Energy-Driven Image Interpolation Using Gaussian Process Regression by Lingling Zi, Junping Du

“…In our algorithm, each interpolated pixel is predicted by a combination of two information sources: first is a statistical model adopted to mine underlying information, and second is an energy computation technique used to acquire information on pixel properties. …”
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Ship Detection in High-Resolution Dual-Polarization SAR Amplitude Images by Gui Gao, Gongtao Shi, Shilin Zhou

“…Second, the PMA detector’s statistical model has been described by the well-known distribution when facing complex sea background. …”
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Modifications and Statistical Analysis of Acoustic Emission Models Based on the Damage and Fractal Characteristics by Jie Yang, Yanna Zheng, Huijing Wang

“…Damage variable expressions are proposed based on the damage and fractal characteristics firstly. Then, the statistical models for acoustic emission considering damage and fractal characteristics are established by deducing the relationship between acoustic emission parameters and load cycles and fractal dimensions. …”
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Design and Optimization of a Process for Sugarcane Molasses Fermentation by Saccharomyces cerevisiae Using Response Surface Methodology by Nour Sh. El-Gendy, Hekmat R. Madian, Salem S. Abu Amr

“…A statistical model was developed in this study to describe bioethanol production through a batch fermentation process of sugarcane molasses by locally isolated Saccharomyces cerevisiae Y-39. …”
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Cluster production and the chemical freeze-out in expanding hot dense matter by D. Blaschke, S. Liebing, G. Röpke, B. Dönigus

“…In heavy-ion collisions at highest energies provided by the LHC, light cluster abundances should follow the statistical model because of low baryon densities. Chemical freeze-out in this domain is correlated with the QCD crossover transition. …”
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Coupling Sensing Hardware with Data Interrogation Software for Structural Health Monitoring by Charles R. Farrar, David W. Allen, Gyuhae Park, Steven Ball, Michael P. Masquelier

“…In this paradigm, the process can be broken down into four parts: (1) Operational Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction and Data Compression, and (4) Statistical Model Development for Feature Discrimination. …”
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Energy Efficient Distributed Fault Identification Algorithm in Wireless Sensor Networks by Meenakshi Panda, P. M. Khilar

“…The accuracy and completeness of the algorithm are verified with the help of statistical model of the sensors data. The performance is evaluated in terms of detection accuracy, false alarm rate, detection latency and message complexity.…”
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Robust Bayesian Regularized Estimation Based on t Regression Model by Zean Li, Weihua Zhao

“…The t distribution is a useful extension of the normal distribution, which can be used for statistical modeling of data sets with heavy tails, and provides robust estimation. …”
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Dispositif d’accompagnement hybride dans un cours de physique de première année à l’université en Belgique by Elisabeth Gruwé

“…To identify at-risk student profiles in the course, we also constructed statistical models to explore the links between the socio-demographic characteristics and past schooling of first-time enrolled students, their participation in the program, and the grade obtained on the exam. …”
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Excited cluster states: A new source for proton number fluctuations in the high baryon density regime by Boris Tomášik, Marcus Bleicher

“…We calculate the contribution of the decay products of excited nuclear cluster states to the event-by-event fluctuations of protons in the energy range from sNN=2−5 GeV within the statistical model. We find that the inclusion of the excited nuclear clusters yields corrections to all cumulant ratios, ranging from 1% for ratio of second to first-order cumulant to 100% for the sixth to second order cumulant towards the lowest inspected energy. …”
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RELIABILITY OPTIMUM DESIGN OF CONFIDENCE SAMPLES FOR CONSTANT-STRESS ACCELERATED LIFE TEST BASED ON WEIBULL DISTRIBUTION by FENG XueFeng, TANG JiaYin, TAN QiTao

“…In order to realize the rapid reliability evaluation of long-life and high reliability products at a normal stress level, the reliability statistical model of Arrhenius—Weibull was established, by using the Weibull distributions products with the consistent failure mechanism and a log-linear acceleration life test model between characteristic life and stress level. …”
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The Impact of COVID-19 on DTP3 Vaccination Coverage in Europe (2012–2023) by Ines Aguinaga-Ontoso, Sara Guillen-Aguinaga, Laura Guillen-Aguinaga, Rosa Alas-Brun, Miriam Guillen-Aguinaga, Luc Onambele, Enrique Aguinaga-Ontoso, Esperanza Rayón-Valpuesta, Francisco Guillen-Grima

“…Results: The findings revealed significant regional disparities across Europe. Statistical models indicated reductions in DTP3 coverage in countries such as Ireland, Sweden, and Switzerland, whereas Ukraine and San Marino showed improvements. …”
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Optimal receiver and blind demodulation performance bounds for single channel co-frequency mixed signals by YU Hongyi, ZHA Renpeng, SHEN Zhixiang, SHEN Caiyao, HU Yunpeng

“…Based on the sufficient statistics model, a lower bound on the performance of single-channel blind demodulation for co-frequency mixed signals was derived using Forney’s method. …”
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Enhancing collapse performance of vulnerable RC frames through steel Bracing: A FEMA P695 methodology study by Ali Sadeghpour, Giray Ozay

“…Seismic assessments and statistical modeling of desired building responses have gained prominence in research. …”
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Examining the Bus Ridership Demand: Application of Spatio-Temporal Panel Models by Moshiur Rahman, Shamsunnahar Yasmin, Ahmadreza Faghih-Imani, Naveen Eluru

“…An important tool to evaluate the influence of these public transit investments on transit ridership is the application of statistical models. Drawing on stop-level boarding and alighting data for the Greater Orlando region, the current study estimates spatial panel models that accommodate for the impact of spatial and temporal observed and unobserved factors on transit ridership. …”
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Monitoring Model of Concrete Dam Deformation Based on Gray Wolf Optimization Algorithm by CHEN Shuyun, ZHOU Wenzhong, GU Yanchang, WANG Hong

“…Dam deformation is one of the most reliable indicators that can reflect the actual condition of concrete dam.Modeling and analysis of dam deformation monitoring data is an effective way to reflect the operation behavior of concrete dam and seek for the internal law of deformation.In addition,the mathematical model can be applied to predict the deformation.In order to improve the accuracy of modeling and deformation prediction,this paper proposes a deformation monitoring model of concrete dam based on gray wolf optimization algorithm,applies the model to the engineering examples and compares the results with that from the statistical model established by the conventional stepwise regression method and the BP-neural network.The results show that the monitoring model based on the gray wolf optimization algorithm has higher accuracy and better prediction effect.Therefore,the gray wolf algorithm is superior in establishing deformation model,which provides a new reference for deformation analysis and prediction of concrete dam.…”
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Comparisons and validations on MIMO channel simulation models by Xiongwen ZHAO, Bo GAO

“…WINNER and COST2100 channel models are geometry based statistical models，they are the most important channel models for MIMO（multi-input multi-output）system simulations in the fourth generation（4G）radio systems. …”
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Program for Studying Intergenerational Transmissions in Infant Mortality Using the Intermediate Data Structure (IDS) by Luciana Quaranta

“…The current work presents two programs that were developed in STATA to construct a dataset for analysis and run statistical models to study intergenerational transfers in infant mortality using databases that are stored in the IDS. …”
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Program for Studying Intergenerational Transmissions in Infant Mortality Using the Intermediate Data Structure (IDS) by Luciana Quaranta

“…The current work presents two programs that were developed in STATA to construct a dataset for analysis and run statistical models to study intergenerational transfers in infant mortality using databases that are stored in the IDS. …”
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 Increasing the resolution of malaria early warning systems for use by local health actors by Michelle V. Evans, Felana A. Ihantamalala, Mauricianot Randriamihaja, Vincent Herbreteau, Christophe Révillion, Thibault Catry, Eric Delaitre, Matthew H. Bonds, Benjamin Roche, Ezra Mitsinjoniala, Fiainamirindra A. Ralaivavikoa, Bénédicte Razafinjato, Oméga Raobela, Andres Garchitorena

“…Abstract Background The increasing availability of electronic health system data and remotely-sensed environmental variables has led to the emergence of statistical models capable of producing malaria forecasts. …”
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