Relevant bibliographies by topics / Criteria for classification

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

Academic literature on the topic 'Criteria for classification'

Author: Grafiati
Published: 3 August 2021
Last updated: 2 February 2022

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Journal articles on the topic "Criteria for classification"

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Katz, Jeffrey N., and Matthew H. Liang. "Classification Criteria Revisited." Arthritis & Rheumatism 34, no. 10 (October 10, 1991): 1228–30. http://dx.doi.org/10.1002/art.1780341004.

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Mahr, Alfred, and Mathilde de Menthon. "Classification and classification criteria for vasculitis." Current Opinion in Rheumatology 27, no. 1 (January 2015): 1–9. http://dx.doi.org/10.1097/bor.0000000000000134.

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Akgul, Ozgur. "Classification criteria for spondyloarthropathies." World Journal of Orthopedics 2, no. 12 (2011): 107. http://dx.doi.org/10.5312/wjo.v2.i12.07.

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Akgul, Ozgur, and Salih Ozgocmen. "Classification criteria for spondyloarthropathies." World Journal of Orthopedics 2, no. 12 (2011): 107. http://dx.doi.org/10.5312/wjo.v2.i12.107.

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Xavier Pi-Sunyer, F. "Obesity: criteria and classification." Proceedings of the Nutrition Society 59, no. 4 (November 2000): 505–9. http://dx.doi.org/10.1017/s0029665100000732.

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Obesity is defined as an excess accumulation of body fat. To measure fat in the body accurately is difficult, and no method is easily available for routine clinical use. Traditionally, overweight and obesity have been evaluated by anthropometric measurement of weight-for-height. More recently, BMI has been used. The normal range is 19–24·9 kg/m2, overweight is 25–29·9 kg/m2, and obesity ≥ 30 kg/m2. Not only is the total amount of fat an individual carries important, but also where the fat is distributed in the body. Fat in a central or upper body (android) distribution is most related to health risk. The most accurate way to measure central obesity is by magnetic resonance imaging or computer-assisted tomography scanning, but this approach is too expensive for routine use. Simple anthropometric measurements can be used, such as waist circumference. A waist circumference of greater than 1020 mm in men and 880 mm in women is a risk factor for insulin resistance, diabetes mellitus and cardiovascular disease. There is a clear genetic predisposition for obesity. The genetic contribution to obesity is between 25 and 40 % of the individual differences in BMI. For the overwhelming majority of individuals, the genetic predisposition will not be defined by one gene, but by multiple genes. Eventually, classification of obesity may be done by genetic means, but this approach will require more knowledge.
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Choromanska, Anna, and Ish Kumar Jain. "Extreme Multiclass Classification Criteria." Computation 7, no. 1 (March 12, 2019): 16. http://dx.doi.org/10.3390/computation7010016.

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We analyze the theoretical properties of the recently proposed objective function for efficient online construction and training of multiclass classification trees in the settings where the label space is very large. We show the important properties of this objective and provide a complete proof that maximizing it simultaneously encourages balanced trees and improves the purity of the class distributions at subsequent levels in the tree. We further explore its connection to the three well-known entropy-based decision tree criteria, i.e., Shannon entropy, Gini-entropy and its modified variant, for which efficient optimization strategies are largely unknown in the extreme multiclass setting. We show theoretically that this objective can be viewed as a surrogate function for all of these entropy criteria and that maximizing it indirectly optimizes them as well. We derive boosting guarantees and obtain a closed-form expression for the number of iterations needed to reduce the considered entropy criteria below an arbitrary threshold. The obtained theorem relies on a weak hypothesis assumption that directly depends on the considered objective function. Finally, we prove that optimizing the objective directly reduces the multi-class classification error of the decision tree.
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Stenholm, Björn. "Classification Criteria and Databases." Symposium - International Astronomical Union 155 (1993): 11–17. http://dx.doi.org/10.1017/s007418090016992x.

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In this review lecture the increase of fundamental data for planetary nebulae is shortly reflected. Special attention is given to the new general catalogue of galactic planetary nebulae, and selection criteria for the entries are summarised. Some information on planetary nebula data in the Magellanic Clouds is also given.
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Leekwijck, Werner Van, and Etienne E. Kerre. "Defuzzification: criteria and classification." Fuzzy Sets and Systems 108, no. 2 (December 1999): 159–78. http://dx.doi.org/10.1016/s0165-0114(97)00337-0.

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Dubreuil, Maureen, and Atul A. Deodhar. "Axial spondyloarthritis classification criteria." Current Opinion in Rheumatology 29, no. 4 (July 2017): 317–22. http://dx.doi.org/10.1097/bor.0000000000000402.

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Ulucan, Aydin, and Kazim Baris Atici. "A MULTIPLE CRITERIA SORTING METHODOLOGY WITH MULTIPLE CLASSIFI CATION CRITERIA AND AN APPLICATION TO COUNTRY RISK EVALUATION." Technological and Economic Development of Economy 19, no. 1 (April 2, 2013): 93–124. http://dx.doi.org/10.3846/20294913.2012.763070.

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In this paper, we propose an extension of the standard UTADIS methodology, an approach that originates from multicriteria decision aid (MCDA) for sorting problems, such that it can handle more than one classification criteria simultaneously which possibly involves different predefined classes for alternatives. Moreover, we test the classification ability of the standard UTADIS methodology using the out-of-classification criterion approach, a new variant of the studies comprising out-of-time and out-of-sample testing methodologies. Results obtained in out-of-classification criterion testing are then compared with the classification ability of the Multiple Classification Criteria UTADIS (MCC UTADIS). Finally, an application to country risk evaluation is performed. In this application, classifications of two credit rating agencies, Standard & Poor's and Moody's, are taken as two different classification criteria. Moreover, robustness of MCC UTADIS method is tested through using several data sets. Results indicate that MCC UTADIS involving more than one classification criteria performs very close to standard UTADIS with single classification criterion and performs better than the out-of-classification criterion tests. These results emphasize both the sensitivity of UTADIS models to the classification criteria and the importance of using a multiple classification criteria approach.
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Dissertations / Theses on the topic "Criteria for classification"

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Chen, Ye. "Multiple Criteria Decision Analysis: Classification Problems and Solutions." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2892.

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Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are
  1. Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice.
  2. Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively.
  3. Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.
Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example.

Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components.

A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.
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au, A. Bremner@murdoch edu, and Alexandra Bremner. "Localised splitting criteria for classification and regression trees." Murdoch University, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040606.142949.

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This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.
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Bremner, Alexandra. "Localised splitting criteria for classification and regression trees." Bremner, Alexandra (2004) Localised splitting criteria for classification and regression trees. PhD thesis, Murdoch University, 2004. http://researchrepository.murdoch.edu.au/440/.

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This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.
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Bremner, Alexandra P. "Localised splitting criteria for classification and regression trees /." Access via Murdoch University Digital Theses Project, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040606.142949.

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Zowid, Fauzi Mohammed. "Development and performance evaluation of multi-criteria inventory classification methods." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0331.

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Cette thèse traite du problème de la classification des produits dans les systèmes de gestion de stock. Plus précisément, elle vise à proposer de nouvelles méthodes de classification pour résoudre le problème de la classification multicritères des produits en stock (MCIC). Actuellement, la méthode ABC de classification des produits en stock est largement utilisée pour rationaliser les systèmes de gestion de stock composés de milliers de produits (SKU). Les méthodes de classification des stocks ABC à un seul critère sont souvent utilisées dans la pratique et, récemment, les MCIC ont également attiré l’attention des chercheurs et des industriels. En ce qui concerne les méthodes multicritères MCIC, un grand nombre de méthodes ont été développées dans la littérature, appartenant à trois approches principales, à savoir: (1) l'approche à base de Machine Learning (ML), (2) programmation mathématique (MP), et (3) multicritères d’aide à la décision (MCDM). Dans ML, de nombreuses méthodes de type ML supervisé ont été proposées ainsi qu'un certain nombre de méthodes hybrides. Cependant, à notre connaissance, très peu d'études de recherche ont envisagé le type ML non supervisé. Concernant les approches de type MP, un certain nombre de méthodes ont été développées en utilisant la programmation linéaire et non linéaire, telles que les méthodes Ng et ZF. Cependant, la plupart de ces méthodes doivent encore être améliorées pour en limiter les inconvénients. Sur MCDM, plusieurs méthodes ont été proposées pour fournir des classifications ABC, y compris la méthode TOPSIS (technique for order preference by similarity to ideal solution), qui est bien connue pour son attractivité et son utilisation, ainsi que certaines méthodes hybrides combinées avec TOPSIS. Il convient de noter que la plupart des études publiées se sont uniquement concentrées sur la proposition de méthodes de classification pour classer les SKUs dans un système de gestion de stock avec un intérêt limité par rapport à l'objectif initial et le plus important de notre travail, qui est la performance en termes de coûts et de niveau de service de la méthode proposée. De plus, la plupart des études existantes n'ont pas considéré des systèmes de gestion de stock avec un grand nombre de données réelles (un grand nombre de références) pour évaluer empiriquement leurs performances et recommander l'utilisation d’une méthode particulière pour des mises en pratique réelles. Ainsi, cette thèse propose d'abord d'évaluer la performance (coût et service) des méthodes MCIC existantes et de proposer diverses méthodes de classification alternatives qui réduisent les coûts et conduisent à des niveaux de service plus élevés. Plus précisément, trois méthodes de type ML non supervisées sont proposées et analysées : Agglomerative hierarchical clustering, Gaussian mixture model et K-means. En outre, d'autres méthodes hybrides dans les approches de type MP et MCDM sont également développées. Ces méthodes proposées représentent une hybridation des méthodes TOPSIS et Ng avec la méthode Triangular distribution, la méthode Simple additive weighting (SAW) et la méthode Multi-Objective Optimization Method by Ratio Analysis (MOORA). Pour mener nos recherches, la thèse analyse empiriquement les performances des méthodes considérées au moyen de deux jeux de données. Le premier jeu de données est un jeu de données benchmark qui provient d’une unité d’hôpital, souvent utilisé dans la littérature traitant des méthodes MCIC, composé de 47 SKUs. Le deuxième jeu de données se compose de 9086 SKUs et provient d'un détaillant aux Pays-Bas qui vend des produits de bricolage. Les performances des méthodes proposées sont comparées à celles des méthodes de classification MCIC existantes dans la littérature. Les résultats empiriques révèlent que les méthodes proposées donnent des performances prometteuses en conduisant à une plus grande efficacité combinée service-coût, notamment pour le second jeu de données très significatif
This thesis deals with the issue of inventory classification within supply chains. More specifically, it aims to provide new alternative classification methods to address the multi-criteria inventory classification (MCIC) problem. It is well known that the ABC inventory classification technique is widely used to streamline inventory systems composed of thousands of stock-keeping-units (SKUs). Single-criterion inventory classification (SCIC) methods are often used in practice and recently MCIC techniques have also attracted researchers and practitioners. With regard to the MCIC techniques, large number of studies have been developed that belong to three main approaches, namely: (1) the machine learning (ML), (2) the mathematical programming (MP), and (3) the multi-criteria decision making (MCDM). On the ML approach, many research methods belonging to the supervised ML type have been proposed as well as a number of hybrid methods. However, to the best of our knowledge, very few research studies have considered the unsupervised ML type. On the MP approach, a number of methods have been developed using linear and non-linear programming, such as the Ng and the ZF methods. Yet, most of these developed methods still can be granted more attentions for more improvements and shortcomings reduction. On the MCDM approach, several methods have been proposed to provide ABC classifications, including the TOPSIS (technique for order preference by similarity to ideal solution) method, which is well known for its wide attractiveness and utilization, as well as some hybrid TOPSIS methods.It is worth noting that most of the published studies have only focused on providing classification methods to rank the SKUs in an inventory system without any interest in the original and most important goal of this exercise, which is achieving a combined service-cost inventory performance, i.e. the maximization of service levels and the minimization of inventory costs. Moreover, most of the existing studies have not considered large and real-life datasets to recommend the run of MCIC technique for real life implementations. Thus, this thesis proposes first to evaluate the inventory performance (cost and service) of existing MCIC methods and to provide various alternative classification methods that lead to higher service and cost performance. More specifically, three unsupervised machine learning methods are proposed and analyzed: the Agglomerative hierarchical clustering, the Gaussian mixture model and K-means. In addition, other hybrid methods within the MP and MCDM approaches are also developed. These proposed methods represent a hybridization of the TOPSIS and Ng methods with the triangular distribution, the Simple additive weighting (SAW) and the Multi-objective optimization method by ratio analysis (MOORA).To conduct our research, the thesis empirically analyzes the performance of the proposed methods by means of two datasets containing more than nine thousand SKUs. The first dataset is a benchmark dataset originating from a Hospital Respiratory Theory Unit, often used in the literature dealing with the MCIC methods, composed of 47 SKUs. The second dataset consists of 9,086 SKUs and coming from a retailer in the Netherlands. The performances of the proposed methods are compared to that of existing MCIC classification methods in the literature. The empirical results reveal that the proposed methods can carry promising performances by leading to a higher combined service-cost efficiency
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TAKEDA, Kazuya, Norihide KITAOKA, and Makoto SAKAI. "Acoustic Feature Transformation Combining Average and Maximum Classification Error Minimization Criteria." Institute of Electronics, Information and Communication Engineers, 2010. http://hdl.handle.net/2237/14970.

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Xing, Lihong, and Yaoxuan Xu. "Product Classification in Supply Chain." Thesis, KTH, Industriell produktion, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-50398.

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Oriflame is a famous international direct sale cosmetics company with complicated supply chain operation but it lacks of a product classification system. It is vital to design a product classification method in order to support Oriflame global supply planning and improve the supply chain performance. This article is aim to investigate and design the multi-criteria of product classification, propose the classification model, suggest application areas of product classification results and introduces the product classification system into Oriflame ERP system. The research scope is defined within Oriflame supply chain from the order placed to suppliers by Global Supply department to the products received in Global Hubs.Investigation approaches in this article including information collection, multi-criteria integration, and quantified analysis. In addition, sample calculation and test to stakeholder departments have been done after the proposal of product classification system.The product classification applies a cross tabulate matrix to classify products into four classes (ABCD classification), it is believed that the results keep consistent at high level with both the calculation time horizons‟ increasing and the monthly forecast report update.Hence, Product Classification System is supposed to be applied in supply planning prioritization, inventory management and workforce balancing, etc.
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Crysandt, Holger. "Hierarchical classification of sound signals with class separation based on information theoretic criteria /." Aachen : Shaker, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017071704&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Liang, Wei. "An Introduction to Ambiguity and Instability: New Merit Criteria for Evaluating Classification Performance." W&M ScholarWorks, 2008. https://scholarworks.wm.edu/etd/1539626865.

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Alves, Frederico Silva de Sousa. "Canine parvovirus and sepsis : SIRS criteria evaluation and implementation of a PIRO classification." Master's thesis, Universidade de Lisboa, Faculdade de Medicina Veterinária, 2020. http://hdl.handle.net/10400.5/19691.

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Dissertação de Mestrado Integrado em Medicina Veterinária
Sepsis is a severe condition associated with high prevalence and mortality rates. Parvovirus enteritis is a predisposing factor for sepsis, as it promotes intestinal bacterial translocation and severe immunosuppression. This makes naturally parvovirus infected dogs a suitable study population as far as sepsis is concerned. The main objective of the present study was to evaluate the differences between two sets of SIRS (Systemic Inflammatory Response Syndrome) criteria in outcome prediction, parallelly the possibility of stratifying and classify septic animals using a proposed animal adapted PIRO (Predisposition, Infection, Response, Organ dysfunction) scoring system was also assessed. The 72 animals enrolled in this study were subjected to a score for each of the PIRO elements (except for the Infection, as all were considered to have the same infection score) and to two sets of SIRS criteria, assessing their correlation with the outcome. The data was retrieved from the clinical records of the Infectious Disease Isolation Unit (IDIU) of the Veterinary Teaching Hospital (VTH) of the Faculty of Veterinary Medicine (FMV) of the University of Lisbon (ULisboa). Concerning the SIRS criteria, it was found that the proposed alterations were significantly associated with the outcome (OR = 4.09, p < 0,05), contrasting with the original SIRS criteria (p=0.352) that did not correlate with the outcome. No significant statistical association was found between Predisposition (p=1), Response (p=0.1135), Organ dysfunction (p=0.1135) or total PIRO score (p=0.093) and outcome. The results obtained reveal the need for consensual and more specific criteria to assess SIRS and sepsis. The results suggest that augmenting the criteria specificity may improve their prognostic value, thus making them more useful in clinical management and treatment decision. This work represents a contribution for the development of an approved set of criteria, to could contribute not only to the classification of septic dogs but also to the improvement of sepsis diagnosis. Further studies are still needed to conclude about the best criteria to be used, but this study can serve as base from which further studies can adapt and improve. Additional more specific criteria, mainly inflammatory and organ dysfunction biomarkers, should be added to the proposed PIRO scoring system in order to improve the its´ prognostic value and clinical utility. Further studies should focus on improving classification systems and finding new biomarkers that would allow a timely intervention in sepsis affected animals and improve sepsis survival rate.
RESUMO - Parvovirose Canina e Sépsis: Avaliação dos critérios de SIRS e Implementação da classificação PIRO - A sépsis esta associada a uma elevada prevalência e taxa de mortalidade. A Parvovirose canina predispõe para o aparecimento de sépsis secundaria à translocação bacteriana intestinal e imunossupressão. Este facto faz dos cães naturalmente infetados com parvovírus uma boa população para o estudo de sépsis. O principal objetivo deste estudo foi avaliar as diferenças entre dois conjuntos de critérios de SRIS (Síndrome de Resposta Inflamatória Sistémica) sobre a sua capacidade de prognóstico, assim como avaliar a possibilidade de implementação de um sistema de estratificação de animais sépticos com base no modelo PIRO (Predisposition, Infection, Response, Organ dysfunction). Os 72 animais da amostra foram submetidos a dois conjuntos de critérios SIRS e classificados para cada um dos elementos constituintes do PIRO (com exceção da infeção, sendo que todos os animais foram considerados como tendo a mesma classificação para a Infeção), avaliando a sua relação com o desfecho. Os dados foram recolhidos a partir dos registos clínicos da Unidade de Isolamento de Doenças Infeciosas (UIDI) do HEV-FMV-UL. Em relação aos critérios de classificação SRIS, os resultados revelaram que a alteração proposta aos critérios originais resulta numa associação estatisticamente significativa com o desfecho (OR = 4.09, p < 0,05), contrastando com os resultados observados quando aplicados os critérios originais (p=0.352) que não se correlacionam significativamente com o desfecho. Não foi encontrada nenhuma associação estatisticamente significativa entre a Predisposição (p=1), Resposta (p=0.1135), Disfunção Orgânica (p=0.1135) ou PIRO total (p=0.093) e o desfecho clínico. Os resultados obtidos revelam a necessidade de critérios mais específicos para a avaliar SRIS e sépsis. Os resultados sugerem que o aumento da especificidade pode melhorar o seu valor prognóstico. Este trabalho representa uma contribuição para o desenvolvimento de um conjunto de critérios consensual e aprovado para a classificação de animais sépticos, servindo de base para estudos futuros. Mais critérios com uma maior especificidade, como marcadores bioquímicos inflamatórios e de disfunção orgânica, devem ser adicionados ao sistema PIRO proposto. Estudos futuros devem concentrar-se em melhorar os sistemas de classificação existentes e descobrir novos biomarcadores que permitam uma intervenção atempada em animais afetados por sépsis, melhorando a taxa de sobrevivência.
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Books on the topic "Criteria for classification"

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Woo, Carolyn Y. Y. Entrepreneurial typology and classification criteria. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1989.

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Constantin, Zopounidis, ed. Multicriteria decision aid classification methods. Dordrecht: Kluwer Academic Publishers, 2002.

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Noble, Elizabeth B. Classification Pamlico Sound nursery areas: Recommendations for critical habitat criteria. Morehead City, NC (P.O. Box 769, Morehead City 28557): North Carolina Dept. of Environment, Health, and Natural Resources, Division of Marine Fisheries, 1991.

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Doumpos, Michael. Multicriteria decision aid classification methods. Dordrecht: Kluwer Academic Publishers, 2002.

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Webb, T. H. Criteria for defining the soil family and soil sibling: The fourth and fifth categories of the New Zealand Soil Classification. 2nd ed. Lincoln, N.Z: Manaaki Whenua Press, Landcare Research, 2011.

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Lin, Chuan-Ju. Effects of item-selection criteria on classification testing with the sequential probability ratio test. Iowa City, Iowa: ACT, Inc., 2000.

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Lin, Chuan-Ju. Effects of item-selection criteria on classification testing with the sequential probability ratio test. Iowa City, Iowa: ACT, Inc., 2000.

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Lin, Chuan-Ju. Effects of item-selection criteria on classification testing with the sequential probability ratio test. Iowa City, Iowa: ACT, Inc., 2000.

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Smith, Gregory M., Jonathan Chun, Anatoly Nemzer, and Bob Richard. Test Procedures and Classification Criteria for Release of Toxic Gases from Water-Reactive Materials. Washington, D.C.: Transportation Research Board, 2014. http://dx.doi.org/10.17226/22276.

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Petti, Cathy A. Interpretive criteria for identification of bacteria and fungi by DNA target sequencing: Approved guideline. Wayne, PA: Clinical and Laboratory Standards Institute, 2008.

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Book chapters on the topic "Criteria for classification"

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Baldini, Chiara, Rosaria Talarico, and Stefano Bombardieri. "Classification Criteria." In Sjögren’s Syndrome, 417–28. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-947-5_29.

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Cantini, Fabrizio, and Carlotta Nannini. "Classification Criteria." In Large and Medium Size Vessel and Single Organ Vasculitis, 3–8. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67175-4_1.

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Gerosa, Maria, and Francesca Rovelli. "Non-classification Criteria." In Antiphospholipid Antibody Syndrome, 61–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11044-8_6.

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Meyn, Sean P., and Richard L. Tweedie. "Generalized Classification Criteria." In Markov Chains and Stochastic Stability, 465–91. London: Springer London, 1993. http://dx.doi.org/10.1007/978-1-4471-3267-7_19.

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Yazici, Hasan, and Yusuf Yazici. "Disease Classification/Diagnosis Criteria." In Understanding Evidence-Based Rheumatology, 65–78. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08374-2_3.

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Bertolaccini, Maria Laura, Oier Ateka-Barrutia, and Munther A. Khamashta. "Classification Criteria for APS." In Antiphospholipid Syndrome Handbook, 15–16. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84628-735-0_4.

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Stenholm, Björn. "Classification Criteria and Databases." In Planetary Nebulae, 11–18. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2088-3_2.

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Lee, Crystal Man Ying, and Stephen Colagiuri. "Diagnostic Criteria and Classification." In Endocrinology, 23–39. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-45015-5_3.

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Lee, Crystal Man Ying, and Stephen Colagiuri. "Diagnostic Criteria and Classification." In Endocrinology, 1–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-27317-4_3-1.

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Linkov, Igor, Emily Moberg, Benjamin D. Trump, Boris Yatsalo, and Jeffrey M. Keisler. "Risk-Based Classification of Nanomaterials 1." In Multi-Criteria Decision Analysis, 123–31. Second edition. | Boca Raton : CRC Press, 2020. |: CRC Press, 2020. http://dx.doi.org/10.1201/9780429326448-10.

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Conference papers on the topic "Criteria for classification"

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Garg, Arti, and Coryn A. L. Bailer-Jones. "Determination of Microlensing Selection Criteria for the SuperMACHO Survey." In CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: “Classification and Discovery in Large Astronomical Surveys”. AIP, 2008. http://dx.doi.org/10.1063/1.3059059.

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Thompson, Roney L., and Paulo R. Souza Mendes. "Considerations on Flow Classification Criteria." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60109.

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Flow classification is still an open problem in continuum mechanics. Among the presently available flow criteria, there are two that have an outstanding importance, namely, Tanner and Huilgol (1975) and Astrarita (1979). While the former is restricted to MWCSH, the latter was shown by Huilgol (1980) to fail for certain 3-D kinematics. In the present work we suggest a generalization of Tanner-Huilgol’s classification to encompass motions other then MWCSH. We also establish both the range of applicability of Astarita’s criterion and the relationship between the two criteria. The application to the Doubly Superposed Viscometric Flow of these two criteria and also of the one recently proposed by Thompson and Souza Mendes (2004), shows that it is advantageous to adopt the persistence-of-straining parameter proposed by Thompson and Souza Mendes (2004).
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Singh, Rita. "Audio Classification with Thermodynamic Criteria." In 2014 IEEE International Conference on Cloud Engineering (IC2E). IEEE, 2014. http://dx.doi.org/10.1109/ic2e.2014.23.

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Skupas, Bronius, Valentina Dagiene, and Miguel Revilla. "Developing classification criteria for programming tasks." In the 14th annual ACM SIGCSE conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1562877.1563015.

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Dobra, Andreea. "General classification of robots. Size criteria." In 2014 23rd International Conference on Robotics in Alpe-Adria-Danube Region (RAAD). IEEE, 2014. http://dx.doi.org/10.1109/raad.2014.7002249.

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Szarucki, Marek. "Developing classification criteria for organizational problems." In The 6th International Scientific Conference "Business and Management 2010". Vilnius, Lithuania: Vilnius Gediminas Technical University Publishing House Technika, 2010. http://dx.doi.org/10.3846/bm.2010.148.

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Kriguer, Henrique, and Valerio Salomon. "MULTI-CRITERIA CLASSIFICATION OF SPARE PARTS." In International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 2016. http://dx.doi.org/10.13033/isahp.y2016.089.

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Kitamura, Yoshinobu, Sho Segawa, Munehiko Sasajima, and Riichiro Mizoguchi. "An Ontology of Classification Criteria for Functional Taxonomies." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48125.

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In order to facilitate sharing of functional models, some functional taxonomies each of which provides a set of verbs for representing generic functions (called functional terms here) have been developed. Their examples include some sets of generally valid functions in the book written by Pahl and Beitz, Functional Basis (FB) developed by Hirtz et al. and FOCUS/Tx developed by the authors of this paper. The issue addressed in this paper is the implicitness of the criteria of classification of functional terms in those taxonomies and thus unclearness of their definitions. This paper proposes an ontology of logical criteria for classification of functional terms (called FOCUS/View). Using the classes defined in FOCUS/View, the classification criteria of a functional taxonomy can be explicitly represented. These classes have been conceptualized based on deep investigation on FB and FOCUS/Tx. The benefits of the proposed FOCUS/View ontology include: (1) users of a taxonomy can easily understand differences of similar terms and select an appropriate term out of them, (2) a developer of a taxonomy can check its logical classification structure and then improve its logical clearness, and (3) we can compare different taxonomies and establish more reliable mappings between their terms for interoperability of functional models. In this paper, as a demonstration of the benefit (1), the classification criteria of FB, FOCUS/Tx, Krumhauer’s and Roth’s generally valid functions are explicitly presented using FOCUS/View. As a demonstration of the benefit (2), some logically problematic classification structures of FB and the Krumhauer’s functions are discussed and modified for the logical clearness. For the benefit (3), this paper demonstrates the mappings between FB and FOCUS/Tx and a semantic interoperable document search system based on these mappings.
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Petri, Michelle, Daniel Goldman, and Laurence S. Magder. "CS-29 Creation of a weighted SLICC SLE classification criteria and comparison with other SLE classification criteria." In LUPUS 21ST CENTURY 2018 CONFERENCE, Abstracts of the Fourth Biannual Scientific Meeting of the North and South American and Caribbean Lupus Community, Armonk, New York, USA, September 13 – 15, 2018. Lupus Foundation of America, 2018. http://dx.doi.org/10.1136/lupus-2018-lsm.64.

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Iyer, Naresh, and Piero P. Bonissone. "Automated Risk Classification and Outlier Detection." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369101.

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Reports on the topic "Criteria for classification"

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Pypenko, Iryna. Classification of the Criteria for Cryptocurrencies. KRPOCH, 2020. http://dx.doi.org/10.26697/krpoch.pypenko.i.report.2020.

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Larsen, Poul Bo, and Daniel Vest Christophersen. The applicability of the GHS classification criteria to nanomaterials. Nordic Council of Ministers, May 2019. http://dx.doi.org/10.6027/na2019-907.

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Wik, Ola, Pascal Suer, Anke Oberender, Ole Hjelmar, Jutta Laine-Ylijoki, and Margareta Wahlström. Consequences of Revised Criteria for Hazardous Waste Classification in the Nordic countries – the criterion for leaching (H15). Nordic Council of Ministers, December 2012. http://dx.doi.org/10.6027/tn2012-547.

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Shulman, Jay, Timothy R. Williams, James E. Tupa, James A. Lalumandier, and Norman W. Richter. A Comparison of Dental Fitness Classification Using Different Class 3 Criteria: A Report of Consultation. Fort Belvoir, VA: Defense Technical Information Center, January 1992. http://dx.doi.org/10.21236/ada255417.

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Moe, Wayne L., and Amir Afzali. Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Safety Classification and Performance Criteria for Structures, Systems, and Components. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1560535.

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Moe, Wayne, and Amir Afzali. Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Safety Classification and Performance Criteria for Structures, Systems, and Components. Office of Scientific and Technical Information (OSTI), March 2020. http://dx.doi.org/10.2172/1700535.

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Furey, John, Austin Davis, and Jennifer Seiter-Moser. Natural language indexing for pedoinformatics. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41960.

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The multiple schema for the classification of soils rely on differing criteria but the major soil science systems, including the United States Department of Agriculture (USDA) and the international harmonized World Reference Base for Soil Resources soil classification systems, are primarily based on inferred pedogenesis. Largely these classifications are compiled from individual observations of soil characteristics within soil profiles, and the vast majority of this pedologic information is contained in nonquantitative text descriptions. We present initial text mining analyses of parsed text in the digitally available USDA soil taxonomy documentation and the Soil Survey Geographic database. Previous research has shown that latent information structure can be extracted from scientific literature using Natural Language Processing techniques, and we show that this latent information can be used to expedite query performance by using syntactic elements and part-of-speech tags as indices. Technical vocabulary often poses a text mining challenge due to the rarity of its diction in the broader context. We introduce an extension to the common English vocabulary that allows for nearly-complete indexing of USDA Soil Series Descriptions.
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Knapp, Deirdre J., and John P. Campbell. Building a Joint-Service Classification Research Roadmap: Criterion- Related Issues. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada269735.

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Manual for the classification of intervention best-practices with rural NEETs. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, December 2020. http://dx.doi.org/10.15847/cisrnyn.mn1.2020.12.

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targeting rural NEETs. In my opinion, this is the most outstanding contribution of this manual, and also an original one, considering that to date no other efforts have been made with the intention of developing a grid of how to describe interventions dealing with rural NEETs. This manual offers, therefore, valuable contributions for upcoming research efforts within and beyond RNYN, including: (a) a complete methodological framework for future case stu-dies; (b) practical tools to conduct field research than can be combined with many different methodological approaches (qualitative, mixed-methods, etc.); and, (c) strategic criteria for conducting research in complex settings such as community-based programs. In addition, this manual sets the necessary conditions to present evidence-based conclusions about programs targeting rural NEETs, further aiding policy-makers to opt for solutions that clearly produce better results. This manual would not have been possible without the efforts and best knowledge from its editorial team. Therefore, as the Chair of RNYN, but also in a more personal note, I would like to thank Claudia Petrescu, Emre Erdogan and Paul Flynn for the impeccable and rigorous way in which they conducted all the process. I would also like to thank the Working Group 2 mem-bers traversing many countries who contributed to this document.
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