and one from the latent to the solution space. Additionally, we incorporate the forward operator to develop an unpaired learning method for the UnDimFlow architecture and propose a tailored point estimator to recover an optimal solution during inference. We evaluate our method on the two underdetermined inverse problems of image inpainting and super-resolution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Inverse problems

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An Efficient Solution for the Collusion Problem of DECO 17

An Efficient Solution for the Collusion Problem of DECO

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17th International Conference on Information Security and Cryptology, ISCTurkiye 2024

作者： Sen, Ugur Osmanoglu, Murat Selcuk, Ali Aydin Institute of Applied Mathematics Middle East Technical University Ankara Turkey Department of Computer Engineering Ankara University Ankara Turkey Department of Computer Engineering TOBB University of Economics and Technology Ankara Turkey

ISBN: (纸本)9798331533649

DECO is one of the state-of-The-Art TLS evidence protocols that enables privacy-preserving verification without necessitating server-side modifications. It allows applications to extract verifiable data from websites. However, DECO is vulnerable to collusion attacks, where the prover and verifier may secretly conspire, even if DECO itself remains secure. This vulnerability limits DECO's ability to transfer data to smart contracts. To address the collusion issue, decentralized oracle networks have been integrated with DECO, involving multiple executions for the same attestation and relying on majority consensus to determine the correct outcome. While this approach mitigates collusion risk, it is inefficient. In this paper, we address the collusion vulnerability in DECO by proposing an enhanced approach that expands the verifier's role to a set of n verifiers within a single DECO execution, utilizing a Distributed Verifiable Random Function (DVRF). This method requires the prover to obtain consensus from all n verifiers, thereby increasing the difficulty of collusion and enhancing the security of the system. Furthermore, the proposed solution is more efficient than executing n separate DECO protocols and provides verifiable features that facilitate integration with slashing and reward mechanisms, thereby improving its applicability in decentralized systems. © 2024 IEEE.

关键词： Smart contract

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A Dynamic Frequency Sweeping Based Parameter Estimation Method for Wireless Power Transfer 49

A Dynamic Frequency Sweeping Based Parameter Estimation Meth...

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

作者： Zhu, Gangwei Dong, Jianning Bauer, Pavol Delft University of Technology Department of Electrical Engineering Mathematics and Computer Science Delft Netherlands

ISBN: (纸本)9798350331820

It is ideal for the wireless power transfer (WPT) systems to operate at the resonance state for better transmission performance. In practice, however, the parameters of the resonant circuits often deviate because of the capacitance drift and coil misalignment. To this end, this paper proposes a new parameter estimation method for the WPT systems, which is able to facilitate the power flow control and active impedance tuning of the WPT systems under parameter deviations. Distinct from the traditional parameter identification methods, the proposed method is implemented with an short-circuited rectifier, and therefore, the whole estimation process is independent of the load variations. Furthermore, to avoid severe system detuning during the frequency-sweeping process, a dynamic frequency sweeping method is proposed to efficiently and safely extract the data of the primary and secondary coil currents. Based on the extracted data, a mathematical model is established, and the JAYA algorithm is utilized to identify the unknown parameters. Experimental results are presented to verify the estimation accuracy of the proposed method. © 2023 IEEE.

关键词： Energy transfer

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Toward Digital-Twin-Assisted Data Acquisition in Underwater Acoustic Sensor Networks 16

Toward Digital-Twin-Assisted Data Acquisition in Underwater ...

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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： Spajić, Ivan Kristensen, Lars Michael Stolz, Volker Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Norway

Data transfer from underwater acoustic sensor networks (UASNs) to cloud services is challenging due to the severe bandwidth constraints of acoustic communication and energy consumption constraints of battery-powered sensor devices. To mitigate this problem, various forms of time series compression algorithms, both lossless and lossy, have been proposed in the literature. These proposals, however, focus on large time series whose in-memory buffering is not feasible in a UASN context. Furthermore, especially in oceanographic data acquisition, buffering large time series sacrifices the Age of Information. To address this gap, we evaluate a modern lossy compression algorithm, Mix-Piece, on small-sized time series. Motivated by our findings, we have developed the Custom-Piece algorithm, an adaptation of Mix-Piece that yields higher data compression at the expense of increased execution times. Our experimental evaluation of the Mix-Piece/Custom-Piece algorithms on real-world oceanographic data shows that compression ratios are highly dependent on the configuration of the algorithms due to the emerging characteristics of the underlying data sets. To facilitate practical use of the Mix-Piece/Custom-Piece algorithms, we outline how a digital twin may dynamically run simulations on available past data to support end-users in developing sensor configurations according to data acquisition requirements. © 2025 Elsevier B.V.. All rights reserved.

关键词： Data compression ratio

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