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accuracy, etc ; exhibitions; models; remote sensing; sampling; satellites; solutions; Show all 7 Subjects
Abstract:
... The main purpose of this article is to evaluate the comprehensive performance of two inter-frequency code bias (IFCB) models using undifferenced and uncombined observations. These two IFCB models estimate IFCB parameters for each GLONASS satellite (EG model) and IFCB parameters using a quadratic function of frequency channels K (K = −7…6) (QF model). The data sampled in 30 s from 140 stations of t ...
accuracy, etc ; accounting; econometrics; humans; inflation; interest (finance); macroeconomics; models; paper; research; time series analysis; Show all 11 Subjects
Abstract:
... This paper demonstrates state-of-the-art text sentiment analysis tools while developing a new time-series measure of economic sentiment derived from economic and financial newspaper articles from January 1980 to April 2015. We compare the predictive accuracy of a large set of sentiment analysis models using a sample of articles that have been rated by humans on a positivity/negativity scale. The r ...
accuracy, etc ; algorithms; artificial intelligence; bias; chemical communication; crystal structure; data collection; materials; physical properties; prediction; Show all 10 Subjects
Abstract:
... Data representation forms a feature space where forms data distribution that is one of the key factors determining the prediction accuracy of machine learning (ML). In particular, the data representation is crucial to handle small and biased training datasets, which is the main challenge of ML in chemical applications. In this paper, we propose a data-agnostic representation method that automatica ...
... One important indicator for the wellbeing status of livestock is their daily behavior. More often than not, daily behavior recognition involves detecting the heads or body gestures of the livestock using conventional methods or tools. To prevail over such limitations, an effective approach using deep learning is proposed in this study for cattle behavior recognition. The approach for detecting the ...
accuracy, etc ; algorithms; data collection; design; exhibitions; extracts; hulling; hulls; image analysis; model validation; neural networks; remote sensing; shipping; ships; Show all 14 Subjects
Abstract:
... The mainstream algorithms used for ship classification and detection can be improved based on convolutional neural networks (CNNs). By analyzing the characteristics of ship images, we found that the difficulty in ship image classification lies in distinguishing ships with similar hull structures but different equipment and superstructures. To extract features such as ship superstructures, this pap ...
... The yield of product (cheese) during the cheese-making process depends on the cutting time of the cheese curd. However, the determination of optimal cutting time on an industrial scale is difficult as current standard methods are destructive or analyse only small volumes and not the entire milk to be curdled into cheese. This paper presents a novel front-face fluorimeter (FFF) that is designed to ...
... A new procedure is proposed for selecting the input value for the adaptation bandwidth λ in nonparametric Gaussian regression via Propagation–Separation approach. Since λ stands at the bias–variance trade-off of this estimation technique, it is its key tuning parameter. So far, however, apart from theoretical concepts, there exists no approach for a data-driven choice of its input value. This comp ...
accuracy, etc ; models; paper; remote sensing; satellites; Show all 5 Subjects
Abstract:
... The BeiDou Navigation Satellite System (BDS) features a heterogeneous constellation so that it is difficult to mitigate the multipath in the coordinate-domain. Therefore, mitigating the multipath in the observation-domain becomes more important. Sidereal filtering is commonly used for multipath mitigation, which needs to calculate the orbit repeat time of each satellite. However, that poses a comp ...
accuracy, etc ; cooling systems; exhibitions; models; particles; Show all 5 Subjects
Abstract:
... Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is ...
accuracy, etc ; algorithms; data analysis; prediction; regression analysis; Show all 5 Subjects
Abstract:
... Gradient boosting algorithms construct a regression predictor using a linear combination of “base learners”. Boosting also offers an approach to obtaining robust non-parametric regression estimators that are scalable to applications with many explanatory variables. The robust boosting algorithm is based on a two-stage approach, similar to what is done for robust linear regression: it first minimiz ...
accuracy, etc ; algorithms; classification; mutation; paper; particles; remote sensing; Show all 7 Subjects
Abstract:
... In indoor target tracking based on wireless sensor networks, the particle filtering algorithm has been widely used because of its outstanding performance in coping with highly non-linear problems. Resampling is generally required to address the inherent particle degeneracy problem in the particle filter. However, traditional resampling methods cause the problem of particle impoverishment. This pro ...
accuracy, etc ; graphs; journals; linear models; prunes; pruning; variance; Show all 7 Subjects
Abstract:
... Covariate adjustment is a commonly used method for total causal effect estimation. In recent years, graphical criteria have been developed to identify all valid adjustment sets, that is, all covariate sets that can be used for this purpose. Different valid adjustment sets typically provide total causal effect estimates of varying accuracies. Restricting ourselves to causal linear models, we introd ...
Dorrain Yanwen Low; Pierre Micheau; Ville Mikael Koistinen; Kati Hanhineva; László Abrankó; Ana Rodriguez-Mateos; Andreia Bento da Silva; Christof van Poucke; Conceição Almeida; Cristina Andres-Lacueva; Dilip K. Rai; Esra Capanoglu; Francisco A. Tomás Barberán; Fulvio Mattivi; Gesine Schmidt; Gözde Gürdeniz; Kateřina Valentová; Letizia Bresciani; Lucie Petrásková; Lars Ove Dragsted; Mark Philo; Marynka Ulaszewska; Pedro Mena; Raúl González-Domínguez; Rocío Garcia-Villalba; Senem Kamiloglu; Sonia de Pascual-Teresa; Stéphanie Durand; Wieslaw Wiczkowski; Maria Rosário Bronze; Jan Stanstrup; Claudine Manach
accuracy, etc ; chromatography; food chemistry; metabolites; metabolomics; prediction; shape; width; Show all 8 Subjects
Abstract:
... Prediction of retention times (RTs) is increasingly considered in untargeted metabolomics to complement MS/MS matching for annotation of unidentified peaks. We tested the performance of PredRet (http://predret.org/) to predict RTs for plant food bioactive metabolites in a data sharing initiative containing entry sets of 29–103 compounds (totalling 467 compounds, >30 families) across 24 chromatogra ...
accuracy, etc ; algorithms; design; fuel cells; mathematical models; system optimization; Show all 6 Subjects
Abstract:
... A joint operation method is proposed in this study for collaborative design of multi-type parameters in direct methanol fuel cell system. This method consists of adaptive numerical simulation for fuel cell operation and adaptive optimal design of the fuel cell system. The simulation key coefficients are designed to be changed following the multi-type parameters variations in order to achieve adapt ...
accuracy, etc ; algorithms; data analysis; density; dimensions; estimation; mixtures; variance; Show all 8 Subjects
Abstract:
... Efficient algorithms for computing the distribution function, (log-)density function and for estimating the parameters of multivariate normal variance mixtures are introduced. For the evaluation of the distribution function, randomized quasi-Monte Carlo (RQMC) methods are utilized in a way that improves upon existing methods proposed for the special case of normal and t distributions. For evaluati ...
accuracy, etc ; auctions; bias; food safety; freshness; information; markets; paper; Show all 8 Subjects
Abstract:
... Freshness is an essential attribute of agricultural products. To meet consumers' demand, suppliers take multiple methods to provide fresher products. But sometimes the effort does not get paid because of quality perception bias. In this study, we investigated the existence of quality perception bias and the effect of reference points. Our results confirmed the existence of quality perception bias. ...
accuracy, etc ; data collection; design; learning; neural networks; remote sensing; Show all 6 Subjects
Abstract:
... Meta-learning is an effective way to deal with the few-shot problem that only very few annotated data samples are available for training the model. In remote sensing scene classification, previous methods with meta-learning often apply a shallow neural network due to lacking sufficient annotated training data that can support the larger number of parameters of a deep neural network (DNN). However, ...
accuracy, etc ; Europeans; journals; prototypes; screws; testing; theoretical models; wood; Show all 8 Subjects
Abstract:
... Self-tapping wood screws are important fasteners in timber construction. A characteristic of these screws is their high axial load-bearing capacity, which also depends on their withdrawal capacity. This is used for structural design and is thus an important optimization parameter for wood screws. To increase the withdrawal capacity, knowledge of the influence of the thread parameters, such as oute ...
accuracy, etc ; food intake; heart rate; hunger; research; risk; satiety; Show all 7 Subjects
Abstract:
... Research supports an association between altered interoceptive accuracy, or the ability to accurately monitor sensations from the body, and disordered eating. However, the behavioral mechanism through which interoceptive accuracy may influence eating behaviors is unclear. Intuitive eating, the ability to regulate food intake according to visceral cues of hunger and satiety, is positively related t ...
accuracy, etc ; activation energy; information; kinetics; models; prediction; sampling; sounds; Show all 8 Subjects
Abstract:
... Isoconversional analysis is a model-free and powerful approach that readily provide quantitative information of the kinetics of a thermally activated transformation. Activation energy and preexponential factor are the main output of isoconversional analysis. Another practical application is the kinetic predictions that are computed in a model-free way. In this communication, a computational tool o ...