Relevant bibliographies by topics / Weight labels

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Weight labels'

Author: Grafiati
Published: 7 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Weight labels"

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Wang, Zhe, Hao Xu, Pan Zhou, and Gang Xiao. "An Improved Multilabel k-Nearest Neighbor Algorithm Based on Value and Weight." Computation 11, no. 2 (2023): 32. http://dx.doi.org/10.3390/computation11020032.

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Multilabel data share important features, including label imbalance, which has a significant influence on the performance of classifiers. Because of this problem, a widely used multilabel classification algorithm, the multilabel k-nearest neighbor (ML-kNN) algorithm, has poor performance on imbalanced multilabel data. To address this problem, this study proposes an improved ML-kNN algorithm based on value and weight. In this improved algorithm, labels are divided into minority and majority, and different strategies are adopted for different labels. By considering the label of latent informatio
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Haunert, Jan-Henrik, and Alexander Wolff. "BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 109–14. http://dx.doi.org/10.5194/isprs-archives-xli-b2-109-2016.

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Map labeling is a classical problem of cartography that has frequently been approached by combinatorial optimization. Given a set of features in the map and for each feature a set of label candidates, a common problem is to select an independent set of labels (that is, a labeling without label–label overlaps) that contains as many labels as possible and at most one label for each feature. To obtain solutions of high cartographic quality, the labels can be weighted and one can maximize the total weight (rather than the number) of the selected labels. We argue, however, that when maximizing the
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Haunert, Jan-Henrik, and Alexander Wolff. "BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 109–14. http://dx.doi.org/10.5194/isprsarchives-xli-b2-109-2016.

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Map labeling is a classical problem of cartography that has frequently been approached by combinatorial optimization. Given a set of features in the map and for each feature a set of label candidates, a common problem is to select an independent set of labels (that is, a labeling without label–label overlaps) that contains as many labels as possible and at most one label for each feature. To obtain solutions of high cartographic quality, the labels can be weighted and one can maximize the total weight (rather than the number) of the selected labels. We argue, however, that when maximizing the
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D’Angelo Campos, Aline, Anna H. Grummon, Shu Wen Ng, Rebecca M. Puhl, Shelley D. Golden, and Marissa G. Hall. "Front-of-Package Food Labels and Perceived Weight Stigmatization." JAMA Network Open 8, no. 6 (2025): e2516821. https://doi.org/10.1001/jamanetworkopen.2025.16821.

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ImportanceFront-of-package food labels (FOPLs) about nutrient content and health effects are a promising policy to improve diet quality but may also contribute to harmful weight stigma.ObjectiveTo assess whether different types of FOPLs impact perceived weight stigmatization, whether weight-neutral label content mitigates stigmatization, and possible trade-offs between perceived stigmatization and effectiveness.Design, Setting, and ParticipantsThis randomized clinical trial with a between- and within-participant design used a single-exposure online survey conducted from January 18 to 26, 2024.
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Wang, Wanzhu, and Yong Liu. "Multi-label Feature Selection based on Label-specific features and Manifold Learning." Academic Journal of Science and Technology 10, no. 1 (2024): 364–69. http://dx.doi.org/10.54097/astymd16.

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Each instance in multi-label data is associated with multiple labels, and there are irrelevant or redundant features in its feature space, which leads to the performance degradation of multi-label learning algorithms. Multi-label feature selection selects representative features from the feature space to improve the accuracy of the model. Due to the high cost of labels and the difficulty of data collection, there will be some missing labels in the data set, which affects the accuracy of feature selection. To solve this problem, a multi-label feature selection algorithm based on label-specific
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Bača, Martin, Mirka Miller, Oudone Phanalasy, Joe Ryan, Andrea Semaničová Feňovčíková, and Anita A. Sillasen. "Total Labelings of Graphs with Prescribed Weights." Journal of Combinatorial Mathematics and Combinatorial Computing 120, no. 1 (2024): 367–76. http://dx.doi.org/10.61091/jcmcc120-33.

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The total labeling of a graph G = ( V , E ) is a bijection from the union of the vertex set and the edge set of G to the set { 1 , 2 , … , | V ( G ) | + | E ( G ) | } . The edge-weight of an edge under a total labeling is the sum of the label of the edge and the labels of the end vertices of that edge. The vertex-weight of a vertex under a total labeling is the sum of the label of the vertex and the labels of all the edges incident with that vertex. A total labeling is called edge-magic or vertex-magic when all the edge-weights or all the vertex-weights are the same, respectively. When all the
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Zhang, Yaojie, Huahu Xu, Junsheng Xiao, and Minjie Bian. "JoSDW: Combating Noisy Labels by Dynamic Weight." Future Internet 14, no. 2 (2022): 50. http://dx.doi.org/10.3390/fi14020050.

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The real world is full of noisy labels that lead neural networks to perform poorly because deep neural networks (DNNs) are prone to overfitting label noise. Noise label training is a challenging problem relating to weakly supervised learning. The most advanced existing methods mainly adopt a small loss sample selection strategy, such as selecting the small loss part of the sample for network model training. However, the previous literature stopped here, neglecting the performance of the small loss sample selection strategy while training the DNNs, as well as the performance of different stages
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A. S., Saranya, and Santhosh Kumar K. R. "On the total edge irregularity strength of certain classes of cycle related graphs." Proyecciones (Antofagasta) 43, no. 1 (2024): 53–67. http://dx.doi.org/10.22199/issn.0717-6279-5728.

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For a graph G=(V,E), an edge irregular total k-labeling is a labeling of the vertices and edges of G with labels from the set {1, 2, ..., k } such that any two different edges have distinct weights. The sum of the label of edge uv and the labels of vertices u and v determines the weight of the edge uv. The smallest possible k for which the graph G has an edge irregular total k-labeling is called the total edge irregularity strength of G. We determine the exact value of the total edge irregularity strength for some cycle related graphs.
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Karaca, Adeviyye, Kamil Can Akyol, Mustafa Keşaplı, et al. "Do Clothing Labels Play a Role for Weight Estimation in Pediatric Emergencies? A Prospective, Cross-Sectional Study." Prehospital and Disaster Medicine 36, no. 3 (2021): 295–300. http://dx.doi.org/10.1017/s1049023x21000194.

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AbstractIntroduction:The aim of this study was to investigate the usability of the age value listed on the labels on children’s clothes in the age-based weight estimation method recommended by the Pediatric Advanced Life Support (PALS) guidelines.Material-Method:This prospective, cross-sectional study was organized in Antalya Training and Research Hospital Emergency Department. Children aged between 1-12 years were included in the study. The weight measurements of the children were obtained based on the age-related criteria on the labels of their clothes. The estimated values were compared wit
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Essayli, Jamal H., Jessica M. Murakami, Rebecca E. Wilson, and Janet D. Latner. "The Impact of Weight Labels on Body Image, Internalized Weight Stigma, Affect, Perceived Health, and Intended Weight Loss Behaviors in Normal-Weight and Overweight College Women." American Journal of Health Promotion 31, no. 6 (2016): 484–90. http://dx.doi.org/10.1177/0890117116661982.

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Purpose: To explore the psychological impact of weight labels. Design: A double-blind experiment that randomly informed participants that they were “normal weight” or “overweight.” Setting: Public university in Honolulu, Hawai‘i. Participants: Normal-weight and overweight female undergraduates (N = 113). Measures: The Body Image States Scale, Stunkard Rating Scale, Weight Bias Internalization Scale, Positive and Negative Affect Schedule, General Health question from the 12-item Short Form Health Survey, modified version of the Weight Loss Methods Scale, and a manipulation check. Analysis: A 2
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Dissertations / Theses on the topic "Weight labels"

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Chazelle, Thomas. "Influence sociale sur la représentation corporelle : Approche expérimentale de l'effet des médias et des labels de poids sur des jugements de corpulence." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALS063.

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La représentation corporelle est l’ensemble des fonctions cognitives permettant le suivi de l’état du corps. Elle est impliquée dans des situations diverses, comme la perception des dimensions physiques du corps, l’action, ou encore la génération d’attitudes à propos du corps. Pour réaliser ces fonctions, elle se base de manière flexible sur un ensemble d’informations sensorimotrices, ainsi que sur les croyances, attentes et émotions de l’individu. Parmi les sources d’informations disponibles à propos du corps, l’influence sociale peut être un facteur de risque, de maintien, et de sévérité des
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Araújo, Olegário da Cruz de. "In-store attractiveness of national brands and private labels in an emerging market." reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/20705.

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Submitted by Olegário Araújo (olegarioaraujo@gmail.com) on 2018-03-23T23:24:12Z No. of bitstreams: 1 FGV_EAESP_MCD_master_thesis_Olegario_Araujo_23_03_18.pdf: 1414422 bytes, checksum: 434b8d8205dce32e92e2acfbc9249916 (MD5)<br>Rejected by Debora Nunes Ferreira (debora.nunes@fgv.br), reason: Prezado, Referente a conferencia, o titulo não confere conforme a defesa da banca realizada no dia 27/02/2018. Peço a gentileza, a correção. Atenciosamente, Débora. on 2018-03-27T16:19:57Z (GMT)<br>Submitted by Olegário Araújo (olegarioaraujo@gmail.com) on 2018-03-28T03:07:34Z No. of bitstrea
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Simmons, Mark R. "Comparison of Weight Loss Outcome Measures in Adolescent Bariatric Surgery Patients using Growth Curve Modeling." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689830.

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Baier, Moritz C. [Verfasser]. "Living Polymerization to Ultra-High Molecular Weight and Dye-Labeled Polyethylene for Single-Molecule Fluorescence Microscopy and Reactor Blends / Moritz C. Baier." Konstanz : Bibliothek der Universität Konstanz, 2016. http://d-nb.info/1173616454/34.

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Sarinnapakorn, Kanoksri. "Induction of Classifiers from Multi-labeled Examples: an Information-retrieval Point of View." Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_dissertations/16.

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An important task of information retrieval is to induce classifiers capable of categorizing text documents. The fact that the same document can simultaneously belong to two or more categories is referred by the term multi-label classification (or categorization). Domains of this kind have been encountered in diverse fields even outside information retrieval. This dissertation discusses one challenging aspect of text categorization: the documents (i.e., training examples) are characterized by an extremely large number of features. As a result, many existing machine learning techniques are in su
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Mohammed, Kader Hamno. "Development of a label-free biosensor method for the identification of sticky compounds which disturb GPCR-assays." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-220645.

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It is widely known that early estimates about the binding properties of drug candidates are important in the drug discovery process. Surface plasmon resonance (SPR) biosensors have become a standard tool for characterizing interactions between a great variety of biomolecules and it offers a unique opportunity to study binding activity. The aim of this project was to develop a SPR based assay for pre-screening of low molecular weight (LMW) drug compounds, to enable filtering away disturbing compounds when interacting with drugs. The interaction between 47 LMW compounds and biological ligands we
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Mata, Jutta. "Healthy food choice." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2008. http://dx.doi.org/10.18452/15723.

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Die vorliegende Dissertation setzt sich damit auseinander, wie das Zusammenspiel von essensbezogener Umwelt und Kognition Ernährungsentscheidungen beeinflusst. Im ersten Manuskript, “When Diets Last: Lower Cognitive Complexity Increases Diet Adherence” wird die Bedeutung der kognitiven Komplexität von Ernährungsregeln für das Einhalten einer Diät untersucht. Können Diäten scheitern, weil sie aus kognitiver Perspektive zu komplex sind, z.B. weil sich Diäthaltende nicht alle wichtigen Informationen merken oder verarbeiten können? 1136 Diäthaltende nahmen an einer längsschnittlichen Onlinestudie
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McKinnon, Loretta Carmen. "The contribution of psychosocial factors to socioeconomic differences in food purchasing." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/60893/1/Loretta_McKinnon_Thesis.pdf.

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In developed countries the relationship between socioeconomic position (SEP) and health is unequivocal. Those who are socioeconomically disadvantaged are known to experience higher morbidity and mortality from a range of chronic diet-related conditions compared to those of higher SEP. Socioeconomic inequalities in diet are well established. Compared to their more advantaged counterparts, those of low SEP are consistently found to consume diets less consistent with dietary guidelines (i.e. higher in fat, salt and sugar and lower in fibre, fruit and vegetables). Although the reasons for dietary
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Villars, Clément. "Mesure objective de l’activité physique en conditions de vie libre et relations avec l’adiponectine." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10301/document.

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Une mesure précise de l’activité physique en conditions de vie libre est nécessaire pour une meilleure compréhension de ses relations avec la santé. Le premier objectif de ce travail thèse a été de valider l’Actiheart (qui combine la mesure de la fréquence cardiaque et du mouvement par accélérométrie) par rapport à l’eau doublement marquée (EDM). Nous montrons un bon niveau de concordance entre la dépense énergétique liée à l’activité physique (DEAP) estimée par l’Actiheart et l’EDM. Une individualisation de la relation entre la fréquence cardiaque et de la DEAP par un test d’effort est nécess
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Chen, Kuan-Tzu, and 陳冠慈. "The Impact of Reading Food Nutrition Labels for Weight Control on Working Adults’Body Mass Index." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/70805620037973064829.

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碩士<br>國立臺灣大學<br>健康政策與管理研究所<br>101<br>Overweight and obesity is the world&apos;&apos;s fifth largest cause of death risk, WHO also estimated that there are at least 2.8 million adults died of overweight or obese. According to the Department of Health, Executive Yuan, R.O.C (Taiwan), "2005-2008 National Nutrition and Health Survey" results of adult overweight and obesity rate of 44.1%, 50.8% were male. Women accounted for 36.9%. 2008 survey by the Ministry of Education student height and weight data show that one in four children are overweight or obese. Overweight and obese has become a health
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Books on the topic "Weight labels"

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Brazil. Serviço Nacional de Aprendizagem Industrial. Departamento Nacional. Coletânea de portarias de produtos pré-medidos. CNI SENAI, 2000.

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Day, Gloria. Weight of Labels: A Poetic Display of an Internal Shift. Lulu Press, Inc., 2018.

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What's So Scary about Diet Fat Exercise Labels and Calories Anyway?: 5 Quick Chapters on Practical Weight Loss. Independently Published, 2022.

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Radman-Livaja, Ivan. Prices and Costs in the Textile Industry in the Light of the Lead Tags from Siscia. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198790662.003.0013.

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This chapter considers a collection of nearly 1,200 inscribed lead tags from the ancient city of Siscia (south-west Pannonia). Most of the tags were reused several times, showing traces of older inscriptions. On one side, one can read personal names, while the other side of the tag usually carries an inscription mentioning the merchandise, usually in an abbreviated form, as well as a price and often an indication of quantity or weight. Most if not all the tags are linked to the wool trade and the textile industry, the prices indicating the value of the goods or the cost of a given service such
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Womens MAY CONTAIN WHISKEY VINTAGE WEATHERED IRISH LABEL - Simple Weight Tracker. Independently Published, 2021.

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Womens MAY CONTAIN WHISKEY VINTAGE WEATHERED IRISH LABEL - Simple Weight Tracker. Independently Published, 2021.

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Young, Deborah E. Swatch Reference Guide for Fashion Fabrics: 5th Edition. 5th ed. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501373206.

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This all-in-one text and swatch book offers current and high-quality fashion fabric samples alongside vital information like fabric name, fiber content, yarn construction, count, coloration, weight, uses, characteristics, and comparisons to other fabrics. The textbook with activities, 210 exclusive fabric samples, Quick Reference Guide tables, pre-printed mounting boards for quick access to all swatches, and an 8x metal pick glass are all contained in a sturdy three-ring binder. Step-by-step instructions and hands-on assignments help students to apply their knowledge about fabric identificatio
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Zoumbaris, Sharon K., and Marjolijn Bijlefeld. Food and You. Greenwood, 2001. http://dx.doi.org/10.5040/9798400652301.

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What is the BMI? How much should I be eating? Do I really need to exercise? Find the answers to these questions and other food, body, and health questions in this guide to understanding the fundamentals of good nutrition and its partner for optimum health--physical activity. Healthy eating can be a habit and good habits started earlier in life are easier to maintain. Good nutrition and physical activity complement each other in weight loss, cardiovascular health, and other benefits. This book provides the advice you need on how to get the most out of what you eat and how to develop healthier h
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Kirchman, David L. Degradation of organic matter. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0007.

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The aerobic oxidation of organic material by microbes is the focus of this chapter. Microbes account for about 50% of primary production in the biosphere, but they probably account for more than 50% of organic material oxidization and respiration (oxygen use). The traditional role of microbes is to degrade organic material and to release plant nutrients such as phosphate and ammonium as well as carbon dioxide. Microbes are responsible for more than half of soil respiration, while size fractionation experiments show that bacteria are also responsible for about half of respiration in aquatic hab
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Millan, John. Coins Weights & Measures, Ancient & Modern, of All Nations. Reduced Into English on Above 100 Tables, Collected & Methodiz'd from Newton, Folkes, ... of Specific Gravities, by Newton, Labelye. Gale Ecco, Print Editions, 2018.

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Book chapters on the topic "Weight labels"

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Adamopoulou, Evgenia, Theodoros Alexakis, Nikolaos Peppes, Emmanouil Daskalakis, and Konstantinos Demestichas. "Leveraging Continuous Learning for Fighting Misinformation." In Security Informatics and Law Enforcement. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62083-6_27.

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AbstractThe evolution brought by social media as well as the Internet itself has led to new paradigms in journalism and mass communication. New technologies revolutionize the way humans communicate and get informed about what is happening in the world; in parallel, however, individuals and organizations can exploit these new paradigms to pursue their own agenda. In this light, the spread of misinformation and disinformation can have a variety of negative effects on society, for instance, by creating dipoles in the political dialogue and threatening democracy, putting the health and security of
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Shield, Andrew DJ. "“White is a color, Middle Eastern is not a color”: Drop-Down Menus, Racial Identification, and the Weight of Labels." In Immigrants on Grindr. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30394-5_6.

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Xu, Jianhua. "Multi-Label Weighted k-Nearest Neighbor Classifier with Adaptive Weight Estimation." In Neural Information Processing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24958-7_10.

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Pirouz, Matin. "Balanced Weighted Label Propagation." In Lecture Notes in Networks and Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80126-7_1.

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Wang, Hongzhi, Jung Wook Suh, John Pluta, Murat Altinay, and Paul Yushkevich. "Optimal Weights for Multi-atlas Label Fusion." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22092-0_7.

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Yang, Lei, Zhan Shi, Dan Feng, et al. "MLND: A Weight-Adapting Method for Multi-label Classification Based on Neighbor Label Distribution." In Web and Big Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60259-8_47.

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Moradi Fard, Maziar, Paula Sorolla Bayod, Kiomars Motarjem, Mohammad Alian Nejadi, Saber Akhondi, and Camilo Thorne. "Learning Section Weights for Multi-label Document Classification." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70242-6_34.

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Verma, Gurudatta, and Tirath Prasad Sahu. "Exploring Label-Specific Feature Weights for Multi-label Feature Selection Using FWMABAC-MFS." In Proceedings of 4th International Conference on Frontiers in Computing and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2611-0_22.

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Sun, Chong, Weiyu Zhou, Zhongshan Song, Fan Yin, Lei Zhang, and Jianquan Bi. "Weighted Multi-label Learning with Rank Preservation." In Big Data. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1899-7_22.

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Liang, Zien, Shuping Zhao, Zhuojie Huang, and Jigang Wu. "Balanced Clustering with Discretely Weighted Pseudo-label." In Lecture Notes in Computer Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8487-5_8.

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Conference papers on the topic "Weight labels"

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Qiu, Xin Ying, and Jingshen Zhang. "Label Confidence Weighted Learning for Target-level Sentence Simplification." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.999.

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Li, Peilei, Hanqing Yu, and Yijin Zhang. "An Improved Label Propagation Algorithm for Undirected Weighted Networks." In 2024 12th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC). IEEE, 2024. http://dx.doi.org/10.1109/icwoc62055.2024.10684964.

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Yousefi, Mohadeseh, Yashar Naderahmadian, and Soosan Beheshti. "Label Consistent Generalized Adaptive Weighted Recursive Least Squares Dictionary Learning." In 2025 IEEE 6th International Conference on Image Processing, Applications and Systems (IPAS). IEEE, 2025. https://doi.org/10.1109/ipas63548.2025.10924517.

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Sheng, Yubin, Zuping Zhang, Panrui Tang, Bo Huang, and Yao Xiao. "EDAW: Enhanced Knowledge Distillation and Adaptive Pseudo Label Weights for Continual Named Entity Recognition." In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2024. https://doi.org/10.1109/smc54092.2024.10831235.

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Ong, Ee Ping, Ruchir Srivastava, and Wenbo Chen. "Fuzzy-Label Weighted Deep Learning Classification for CT Image Quality Evaluation." In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024. https://doi.org/10.1109/embc53108.2024.10782438.

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Zhao, Shanyu, and Yufei Gao. "Semi-supervised medical image classification method based on category pseudo-labels and weighted consistency loss." In International Conference on Advances in Computer Vision Research and Applications, edited by Zhonghong Ou and Hui Liu. SPIE, 2025. https://doi.org/10.1117/12.3068208.

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Jiawen, Sun, Fan Mao, Hua Dong, Cao Qian, Liao Mengke, and Chang Xiqiang. "Multi-Dimensional Carbon Label Evaluation of Electric Power Based on Improved Analytic Hierarchy Process and Entropy Weight Method." In 2024 IEEE 2nd International Conference on Sensors, Electronics and Computer Engineering (ICSECE). IEEE, 2024. http://dx.doi.org/10.1109/icsece61636.2024.10729459.

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Liu, Xianzhi, Shaoru Guo, Juncai Li, et al. "Improving Implicit Discourse Relation Recognition via Connective Prediction and Dependency-weighted Label Hierarchy." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650647.

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Feng, Lei, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, and Bo An. "Can Cross Entropy Loss Be Robust to Label Noise?" In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/305.

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Trained with the standard cross entropy loss, deep neural networks can achieve great performance on correctly labeled data. However, if the training data is corrupted with label noise, deep models tend to overfit the noisy labels, thereby achieving poor generation performance. To remedy this issue, several loss functions have been proposed and demonstrated to be robust to label noise. Although most of the robust loss functions stem from Categorical Cross Entropy (CCE) loss, they fail to embody the intrinsic relationships between CCE and other loss functions. In this paper, we propose a general
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Yang, Xu, Yanan Gu, Kun Wei, and Cheng Deng. "Exploring Safety Supervision for Continual Test-time Domain Adaptation." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/183.

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Continual test-time domain adaptation aims to adapt a source pre-trained model to a continually changing target domain without using any source data. Unfortunately, existing methods based on pseudo-label learning suffer from the changing target domain environment, and the quality of generated pseudo-labels is attenuated due to the domain shift, leading to instantaneous negative learning and long-term knowledge forgetting. To solve these problems, in this paper, we propose a simple yet effective framework for exploring safety supervision with three elaborate strategies: Label Safety, Sample Saf
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Reports on the topic "Weight labels"

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Cao, Shoufeng, Uwe Dulleck, Warwick Powell, Charles Turner-Morris, Valeri Natanelov, and Marcus Foth. BeefLedger blockchain-credentialed beef exports to China: Early consumer insights. Queensland University of Technology, 2020. http://dx.doi.org/10.5204/rep.eprints.200267.

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The BeefLedger Export Smart Contracts project is a collaborative research study between BeefLedger Ltd and QUT co-funded by the Food Agility CRC. This project exists to deliver economic value to those involved in the production, export and consumption of Australian beef to China through: (1) reduced information asymmetry; (2) streamlined compliance processes, and; (3) developing and accessing new data-driven value drivers, through the deployment of decentralised ledger technologies and associated governance systems. This report presents early insights from a survey deployed to Chinese consumer
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Puthanakit, Thanyawee, Kiat Ruxrungtham, Chitsanu Pancharoen, Jintanat Ananworanich, Torsak Burunupradah, and Arunee Klinklom. Pharmacokinetics of low-dose lopinavir/ritonavir tablet formulation in HIV-1 infected children. Chulalongkorn University, 2010. https://doi.org/10.58837/chula.res.2010.14.

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Methods: This was an open-label, cross-over study of 24 HIV-infected children with HIV RNA &lt; 50 copies/ml comparing PK parameter of standard dose LPV/r and low dose of LPV/r for 4 weeks. LPV dosage was prescribed by body weight band; 25~35 kg: LPV/r 300/75 vs. 200/50 mg, &gt; 35 kg 400/100 vs. 300/75 mg. Glood samples were drawn at 0 (pre-dose), 2,4,6,8, 10 and 12 hours. Plasma concentrations of LPV and RTV were measured by HPLC method. The acceptable C12h is &gt; 1 mg/L. The HIV RNA was measured at week 12 after switch back to standard dose for 4 weeks. Results: Twenty four children were i
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Alonso, Pablo, Basil Kavalsky, Jose Ignacio Sembler, et al. How is the IDB Serving Higher-Middle-Income Countries?: Borrowers' Perspective. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0010547.

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This evaluation assesses how well IDB's current mode of engagement meets the needs and expectations of countries that have relatively higher income levels and increasing access to diverse funding sources.For the purpose of this evaluation OVE selected 10 countries as case study countries using three objective indicators: (a) income level, (b) level of access to international financial markets, and (c) the weight of the country in IDB's lending portfolio. The countries, labeled higher middle income countries (HMICs) in this evaluation, are Argentina, Brazil, Chile, Colombia, Mexico, Panama, Per
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Lunn, Pete, Marek Bohacek, Jason Somerville, Áine Ní Choisdealbha, and Féidhlim McGowan. PRICE Lab: An Investigation of Consumers’ Capabilities with Complex Products. ESRI, 2016. https://doi.org/10.26504/bkmnext306.

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Executive Summary This report describes a series of experiments carried out by PRICE Lab, a research programme at the Economic and Social Research Institute (ESRI) jointly funded by the Central Bank of Ireland, the Commission for Energy Regulation, the Competition and Consumer Protection Commission and the Commission for Communications Regulation. The experiments were conducted with samples of Irish consumers aged 18-70 years and were designed to answer the following general research question: At what point do products become too complex for consumers to choose accurately between the good ones
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