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Journal articles on the topic 'Adaptive parametric sampling'

Author: Grafiati

Published: 29 August 2023

Last updated: 31 July 2025

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1

Rafiq, Danish, and Mohammad Abid Bazaz. "Adaptive parametric sampling scheme for nonlinear model order reduction." Nonlinear Dynamics 107, no. 1 (2021): 813–28. http://dx.doi.org/10.1007/s11071-021-07025-7.

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Azencott, R., A. Beri, and I. Timofeyev. "Adaptive Sub-sampling for Parametric Estimation of Gaussian Diffusions." Journal of Statistical Physics 139, no. 6 (2010): 1066–89. http://dx.doi.org/10.1007/s10955-010-9975-y.

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Borggaard, Jeff, Kevin R. Pond, and Lizette Zietsman. "Parametric Reduced Order Models Using Adaptive Sampling and Interpolation." IFAC Proceedings Volumes 47, no. 3 (2014): 7773–78. http://dx.doi.org/10.3182/20140824-6-za-1003.02664.

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Liu, Ying, Hongguang Li, Huanyu Du, Ningke Tong, and Guang Meng. "An adaptive sampling procedure for parametric model order reduction by matrix interpolation." Journal of Low Frequency Noise, Vibration and Active Control 39, no. 4 (2019): 821–34. http://dx.doi.org/10.1177/1461348419851595.

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An adaptive sampling approach for parametric model order reduction by matrix interpolation is developed. This approach is based on an efficient exploration of the candidate parameter sets and identification of the points with maximum errors. An error indicator is defined and used for fast evaluation of the parameter points in the configuration space. Furthermore, the exact error of the model with maximum error indicator is calculated to determine whether the adaptive sampling procedure reaches a desired error tolerance. To improve the accuracy, the orthogonal eigenvectors are utilized as the r

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Chen, Yi-Wen, and Wen-Hsiao Peng. "Parametric OBMC for Pixel-Adaptive Temporal Prediction on Irregular Motion Sampling Grids." IEEE Transactions on Circuits and Systems for Video Technology 22, no. 1 (2012): 113–27. http://dx.doi.org/10.1109/tcsvt.2011.2158341.

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Lu, Kuan, Haopeng Zhang, Kangyu Zhang, et al. "The Transient POD Method Based on Minimum Error of Bifurcation Parameter." Mathematics 9, no. 4 (2021): 392. http://dx.doi.org/10.3390/math9040392.

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An invariable order reduction model cannot be obtained by the adaptive proper orthogonal decomposition (POD) method in parametric domain, there exists uniqueness of the model with different conditions. In this paper, the transient POD method based on the minimum error of bifurcation parameter is proposed and the order reduction conditions in the parametric domain are provided. The order reduction model equivalence of optimal sampling length is discussed. The POD method was applied for order reduction of a high-dimensional rotor system supported by sliding bearings in a certain speed range. The

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Woudt, Edwin, Pieter-Tjerk de Boer, and Jan-Kees van Ommeren. "Improving Adaptive Importance Sampling Simulation of Markovian Queueing Models using Non-parametric Smoothing." SIMULATION 83, no. 12 (2007): 811–20. http://dx.doi.org/10.1177/0037549707087223.

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Jia, Gaofeng, and Alexandros A. Taflanidis. "Non-parametric stochastic subset optimization utilizing multivariate boundary kernels and adaptive stochastic sampling." Advances in Engineering Software 89 (November 2015): 3–16. http://dx.doi.org/10.1016/j.advengsoft.2015.06.014.

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Ourbih-Tari, Megdouda, and Mahdia Azzal. "Survival function estimation with non parametric adaptive refined descriptive sampling algorithm: A case study." Communications in Statistics - Theory and Methods 46, no. 12 (2016): 5840–50. http://dx.doi.org/10.1080/03610926.2015.1065328.

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Morio, Jérôme. "Non-parametric adaptive importance sampling for the probability estimation of a launcher impact position." Reliability Engineering & System Safety 96, no. 1 (2011): 178–83. http://dx.doi.org/10.1016/j.ress.2010.08.006.

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Botev, Z. I., A. Ridder, and L. Rojas-Nandayapa. "Semiparametric cross entropy for rare-event simulation." Journal of Applied Probability 53, no. 3 (2016): 633–49. http://dx.doi.org/10.1017/jpr.2016.31.

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AbstractThe cross entropy is a well-known adaptive importance sampling method which requires estimating an optimal importance sampling distribution within a parametric class. In this paper we analyze an alternative version of the cross entropy, where the importance sampling distribution is selected instead within a general semiparametric class of distributions. We show that the semiparametric cross entropy method delivers efficient estimators in a wide variety of rare-event problems. We illustrate the favourable performance of the method with numerical experiments.

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Gautier, Athénaïs, David Ginsbourger, and Guillaume Pirot. "Goal-oriented adaptive sampling under random field modelling of response probability distributions." ESAIM: Proceedings and Surveys 71 (August 2021): 89–100. http://dx.doi.org/10.1051/proc/202171108.

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In the study of natural and artificial complex systems, responses that are not completely determined by the considered decision variables are commonly modelled probabilistically, resulting in response distributions varying across decision space. We consider cases where the spatial variation of these response distributions does not only concern their mean and/or variance but also other features including for instance shape or uni-modality versus multi-modality. Our contributions build upon a non-parametric Bayesian approach to modelling the thereby induced fields of probability distributions, a

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Trampert, Patrick, Dmitri Rubinstein, Faysal Boughorbel, et al. "Deep Neural Networks for Analysis of Microscopy Images—Synthetic Data Generation and Adaptive Sampling." Crystals 11, no. 3 (2021): 258. http://dx.doi.org/10.3390/cryst11030258.

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The analysis of microscopy images has always been an important yet time consuming process in materials science. Convolutional Neural Networks (CNNs) have been very successfully used for a number of tasks, such as image segmentation. However, training a CNN requires a large amount of hand annotated data, which can be a problem for material science data. We present a procedure to generate synthetic data based on ad hoc parametric data modelling for enhancing generalization of trained neural network models. Especially for situations where it is not possible to gather a lot of data, such an approa

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Liu, Yang, and Balgobin Nandram. "Sampling methods for the concentration parameter and discrete baseline of the Dirichlet Process." Statistics in Transition New Series 23, no. 4 (2022): 21–36. http://dx.doi.org/10.2478/stattrans-2022-0040.

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Abstract There are many models in the current statistical literature for making inferences based on samples selected from a finite population. Parametric models may be problematic because statistical inference is sensitive to parametric assumptions. The Dirichlet process (DP) prior is very flexible and determines the complexity of the model. It is indexed by two hyper-parameters: the baseline distribution and concentration parameter. We address two distinct problems in the article. Firstly, we review the current sampling methods for the concentration parameter, which use the continuous baselin

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S. Sureshkrishna, S. Varalakshmi, K. Senthil Kumar, A. K. Gnanasekar,. "An Effective Adaptive Threshold Based Compressive Spectrum Sensing in Cognitive Radio Networks." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 1220–24. http://dx.doi.org/10.17762/itii.v9i1.260.

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Spectrum sensing is playing a vital role in Cognitive Radio networks. Wideband spectrum sensing increases the speed of sensing but which in turn requires higher sampling rate and also increases the complexity of hardware and also power consumption. Compression based sensing reduces the sampling rate by using Sub-Nyquist sampling but the compression and the reconstruction problem exists. In compression based spectrum sensing, noise uncertainty is one of the major performance degradation factor. To reduce this degradation, compressive measurements based sensing with adaptive threshold is propose

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Скачков, Валерій, Віктор Чепкій, Олександр Єфимчиков та Владислав Набок. "ПРОБЛЕМА ОПТИМАЛЬНОСТІ АДАПТИВНИХ РАДІОТЕХНІЧНИХ СИСТЕМ В СИТУАЦІЇ З НЕКЛАСИФІКОВАНОЮ НАВЧАЛЬНОЮ ВИБІРКОЮ СПОСТЕРЕЖЕНЬ". Collection of scientific works of Odesa Military Academy, № 18 (3 березня 2023): 66–77. http://dx.doi.org/10.37129/2313-7509.2022.18.66-77.

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Statistical synthesis of adaptive systems for spatiotemporal signal processing in most radio engineering problems occurs under the condition of parametric a priori uncertainty. The prospective direction of overcoming parametric a priori uncertainty is affiliated with the prior learning procedure. As a result of the training, sufficient statistics of likelihood ratios are formed, which are used in decision-making. The asymptotic optimality of adaptive systems with alternative benchmarks, one of which is peculiar to the class of radio structures with an adaptive antenna array and the other with

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Vosniakos, G. C., and T. Giannakakis. "Reverse engineering of simple surfaces of unknown shape with touch probes: Scanning and compensation issues." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 4 (2003): 563–68. http://dx.doi.org/10.1243/095440503321628233.

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This work discusses issues concerning the implementation of scanning of unknown engineering objects containing just simple (i.e. no freeform) surfaces with touch probes on three-axis computer numerical control (CNC) measuring machines in order to reconstruct their shape in a computer aided design (CAD) system. Several ideas are put forward e.g. scanning along vertical slicing planes adaptive point sampling distances in-process ‘proactive’ segmentation of points into curve sections and probe radius compensation in two directions as well as limited remedy of edge scanning ambiguities. Most of th

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Singh, Kundan, Yogesh Mani Tripathi, Liang Wang, and Shuo-Jye Wu. "Analysis of Block Adaptive Type-II Progressive Hybrid Censoring with Weibull Distribution." Mathematics 12, no. 24 (2024): 4026. https://doi.org/10.3390/math12244026.

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The estimation of unknown model parameters and reliability characteristics is considered under a block adaptive progressive hybrid censoring scheme, where data are observed from a Weibull model. This censoring scheme enhances experimental efficiency by conducting experiments across different testing facilities. Point and interval estimates for parameters and reliability assessments are derived using both classical and Bayesian approaches. The existence and uniqueness of maximum likelihood estimates are established. Consequently, reliability performance and differences across different testing

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19

Karwowski, Andrzej. "Performance evaluation of MoM-based wide-band EM simulation with adaptive frequency sampling and Stöer-Bulirsch algorithm." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 4 (2017): 859–70. http://dx.doi.org/10.1108/compel-07-2016-0318.

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Purpose The purpose of this paper is to examine the convergence, offered accuracy and efficiency of the bisectional adaptive frequency sampling (AFS) scheme combined with the Stöer-Bulirsch (SB) algorithm as a tool for supporting frequency-domain method-of-moments (MoM) in broadband electromagnetic (EM) simulations. Design/methodology/approach The AFS and SB procedures have been interfaced with the MoM code, and then, an extensive parametric study has been carried out to explore the performance of the numerical solution for the test problems of reconstructing frequency responses of the wire ra

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Binder, Andreas, Onkar Jadhav, and Volker Mehrmann. "Model order reduction for the simulation of parametric interest rate models in financial risk analysis." Journal ofMathematics in Industry 11 (June 3, 2021): 1–34. https://doi.org/10.1186/s13362-021-00105-8.

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This paper presents a model order reduction approach for large scale high dimensional parametric models arising in the analysis of financial risk. To understand the risks associated with a financial product, one has to perform several thousand computationally demanding simulations of the model which require efficient algorithms. We establish a model reduction approach based on a variant of the proper orthogonal decomposition method to generate small model approximations for the high dimensional parametric convection-diffusion-reaction partial differential equations. This approach requires to s

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Bellam Muralidhar, Nanda Kishore, Natalie Rauter, Andrey Mikhaylenko, Rolf Lammering, and Dirk A. Lorenz. "Parametric Model Order Reduction of Guided Ultrasonic Wave Propagation in Fiber Metal Laminates with Damage." Modelling 2, no. 4 (2021): 591–608. http://dx.doi.org/10.3390/modelling2040031.

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This paper focuses on parametric model order reduction (PMOR) of guided ultrasonic wave propagation and its interaction with damage in a fiber metal laminate (FML). Structural health monitoring in FML seeks to detect, localize and characterize the damage with high accuracy and minimal use of sensors. This can be achieved by the inverse problem analysis approach, which employs the signal measurement data recorded by the embedded sensors in the structure. The inverse analysis requires us to solve the forward simulation of the underlying system several thousand times. These simulations are often

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Martín del Campo, Gustavo, Yuriy Shkvarko, Andreas Reigber, and Matteo Nannini. "TomoSAR Imaging for the Study of Forested Areas: A Virtual Adaptive Beamforming Approach." Remote Sensing 10, no. 11 (2018): 1822. http://dx.doi.org/10.3390/rs10111822.

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Among the objectives of the upcoming space missions Tandem-L and BIOMASS, is the 3-D representation of the global forest structure via synthetic aperture radar (SAR) tomography (TomoSAR). To achieve such a goal, modern approaches suggest solving the TomoSAR inverse problems by exploiting polarimetric diversity and structural model properties of the different scattering mechanisms. This way, the related tomographic imaging problems are treated in descriptive regularization settings, applying modern non-parametric spatial spectral analysis (SSA) techniques. Nonetheless, the achievable resolution

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Li, Tianyi, and Jean-François Luyé. "Optimization of Fiber Orientation Model Parameters in the Presence of Flow-Fiber Coupling." Journal of Composites Science 2, no. 4 (2018): 73. http://dx.doi.org/10.3390/jcs2040073.

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In this paper, we propose a novel systematic procedure to minimize the discrepancy between the numerically predicted and the experimentally measured fiber orientation results on an injection-molded part. Fiber orientation model parameters are optimized simultaneously using Latin hypercube sampling and kriging-based adaptive surrogate modeling techniques. Via an adequate discrepancy measure, the optimized solution possesses correct skin–shell–core structure and global orientation evolution throughout the considered center-gated disk. Some non-trivial interaction between these parameters and flo

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24

Lang, Michael. "Control Limits for an Adaptive Self-Starting Distribution-Free CUSUM Based on Sequential Ranks." Technologies 7, no. 4 (2019): 71. http://dx.doi.org/10.3390/technologies7040071.

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Since their introduction in 1954, cumulative sum (CUSUM) control charts have seen a widespread use beyond the conventional realm of statistical process control (SPC). While off-the-shelf implementations aimed at practitioners are available, their successful use is often hampered by inherent limitations which make them not easily reconcilable with real-world scenarios. Challenges commonly arise regarding a lack of robustness due to underlying parametric assumptions or requiring the availability of large representative training datasets. We evaluate an adaptive distribution-free CUSUM based on s

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ROVEA, S. B., and RODOLFO FLESCH. "FAST ADAPTIVE GENERALIZED PREDICTIVE CONTROL FOR SYSTEMS WITH VARIABLE PARAMETERS." Journal of Engineering and Exact Sciences 5, no. 5 (2019): 0408–14. http://dx.doi.org/10.18540/jcecvl5iss5pp0408-0414.

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This paper proposes a fast predictive control structure with online model update according to process parametric variations. The proposed controller is based on the Generalized Predictive Control (GPC) algorithm, but it integrates the recursive least squares identification method with a variable forgetting factor to estimate at each iteration the parameters of a linear structure model used for multi-step ahead prediction. For a system with constraints on the process variables, the resulting optimization problem of GPC is solved using quadratic programming based on the Alternate Direction Metho

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OPUALA-CHARLES, SILVA. "PROMOTING SUPPLY CHAIN INNOVATION THROUGH SUPPLY CHAIN RESILIENCE AND RISK MANAGEMENT IN THE NIGER DELTA REGION OF NIGERIA." International Journal of Social Sciences and Management Review 08, no. 01 (2025): 70–90. https://doi.org/10.37602/ijssmr.2025.8105.

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This study investigates the role of supply chain resilience and risk management in fostering supply chain innovation for manufacturing firms in Nigeria's Niger Delta region. The research employs a purposive sampling method, focusing on 15 manufacturing firms with at least 50 employees each. Key variables include supply chain disruptions (security threats, infrastructure deficits, and energy crises), innovation levels (technology adoption), and resilience strategies (supplier diversification, flexibility, and redundancy). The study utilizes a mixed-methods approach with non-parametric correlati

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Mukherjee, S., D. Kumar, L. Udpa, and Y. Deng. "Robust defect detection under uncertainties using spatially adaptive capacitive imaging." Journal of Applied Physics 131, no. 23 (2022): 234901. http://dx.doi.org/10.1063/5.0088320.

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We develop a high-Q capacitive sensing based robust non-destructive evaluation (NDE) methodology that can be widely used in varied NDE applications. We show that the proposed method can detect defects in a host of robust regimes where uncertainties such as lift-off, probe tilt, fluctuations in sampling rates, and step sizes are inherent in the data collection process. We explicitly characterize the corruption in the capacitive sensing data due to various lift-off based uncertainties. We use a Bayesian decision theoretic approach to rigorously understand the impact of these corruptions on defec

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Sarma, Sridevi V., David P. Nguyen, Gabriela Czanner, et al. "Computing Confidence Intervals for Point Process Models." Neural Computation 23, no. 11 (2011): 2731–45. http://dx.doi.org/10.1162/neco_a_00198.

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Characterizing neural spiking activity as a function of intrinsic and extrinsic factors is important in neuroscience. Point process models are valuable for capturing such information; however, the process of fully applying these models is not always obvious. A complete model application has four broad steps: specification of the model, estimation of model parameters given observed data, verification of the model using goodness of fit, and characterization of the model using confidence bounds. Of these steps, only the first three have been applied widely in the literature, suggesting the need t

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Krisnawati, Endang, Adji Achmad Rinaldo Fernandes, and Solimun Solimun. "Development of Nonparametric Path Model using Multivariate Adaptive Regression Spline (MARS) Method In Compliance Behavior of Paying Credit In Bank." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (December 20, 2021): 686–95. http://dx.doi.org/10.37394/23203.2021.16.62.

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The purpose of this study is to develop a Non-parametric Path with the MARS (Multivariate Adaptive Regression Spline) approach which is applied to the behavior of paying credit compliance at Bank. prospective debtor by a Bank. The data used in this study is primary data using a research instrument in the form of a questionnaire. There are 7 variables, namely 5 exogenous variables in the form of 5C variables (Character (X1), Capacity (X2), Capital (X3), Collateral (X4), Condition of Economy (X5)), and two endogenous variables, namely Punctual Payment (Y1), Obedient Paying Behavior (Y2). Variabl

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Ma, Runlong, Lan Lan, Guisheng Liao, Jingwei Xu, Fa Wei, and Ximin Li. "Sparse Reconstruction-Based Target Localization with Distributed Waveform-Diverse Array Radars." Remote Sensing 17, no. 13 (2025): 2278. https://doi.org/10.3390/rs17132278.

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This paper addresses the problem of target localization in a distributed waveform diverse array radar system, exploiting the technique of sparse reconstruction. At the configuration stage, the distributed radar system consists of two individual Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) radars and one single Element-Pulse Coding MIMO (EPC-MIMO) radar. To obtain the angle and incremental range (i.e., the range offset between the sampling point and actual position within the range bin) of the targets in each local radar, two sparse reconstruction-based algorithms, includin

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Ülker, Dilan, and Kürşat Timuroğlu. "The Effect of Conflict Management Strategies on Job Satisfaction: A Study in the Accounting Sector." Anadolu Üniversitesi Sosyal Bilimler Dergisi 24, no. 3 (2024): 871–96. http://dx.doi.org/10.18037/ausbd.1340285.

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The aim of this study is to examine the effect of conflict management on job satisfaction for the accounting sectorand to examine the effect between the conflict management strategies used by employees and their job satisfaction. Also, demographic characteristics are to contribute to the related literature by examining the effect of job satisfaction, conflict management, and conflict management strategies. In this study, survey research method and relational screening model were used. Then, e-survey was applied to 451 accounting professionals through convenience sampling among approximately 20

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Levy, Jonathan, Mark van der Laan, Alan Hubbard, and Romain Pirracchio. "A fundamental measure of treatment effect heterogeneity." Journal of Causal Inference 9, no. 1 (2021): 83–108. http://dx.doi.org/10.1515/jci-2019-0003.

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Abstract The stratum-specific treatment effect function is a random variable giving the average treatment effect (ATE) for a randomly drawn stratum of potential confounders a clinician may use to assign treatment. In addition to the ATE, the variance of the stratum-specific treatment effect function is fundamental in determining the heterogeneity of treatment effect values. We offer a non-parametric plug-in estimator, the targeted maximum likelihood estimator (TMLE) and the cross-validated TMLE (CV-TMLE), to simultaneously estimate both the average and variance of the stratum-specific treatmen

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Wang, Pengjiao, Fengqi Guo, Hong Zhang, Junhui Jin, Qiaoyun Liao, and Yongfeng Yan. "Acquiring the High-Precision Spectrum of Track Irregularity by Integrating Inclination in Chord Methods: Mathematics, Simulation, and a Case Study." Mathematics 12, no. 14 (2024): 2197. http://dx.doi.org/10.3390/math12142197.

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Accurate measurement of track irregularity and the corresponding spectrum is essential for evaluating the performance of transportation systems. Chord measuring methods can achieve fine accuracy but are limited by waveform distortion and a restricted range of recoverable wavelength. To address this, this work explores the effectiveness of integrating inclination data in chord-based measurement to obtain a higher precision and more reliable spectrum. Firstly, the theoretical principles and mathematics of the proposed method are described. We demonstrate that by utilizing inclinometer sensors, t

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Lin, Shan, Jianfen Zheng, Yun Lu, Fei Zhao, and Chunfang Wang. "Single-Switch Inverter Wireless Charger with Adaptive Constant Current and Constant Voltage Control by Transmitting Side Sensing Load Changes of Receiving Side." American Journal of Electrical Power and Energy Systems 13, no. 4 (2024): 69–82. https://doi.org/10.11648/j.epes.20241304.12.

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Because of its excellent flexibility, security, reliability and convenience, wireless power transfer(WPT) has become a research hotspot at home and abroad. Currently available WPT technology has the broadest application prospects and can be used in consumer electronics, household appliances, medical equipment, electric vehicles and many other fields. In low-power wireless charging systems such as electric bicycles, volume and cost of the receiving side are required to be minimized. However, in traditional receiving side circuit, compensation network, sampling circuit and wireless communication

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Hastata, Limpat Tri, Sugiyanto, and M. Furqon Hidayatullah. "Adaptive Children'S Management Of Special Education In Special Research School Inclusive Education (Case Study of Management of Adaptive Physical Education at Organizing Middle School Inclusive Education in Boyolali Regency)." Journal of Education, Health and Sport 9, no. 4 (2019): 204–9. https://doi.org/10.5281/zenodo.2631055.

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<strong>Hastata Limpat Tri, Sugiyanto, Hidayatullah M. Furqon. Adaptive Children'S Management Of Special Education In Special Research School Inclusive Education (Case Study of Management of Adaptive Physical Education at Organizing Middle School Inclusive Education in Boyolali Regency).</strong><strong> Journal of Education, Health and Sport. 2019;9(4):</strong><strong>204</strong><strong>-20</strong><strong>9</strong><strong>. eIS</strong><strong>S</strong><strong>N 2391-8306. DOI </strong><strong>http://dx.doi.org/10.5281/zenodo</strong><strong>.</strong><strong>2631055</strong> <strong

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Hermawan, Romy, M. Daniel Septian, and Hayat Hayat. "Impacts of Implementing the Learning Policy on Vocational Higher Education in Post Covid-19 Pandemic." AL-ISHLAH: Jurnal Pendidikan 14, no. 1 (2022): 119–26. http://dx.doi.org/10.35445/alishlah.v14i1.1835.

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This study aimed to describe the influences of learning policies within the period of vocational higher education after the Covid-19 pandemic. The field research design applied the quantitative approach. The research population, 5.915 respondents, came from elements of the academic community at the Vocational Education Program, Brawijaya University, Malang, and the Vocational Faculty, Airlangga University, Surabaya. Then, the sampling technique determined 98 samples based on the Stratified Random Sampling approach. Data collection techniques were supported by questionnaires, documentation, and

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Carrilho, A. C., M. Galo, and R. C. Santos. "STATISTICAL OUTLIER DETECTION METHOD FOR AIRBORNE LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (September 26, 2018): 87–92. http://dx.doi.org/10.5194/isprs-archives-xlii-1-87-2018.

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<p><strong>Abstract.</strong> Sampling the Earth’s surface using airborne LASER scanning (ALS) systems suffers from several factors inherent to the LASER system itself as well as external factors, such as the presence of particles in the atmosphere, and/or multi-path returns due to reflections. The resulting point cloud may therefore contain some outliers and removing them is an important (and difficult) step for all subsequent processes that use this kind of data as input. In the literature, there are several approaches for outlier removal, some of which require external inf

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Bujak, Damjan, Nino Krvavica, Goran Lončar, and Dalibor Carević. "Overtopping over Vertical Walls with Storm Walls on Steep Foreshores." Journal of Marine Science and Engineering 13, no. 7 (2025): 1285. https://doi.org/10.3390/jmse13071285.

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As sea levels rise and extreme weather events become more frequent due to climate change, coastal urban areas are increasingly vulnerable to wave overtopping and flooding. Retrofitting existing vertical seawalls with retreated storm walls represents a key adaptive strategy, especially in the Mediterranean, where steep foreshores and limited public space constrain conventional coastal defenses. This study investigates the effectiveness of storm walls in reducing wave overtopping on vertical walls with steep foreshores (1:7 to 1:10) through high-fidelity numerical simulations using the SWASH mod

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Fusco, Roberta, Adele Piccirillo, Mario Sansone, et al. "Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions." Applied Sciences 11, no. 4 (2021): 1880. http://dx.doi.org/10.3390/app11041880.

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Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malig

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Fusco, Roberta, Elio Di Bernardo, Adele Piccirillo, et al. "Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions." Current Oncology 29, no. 3 (2022): 1947–66. http://dx.doi.org/10.3390/curroncol29030159.

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Purpose:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures were performed. Methods: Fifty-four patients with 79 histo-pathologically proven breast lesions (48 malignant lesions and 31 benign lesions) underwent both CEM and DCE-MRI. The lesions were retrospectively analyzed with radiomic and artificial intelligence approaches. Forty-eight textural metrics were extracted, and

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Zhu, Fang, and Wei Liu. "A novel medical image fusion method based on multi-scale shearing rolling weighted guided image filter." Mathematical Biosciences and Engineering 20, no. 8 (2023): 15374–406. http://dx.doi.org/10.3934/mbe.2023687.

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<abstract><p>Medical image fusion is a crucial technology for biomedical diagnoses. However, current fusion methods struggle to balance algorithm design, visual effects, and computational efficiency. To address these challenges, we introduce a novel medical image fusion method based on the multi-scale shearing rolling weighted guided image filter (MSRWGIF). Inspired by the rolling guided filter, we construct the rolling weighted guided image filter (RWGIF) based on the weighted guided image filter. This filter offers progressive smoothing filtering of the image, generating smooth a

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Kilic, Zeliha, Max Schweiger, Camille Moyer, and Steve Pressé. "Monte Carlo samplers for efficient network inference." PLOS Computational Biology 19, no. 7 (2023): e1011256. http://dx.doi.org/10.1371/journal.pcbi.1011256.

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Accessing information on an underlying network driving a biological process often involves interrupting the process and collecting snapshot data. When snapshot data are stochastic, the data’s structure necessitates a probabilistic description to infer underlying reaction networks. As an example, we may imagine wanting to learn gene state networks from the type of data collected in single molecule RNA fluorescence in situ hybridization (RNA-FISH). In the networks we consider, nodes represent network states, and edges represent biochemical reaction rates linking states. Simultaneously estimating

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Nugroho, Yusanto, Suyanto Suyanto, Gusti Syeransyah Rudy, et al. "A comparison of soil characteristics from four land covers around a coal mining concession area in South Kalimantan." Journal of Degraded and Mining Lands Management 10, no. 1 (2022): 3883. http://dx.doi.org/10.15243/jdmlm.2022.101.3883.

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Understanding soil characteristics is important to determine the alternative strategies of land management, particularly those related to the scheme of soil and water conservation. This study investigated soil characteristics from four land covers around the coal mining concession area located in South Kalimantan. A soil survey was conducted using a purposive sampling method with three replicates in each land cover. Soil samples that were taken at depths of 0-10 cm, 11-20 cm, and 21-30 cm, were composited before being brought to the laboratory to quantify their characteristics, such as texture

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Fusco, Roberta, Adele Piccirillo, Mario Sansone, et al. "Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification." Diagnostics 11, no. 5 (2021): 815. http://dx.doi.org/10.3390/diagnostics11050815.

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The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference st

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Grivas, A., M. Grigoriou, P. Katsimpri, P. Verginis, and D. Boumpas. "POS0413 COMPREHENSIVE IMMUNE PROFILING OF PERIPHERAL BLOOD IN PSORIATIC ARTHRITIS (PsA) PATIENTS: EXPANSION OF INTERMEDIATE MONOCYTES AND DECREASED T REG AND CD8 T CELLS." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 436.1–436. http://dx.doi.org/10.1136/annrheumdis-2021-eular.3540.

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Background:Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis that develops in a subset of patients with psoriasis. According to the current paradigm, cells of the innate and adaptive immunity interact with resident tissue fibroblasts mounting an inflammatory response via complex cytokine networks in the skin and joints in which type 1 and type 17 T cells play a dominant role. The abundance and relative contribution of other peripheral blood immune cells to disease pathogenesis as well the molecular signature of peripheral blood mononuclear cells and tissue fibroblasts remain

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Komolafe, Adebayo Francis. "The Nexus Between Fatigue Indices and Coping Strategies in Sports Among Oyo State Special Athletes." European Scientific Journal, ESJ 14, no. 1 (2018): 151. http://dx.doi.org/10.19044/esj.2018.v14n1p151.

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Disability sports have acquired an indispensable status in the life of many nations and the special athlete as a whole. Special athletes are exposed to a number of intense physical and psychosocial activities and they needed to make use of a set of cognitive and behavioural strategies in order to cope with these challenges and related fatigue. Hitherto, previous studies had focused largely on adaptive sports and effects of sporting activities on persons with disability without establishing a link between disabled athlete’s use of coping strategies and their achievement motivation. Therefore, i

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Petrillo, Antonella, Roberta Fusco, Elio Di Bernardo, et al. "Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography." Cancers 14, no. 9 (2022): 2132. http://dx.doi.org/10.3390/cancers14092132.

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Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. Methods: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually se

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Petrillo, Antonella, Roberta Fusco, Elio Di Bernardo, et al. "Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography." Cancers 14, no. 9 (2022): 2132. http://dx.doi.org/10.3390/cancers14092132.

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Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. Methods: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually se

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Liu, Jiajun, Michael Neely, Jeffrey Lipman, et al. "1573. Population Pharmacokinetic Analyses for Cefepime in Adult and Pediatric Patients." Open Forum Infectious Diseases 6, Supplement_2 (2019): S574—S575. http://dx.doi.org/10.1093/ofid/ofz360.1437.

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Abstract Background Cefepime (CEF) is commonly used for adult and pediatric infections. Several studies have examined CEF’s pharmacokinetics (PK) in various populations; however, a unifying PK model for adult and pediatric subjects does not yet exist. We developed a combined population model for adult and pediatric patients and validated the model. Methods The initial model includes adult and pediatric patients with a rich cefepime sampling design. All adults received 2 g CEF while pediatric subjects received a mean of 49 (SD 5) mg/kg. One- and two-compartment models were considered as base mo

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Hadka, David, and Patrick Reed. "Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework." Evolutionary Computation 21, no. 2 (2013): 231–59. http://dx.doi.org/10.1162/evco_a_00075.

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This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-objective, multimodal optimization. The Borg MOEA combines [Formula: see text]-dominance, a measure of convergence speed named [Formula: see text]-progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization framework. A comparative study on 33 instances of 18 test problems from the DTLZ, WFG, and CEC 2009 test suites demonstrates Borg meets or exceeds six state of the art MOEAs on the majority of the tested problems. The performance for each test problem is evaluat

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