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1. Evaluating the Performance of Two Inter-Frequency Code Bias (IFCB) Models in Combined Precise Point Positioning (PPP)

Author:
Ban Zhao; Yongliang Xiong
Source:
Remote Sensing 2022 v.14 no.6 pp. -
ISSN:
2072-4292
Subject:
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 ...
DOI:
10.3390/rs14061476

2. Measuring news sentiment

Author:
Adam Hale Shapiro; Moritz Sudhof; Daniel J. Wilson
Source:
Journal of econometrics 2022 v.228 no.2 pp. 221-243
ISSN:
0304-4076
Subject:
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 ...
DOI:
10.1016/j.jeconom.2020.07.053

3. Contrastive representation learning of inorganic materials to overcome lack of training datasets

Author:
Gyoung S. Na; Hyun Woo Kim
Source:
Chemical communications 2022 v.58 no.47 pp. 6729-6732
ISSN:
1364-548X
Subject:
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 ...
DOI:
10.1039/d2cc01764d

4. Behavior Recognition of Group-ranched Cattle from Video Sequences using Deep Learning

Author:
Rotimi-Williams Bello; Ahmad Sufril Azlan Mohamed; Abdullah Zawawi Talib; Salisu Sani; Mohd Nadhir Ab Wahab
Source:
Indian journal of animal research 2022 v.56 no.4 pp. 505-512
ISSN:
0976-0555
Subject:
accuracy,   etc   ; animal research; behavior; beverages; cows; design; drinking; head; high-throughput nucleotide sequencing; journals; laboratory animals; models; nucleotide sequences;     Show all 13 Subjects
Abstract:
... 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 ...
DOI:
10.18805/IJAR.B-1369

5. Fine-Grained Ship Classification by Combining CNN and Swin Transformer

Author:
Liang Huang; Fengxiang Wang; Yalun Zhang; Qingxia Xu
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
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 ...
DOI:
10.3390/rs14133087

6. Front-Face Fluorimeter for the Determination of Cutting Time of Cheese Curd

Author:
Maryna Lazouskaya; Irina Stulova; Aavo Sõrmus; Ott Scheler; Kalle Tiisma; Toomas Vinter; Roman Loov; Martti Tamm
Source:
Foods 2021 v.10 no.3 pp. -
ISSN:
2304-8158
Subject:
accuracy,   etc   ; cheesemaking; cheeses; milk; paper;     Show all 5 Subjects
Abstract:
... 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 ...
DOI:
10.3390/foods10030576

7. On data-driven choice of [formula omitted] in nonparametric Gaussian regression via Propagation–Separation approach

Author:
Ewelina Marta Fiebig
Source:
Computational statistics & data analysis 2021 v.154 pp. 107087
ISSN:
0167-9473
Subject:
accuracy,   etc   ; data analysis; estimation; sample size;     Show all 4 Subjects
Abstract:
... 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 ...
DOI:
10.1016/j.csda.2020.107087

8. A Single-Difference Multipath Hemispherical Map for Multipath Mitigation in BDS-2/BDS-3 Short Baseline Positioning

Author:
Chao Liu; Yuan Tao; Haiqiang Xin; Xingwang Zhao; Chunyang Liu; Haojie Hu; Tengfei Zhou
Source:
Remote Sensing 2021 v.13 no.2 pp. -
ISSN:
2072-4292
Subject:
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 ...
DOI:
10.3390/rs13020304

9. An error-controlled adaptive time-stepping method for particle advancement in coupled CFD-DEM simulations

Author:
Hariswaran Sitaraman; Deepthi Vaidhynathan; Ray Grout; Thomas Hauser; Christine M. Hrenya; Jordan Musser
Source:
Powder technology 2021 v.379 pp. 203-216
ISSN:
0032-5910
Subject:
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 ...
DOI:
10.1016/j.powtec.2020.10.051

10. Robust boosting for regression problems

Author:
Xiaomeng Ju; Matías Salibián-Barrera
Source:
Computational statistics & data analysis 2021 v.153 pp. 107065
ISSN:
0167-9473
Subject:
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 ...
DOI:
10.1016/j.csda.2020.107065

11. A Genetic Optimization Resampling Based Particle Filtering Algorithm for Indoor Target Tracking

Author:
Ning Zhou; Lawrence Lau; Ruibin Bai; Terry Moore
Source:
Remote Sensing 2021 v.13 no.1 pp. -
ISSN:
2072-4292
Subject:
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 ...
DOI:
10.3390/rs13010132

12. Graphical criteria for efficient total effect estimation via adjustment in causal linear models

Author:
Leonard Henckel; Emilija Perković; Marloes H. Maathuis
Source:
Journal of the Royal Statistical Society 2022 v.84 no.2 pp. 579-599
ISSN:
1369-7412
Subject:
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 ...
DOI:
10.1111/rssb.12451

13. Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds

Author:
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
Source:
Food chemistry 2021 v.357 pp. 129757
ISSN:
0308-8146
Subject:
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 ...
DOI:
10.1016/j.foodchem.2021.129757

14. Joint operation of adaptive numerical simulation and adaptive optimization for direct methanol fuel cell performance improvement

Author:
Qinwen Yang; Shujun Chen; Gang Xiao; Lexi Li; Tao Liu; Jianghua Feng
Source:
Journal of cleaner production 2021 v.289 pp. 125630
ISSN:
0959-6526
Subject:
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 ...
DOI:
10.1016/j.jclepro.2020.125630

15. Normal variance mixtures: Distribution, density and parameter estimation

Author:
Erik Hintz; Marius Hofert; Christiane Lemieux
Source:
Computational statistics & data analysis 2021 v.157 pp. 107175
ISSN:
0167-9473
Subject:
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 ...
DOI:
10.1016/j.csda.2021.107175

16. Bias and reference-dependence in quality perception of freshness: Analysis based on experimental auction and physical &chemical tests

Author:
Jiehong Zhou; Hao Huang; Zhifeng Gao; Ye Song; Zhen Yan
Source:
Food control 2021 v.126 pp. 108077
ISSN:
0956-7135
Subject:
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. ...
DOI:
10.1016/j.foodcont.2021.108077

17. Meta-learning based on parameter transfer for few-shot classification of remote sensing scenes

Author:
Chenhui Ma; Xiaodong Mu; Peng Zhao; Xin Yan
Source:
Remote sensing letters 2021 v.12 no.6 pp. 531-541
ISSN:
2150-7058
Subject:
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, ...
DOI:
10.1080/2150704X.2021.1903609

18. Wood screw design: influence of thread parameters on the withdrawal capacity

Author:
Kevin Hoelz; Lukas Kleinhans; Sven Matthiesen
Source:
European journal of wood and wood products 2021 v.79 no.4 pp. 773-784
ISSN:
0018-3768
Subject:
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 ...
DOI:
10.1007/s00107-021-01668-4

19. Intuitive eating mediates the relationship between interoceptive accuracy and eating disorder risk

Author:
Danielle C. DeVille; Mindy J. Erchull; Jennifer R. Mailloux
Source:
Eating behaviors 2021 v.41 pp. 101495
ISSN:
1471-0153
Subject:
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 ...
DOI:
10.1016/j.eatbeh.2021.101495

20. Isoconversional computations for nonisothermal kinetic predictions

Author:
Lérys Granado; Nicolas Sbirrazzuoli
Source:
Thermochimica acta 2021 v.697 pp. 178859
ISSN:
0040-6031
Subject:
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 ...
DOI:
10.1016/j.tca.2020.178859