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1. Feature transfer based adversarial domain adaptation method for cross-domain road extraction

Author:
Shuyang Wang; Xiaodong Mu; Hao He; Dongfang Yang; Peng Zhao
Source:
Geocarto international 2022 v.37 no.2 pp. 445-455
ISSN:
1752-0762
Subject:
learning,   etc   ; extracts; image analysis; roads;     Show all 4 Subjects
Abstract:
... In order to improve the cross-domain applicability of road segmentation, a feature transfer based adversarial domain adaptation method is presented for cross-domain road extraction. The presented method consists of two main parts, a feature transfer network and an adversarial domain adaption network. The feature transfer network transforms the images of the source domain into the feature space of ...
DOI:
10.1080/10106049.2020.1753819

2. Perspective: Scientific rigor or ritual? Statistical significance in pest management science

Author:
Brendan CS Alexander; Adam S Davis
Source:
Pest management science 2022 v.78 no.3 pp. 847-854
ISSN:
1526-498X
Subject:
learning,   etc   ; bioactive properties; byproducts; pest management;     Show all 4 Subjects
Abstract:
... P values, binary hypothesis tests, and statistical significance are too often overused or used incorrectly in pest management reports. These statistical results are not the point of an analysis, they are just a by‐product that can sometimes be informative. The point of the analysis is always a biological interpretation of the data focusing on whether something new has been learned and then quantif ...
DOI:
10.1002/ps.6668

3. A comparison of testing and estimation of firm conduct

Author:
Lorenzo Magnolfi; Christopher Sullivan
Source:
Economics letters 2022 v.212 pp. 110316
ISSN:
0165-1765
Subject:
learning,   etc   ; econometric models; economic theory; testing;     Show all 4 Subjects
Abstract:
... Researchers both test and estimate structural models to learn firm conduct. As testing imposes candidate models suggested by economic theory, it is less demanding of the instruments. However, relative performance under misspecification depends on whether a candidate model approximates the truth. ...
DOI:
10.1016/j.econlet.2022.110316

4. Number-of-responses matching in pigeons (Columba livia): Choice biases following delay and no-sample tests

Author:
Carlos Pinto; Márcio Mota
Source:
Behavioural processes 2022 v.196 pp. 104605
ISSN:
0376-6357
Subject:
learning,   etc   ; Columba livia; pecking; pigeons; sampling; testing;     Show all 6 Subjects
Abstract:
... In a symbolic matching-to-sample task, pigeons learned to discriminate between 5 and 15 key pecks (samples): different choices were correct following the smaller and the larger response requirements. Subsequently, accuracy was tested in delayed matching, with the delay spent in darkness, contrarily to previous studies, that used illuminated delays. On average, delayed choices reflected indifferenc ...
DOI:
10.1016/j.beproc.2022.104605

5. Beyond “blah blah blah”: exploring the “how” of transformation

Author:
Julia Bentz; Karen O’Brien; Morgan Scoville-Simonds
Source:
Sustainability science 2022 v.17 no.2 pp. 497-506
ISSN:
1862-4065
Subject:
learning,   etc   ; paper; sustainability science and engineering; weaving; wills;     Show all 5 Subjects
Abstract:
... Calls for transformations are clear and multiple pathways and alternative visions for the future have been defined. Yet, there is very little shared understanding of how such transformations come about and how knowledge-action gaps will be filled. This Special Feature focuses on how we can go beyond talking about transformation—the “blah blah blah”—and moving toward action for results. It does so ...
DOI:
10.1007/s11625-022-01123-0

6. Selection of learning strategies supported on SMAA-M

Author:
Rafael Guillermo García-Cáceres; Arnoldo Emilio Delgado-Tobón; John Wilmer Escobar-Velásquez
Source:
Heliyon 2022 v.8 no.2 pp. e08978
ISSN:
2405-8440
Subject:
learning,   etc   ; color; decision making; exhibitions; solutions; students; teachers;     Show all 7 Subjects
Abstract:
... The present work introduces a systematic decision making process which, based on Stochastic Multicriteria Acceptability Analysis – Matching, is aimed at supporting the selection of pedagogical strategies according to the theoretical paradigms provided by the Color Theory and the Learning Styles concept. This novel procedure is illustrated by an example which allowed comparison with the traditional ...
DOI:
10.1016/j.heliyon.2022.e08978

7. scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

Author:
Kun Qian; Shiwei Fu; Hongwei Li; Wei Vivian Li
Source:
Genome biology 2022 v.23 no.1 pp. 82
ISSN:
1474-760X
Subject:
learning,   etc   ; gene expression; gene expression regulation; genome; methodology;     Show all 5 Subjects
Abstract:
... The increasing number of scRNA-seq data emphasizes the need for integrative analysis to interpret similarities and differences between single-cell samples. Although different batch effect removal methods have been developed, none are suitable for heterogeneous single-cell samples coming from multiple biological conditions. We propose a method, scINSIGHT, to learn coordinated gene expression patter ...
DOI:
10.1186/s13059-022-02649-3

8. Interaction between cognitive styles and genders when using virtual laboratories and its influence on students of health college’s laboratory skills and cognitive load during the Corona pandemic

Author:
Usama M. Ibrahem; Bandar S. Alsaif; Munthir Alblaihed; Sameh S.I. Ahmed; Haisam A. Alshrif; Rabab A. Abdulkader; Hanan M. Diab
Source:
Heliyon 2022 v.8 no.4 pp. e09213
ISSN:
2405-8440
Subject:
electronic learning,   etc   ; cognition; females; males; microbiology; pandemic; surveys;     Show all 7 Subjects
Abstract:
... This study examined the interaction between cognitive style–gender within Virtual Laboratories (VL) and its influence on students of health college’s Laboratory Skills (LS) and Cognitive Load (CL) during the Corona pandemic. This research method is a combination of quasi-experimental research and survey research; consisting of two male and two female experimental groups (contemplative and impulsiv ...
DOI:
10.1016/j.heliyon.2022.e09213

9. Video Satellite Imagery Super-Resolution via Model-Based Deep Neural Networks

Author:
Zhi He; Xiaofang Li; Rongning Qu
Source:
Remote Sensing 2022 v.14 no.3 pp. -
ISSN:
2072-4292
Subject:
learning,   etc   ; image analysis; neural networks; remote sensing; satellites;     Show all 5 Subjects
Abstract:
... Video satellite imagery has become a hot research topic in Earth observation due to its ability to capture dynamic information. However, its high temporal resolution comes at the expense of spatial resolution. In recent years, deep learning (DL) based super-resolution (SR) methods have played an essential role to improve the spatial resolution of video satellite images. Instead of fully considerin ...
DOI:
10.3390/rs14030749

10. Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning

Author:
Junfeng Zhou; Yanhui Zhang; Yubo Zhang; Wen-Long Shang; Zhile Yang; Wei Feng
Source:
Applied energy 2022 v.314 pp. 118877
ISSN:
0306-2619
Subject:
learning,   etc   ; algorithms; energy; evolutionary adaptation; models; problem solving; testing;     Show all 7 Subjects
Abstract:
... The performance of photovoltaic (PV) cell is affected by the model structure and corresponding parameters. However, these parameters are adjustable and variable, which play an available role in regarding to the efficiency and effectiveness of PV generation. Due to strong non-linear characteristics, existing PV model parameters identification methods cannot easily obtain accurate solutions. To tack ...
DOI:
10.1016/j.apenergy.2022.118877

11. A personal view on basic education in reproduction: Where are we now and where are we going?

Author:
F. Herman Jonker
Source:
Reproduction in domestic animals 2022 v.57 Suppl S1 pp. 7-15
ISSN:
0936-6768
Subject:
electronic learning,   etc   ; computer simulation; education; reproduction; veterinary medicine; Netherlands;     Show all 6 Subjects
Abstract:
... This article explores the current and expected direction of education in reproduction at the Faculty of Veterinary Medicine of Utrecht University. The current reproductive course in the Bachelor's programme is described. Based on the yearly routine course evaluation, changes have been started and continue to be implemented, and the educational ideas behind it are defined. Interactive e‐learning mo ...
DOI:
10.1111/rda.13769

12. Dual Modality Collaborative Learning for Cross-Source Remote Sensing Retrieval

Author:
Jingjing Ma; Duanpeng Shi; Xu Tang; Xiangrong Zhang; Licheng Jiao
Source:
Remote Sensing 2022 v.14 no.6 pp. -
ISSN:
2072-4292
Subject:
learning,   etc   ; data collection; extractors; image analysis; models; remote sensing; satellites;     Show all 7 Subjects
Abstract:
... Content-based remote sensing (RS) image retrieval (CBRSIR) is a critical way to organize high-resolution RS (HRRS) images in the current big data era. The increasing volume of HRRS images from different satellites and sensors leads to more attention to the cross-source CSRSIR (CS-CBRSIR) problem. Due to the data drift, one crucial problem in CS-CBRSIR is the modality discrepancy. Most existing met ...
DOI:
10.3390/rs14061319

13. Efficient learning of optimal individualized treatment rules for heteroscedastic or misspecified treatment‐free effect models

Author:
Weibin Mo; Yufeng Liu
Source:
Journal of the Royal Statistical Society 2022 v.84 no.2 pp. 440-472
ISSN:
1369-7412
Subject:
electronic learning,   etc   ; heteroskedasticity; noninsulin-dependent diabetes mellitus; observational studies; variance;     Show all 5 Subjects
Abstract:
... Recent development in data‐driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outcomes, researchers can search for the optimal individualized treatment rule (ITR) that maximizes the expected outcome. Existing methods typically require initial estimation of some nuisance models. The double robustness pr ...
DOI:
10.1111/rssb.12474

14. The university students’ viewpoints on e-learning system during COVID-19 pandemic: the case of Iran

Author:
Arash Salahshouri; Kaveh Eslami; Hatam Boostani; Mansour Zahiri; Simin Jahani; Reza Arjmand; Akbar Babaei Heydarabadi; Behzad Fouladi Dehaghi
Source:
Heliyon 2022 v.8 no.2 pp. e08984
ISSN:
2405-8440
Subject:
electronic learning,   etc   ; COVID-19 infection; complement; qualitative analysis; questionnaires; Iran;     Show all 6 Subjects
Abstract:
... The outbreak of COVID-19 closed educational institutions and universities. The aim of this study was to explain the strengths and weaknesses of the e-learning system in Iranian universities of medical sciences in the COVID-19 pandemic. This is a qualitative study that was conducted with students enrolled in Iranian medical universities. Data was collected through an open-ended electronic questionn ...
DOI:
10.1016/j.heliyon.2022.e08984

15. Assessing the spontaneous use of human-given cues in ground-hornbills

Author:
Samara Danel; Nancy Rebout; Lucy Valeska Kemp
Source:
Behavioural processes 2022 v.199 pp. 104659
ISSN:
0376-6357
Subject:
learning,   etc   ; Bucorvus leadbeateri; baiting; baits; birds; containers; exhibitions; foods; humans;     Show all 9 Subjects
Abstract:
... A wide range of species relies on heterospecific visual cues to detect the location of resources like food. Although different hypotheses have been suggested to explain the emergence of this capacity in animals, results are often difficult to interpret due to the influence of other factors, such as close contact with humans. In this study, we presented eight Southern ground-hornbills (Bucorvus lea ...
DOI:
10.1016/j.beproc.2022.104659

16. Latent Low-Rank Projection Learning with Graph Regularization for Feature Extraction of Hyperspectral Images

Author:
Lei Pan; Hengchao Li; Xiang Dai; Ying Cui; Xifeng Huang; Lican Dai
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
learning,   etc   ; dimensions; extracts; graphs; hyperspectral imagery; models; remote sensing; windows;     Show all 8 Subjects
Abstract:
... Due to the great benefit of rich spectral information, hyperspectral images (HSIs) have been successfully applied in many fields. However, some problems of concern also limit their further applications, such as high dimension and expensive labeling. To address these issues, an unsupervised latent low-rank projection learning with graph regularization (LatLRPL) method is presented for feature extra ...
DOI:
10.3390/rs14133078

17. Structurally re-parameterized rotation detector for arbitrary-oriented objects in high-resolution remote sensing images

Author:
Jimiao Tian; Jing Zhang; Wensheng Li; Jiafeng Li; Li Zhuo
Source:
International journal of remote sensing 2022 v.43 no.1 pp. 241-269
ISSN:
1366-5901
Subject:
learning,   etc   ; data collection; detectors; image analysis; journals; refining; remote sensing;     Show all 7 Subjects
Abstract:
... Horizontal bounding boxes are inflexible for precisely locating geospatial objects with arbitrary orientations in high-resolution remote sensing images. Recently, rotation detectors with oriented bounding boxes have been found to have a positive effect on the detection of arbitrary-oriented objects. However, this method usually suffers from the requirement of a heavy network structure to learn ori ...
DOI:
10.1080/01431161.2021.2012294

18. Densely Residual Network with Dual Attention for Hyperspectral Reconstruction from RGB Images

Author:
Lixia Wang; Aditya Sole; Jon Yngve Hardeberg
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
learning,   etc   ; data collection; hyperspectral imagery; image analysis; remote sensing; spatial data;     Show all 6 Subjects
Abstract:
... In the last several years, deep learning has been introduced to recover a hyperspectral image (HSI) from a single RGB image and demonstrated good performance. In particular, attention mechanisms have further strengthened discriminative features, but most of them are learned by convolutions with limited receptive fields or require much computational cost, which hinders the function of attention mod ...
DOI:
10.3390/rs14133128

19. Gamification and citizen motivation and vitality in smart cities: a qualitative meta-analysis study

Author:
Gholam Reza Latifi; Masoumeh Poor Monfared; Hasan Abdi Khojasteh
Source:
GeoJournal 2022 v.87 no.2 pp. 1217-1230
ISSN:
0343-2521
Subject:
electronic learning,   etc   ; citizen science; databases; education; meta-analysis; motivation; researchers; trade;     Show all 8 Subjects
Abstract:
... Gamification has attracted the attention of many scholars of different fields such as education, commerce, management, urban planning, and citizen science since a decade ago. The review of the related literature indicates that there is a plethora of research on the implications of gamification in various fields. However, to the best of the researcher, these studies have not been synthesized yet. T ...
DOI:
10.1007/s10708-020-10295-0

20. Spectral-spatial classification method for hyperspectral images using stacked sparse autoencoder suitable in limited labelled samples situation

Author:
Seyyed Ali Ahmadi; Nasser Mehrshad; Seyyed Mohammadali Arghavan
Source:
Geocarto international 2022 v.37 no.7 pp. 2031-2054
ISSN:
1752-0762
Subject:
learning,   etc   ; data collection; distance education; hyperspectral imagery; model validation; spatial data;     Show all 6 Subjects
Abstract:
... Recently, deep learning (DL)-based methods have attracted increasing attention for hyperspectral images (HSIs) classification. However, the complex structure and limited number of labelled training samples of HSIs negatively affect the performance of DL models. In this paper, a spectral-spatial classification method is proposed based on the combination of local and global spatial information, incl ...
DOI:
10.1080/10106049.2020.1797188