Process data from wastewater treatment plants are often corrupted by errors. These data provide a basis for operating the plant, therefore effort should be made to improve the data quality. Currently, Stockholm Vatten och Avfall uses a method where they quantitatively verify water flow measurement data by comparing it to water level measurements. In this thesis, an alternative approach based on mass balancing to detect errors was evaluated. The aim was to find, implement and evaluate a mass balance based method to detect and locate errors. The objective was to use this method to corroborate the flow verification method used by Stockholm Vatten och Avfall, and to improve flow data from Bromma Wastewater treatment plant. The chosen method consisted of two major steps, gross error detection and data reconciliation. A case study was performed where the method was tested on both simulated data with known added errors, real process data and finally a case where the suggested method was compared to the flow verification method. The results showed that this method was efficient in detecting a gross error when only one flow measurement was erroneous and that the estimation of the error magnitude was good. However, the suggested method was not useful for corroboration of the flow verification method. With the flow verification method, the flow in one filter basin at the time was examined. The suggested method required the combined flow in all 24 filter basins, which made it difficult to compare the two methods. The method has potential to be valuable for error detection in wastewater treatment plants, and to be used as a live tool to detect gross errors.

Magister Scientiae - MSc / The intention is to draw more specific connections between certain deconvolution methods and also to demonstrate the application of the statistical theory of estimation in the presence of measurement error. A parametric methodology for deconvolution when the underlying distribution is of the Pareto form is developed. Maximum likelihood estimation (MLE) of the parameters of the convolved distributions is considered. Standard errors of the estimated parameters are calculated from the inverse Fisher’s information matrix and a jackknife method. Probability-probability (P-P) plots and Kolmogorov-Smirnov (K-S) goodnessof- fit tests are used to evaluate the fit of the posited distribution. A bootstrapping method is used to calculate the critical values of the K-S test statistic, which are not available. / South Africa

>Magister Scientiae - MSc / Estimation of population distributions, from samples that are contaminated by measurement errors, is a common problem. This study considers the problem of estimating the population distribution of independent random variables Xi, from error-contaminated samples ~i (.j = 1, ... , n) such that Yi = Xi + f·.i, where E is the measurement error, which is assumed independent of X. The measurement error ( is also assumed to be normally distributed. Since the observed distribution function is a convolution of the error distribution with the true underlying distribution, estimation of the latter is often referred to as a deconvolution problem. A thorough study of the relevant deconvolution literature in statistics is reported. We also deal with the specific case when X is assumed to follow a truncated Pareto form. If observations are subject to Gaussian errors, then the observed Y is distributed as the convolution of the finite-support Pareto and Gaussian error distributions. The convolved probability density function (PDF) and cumulative distribution function (CDF) of the finite-support Pareto and Gaussian distributions are derived. The intention is to draw more specific connections bet.ween certain deconvolution methods and also to demonstrate the application of the statistical theory of estimation in the presence of measurement error. A parametric methodology for deconvolution when the underlying distribution is of the Pareto form is developed. Maximum likelihood estimation (MLE) of the parameters of the convolved distributions is considered. Standard errors of the estimated parameters are calculated from the inverse Fisher's information matrix and a jackknife method. Probability-probability (P-P) plots and Kolmogorov-Smirnov (K-S) goodnessof- fit tests are used to evaluate the fit of the posited distribution. A bootstrapping method is used to calculate the critical values of the K-S test statistic, which are not available. Simulated data are used to validate the methodology. A real-life application of the methodology is illustrated by fitting convolved distributions to astronomical data

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The current study assessed an error reflection intervention on Algebra I students’ conceptual and procedural knowledge and sense of belonging to mathematics. Also of interest was whether perceptions of the functionality of errors mediated the effect of condition on learning and sense of belonging to mathematics. Middle school students (N = 207) were randomly assigned within classroom to one of four conditions: 1) a Problem-Solving Control group, 2) a Correct Examples Control group, 3) a Correct Examples Error Reflection condition that promoted reflection on hypothetical errors through self-explanation prompts, or 4) an Incorrect Examples Error Reflection condition that promoted reflection on displayed errors within the example through self-explanation prompts. Conceptual and procedural knowledge, sense of belonging to mathematics and perceived functionality of errors were measured pre- and post-intervention. After controlling for unanticipated clustering effects, results suggest that reflecting on and explaining errors within a worked examples intervention is just as effective at promoting learning as traditional problem solving alone or working with traditional correct worked examples and written self-explanation prompts. Students’ sense of belonging to mathematics or perceived functionality of errors for learning were high at the start of the study and remained so throughout the intervention. Perceptions of the functionality of errors were unrelated to learning and sense of belonging to mathematics. The limited size of the minority population in the sample did not allow for exploration of differential effects of condition for underrepresented minority (URM) students. However, these students reported lower feelings of belonging to mathematics than non-URM students. Implications for theory and practice are discussed. / Educational Psychology

No / This study aimed to evaluate the use of a shared electronic primary health care record (EHR) to assist with medicines reconciliation in the hospital from admission to discharge. Methods: This is a prospective cross-sectional, comparison evaluation for 2 phases, in a short-term elderly admissions ward in the United Kingdom. In phase 1, full reconciliation of the medication history was attempted, using conventional methods, before accessing the EHR, and then the EHR was used to verify the reconciliation. In phase 2, the EHR was the initial method of retrieving the medication history-validated by conventional methods. Results: Where reconciliation was led by conventional methods, and before any access to the EHR was attempted, 28 (28%) of hospital prescriptions were found to contain errors. Of 99 prescriptions subsequently checked using the EHR, only 50 (50%) matched the EHR. Of the remainder, 25% of prescriptions contained errors when verified by the EHR. However, 26% of patients had an incorrect list of current medications on the EHR. Using the EHR as the primary method of reconciliation, 33 (32%) of 102 prescriptions matched the EHR. Of those that did not match, 39 (38%) of prescriptions were found to contain errors. Furthermore, 37 (36%) of patients had an incorrect list of current medications on the EHR. The most common error type on the discharge prescription was drug omission; and on the EHR, wrong drug. Common potentially serious errors were related to unidentified allergies and adverse drug reactions. Conclusions: The EHR can reduce medication errors. However, the EHR should be seen as one of a range of information sources for reconciliation; the primary source being the patient or their carer. Both primary care and hospital clinicians should have read-and-write access to the EHR to reduce errors at care transitions. We recommend further evaluation studies.

Este trabalho foi proposto com o objetivo de implementar uma ferramenta computacional para estimar os estados (tensões complexas nodais) de um sistema elétrico de potência e aplicar métodos alternativos para o processamento de erros topológicos, erros de parâmetros e/ou de erros grosseiros em medidas, baseados na interpretação geométrica dos erros e no conceito de inovação das medidas. O método utilizado para a resolução do problema de estimação de estado é o de mínimos quadrados ponderados. Através da interpretação geométrica, demonstrou-se matematicamente que o erro da medida é constituído de uma componente detectável e uma não-detectável, entretanto, as metodologias até então utilizadas para o processamento de erros consideram apenas a componente detectável do erro e, como consequência, podem falhar. Na tentativa de contornar essa limitação e baseado nos conceitos citados previamente, foi estudada e implementada uma metodologia alternativa para processar tais erros baseada na análise das componentes dos erros das medidas. Em primeiro lugar, é testado se o conjunto de medidas possui erros utilizando, para isso, o valor do erro de medida composto normalizado. Em seguida, diferencia-se se um ou outro erro ocorreu, ou mesmo se mais de um tipo de erro ocorreu. A correção a ser feita no parâmetro de linha ou na medida com erro grosseiro será o erro normalizado composto correspondente. A abordagem proposta neste trabalho requer somente um conjunto de medidas, e no mesmo instante. Para validação do programa, foram feitas diversas simulações nos sistemas de 14 e 57 barras do IEEE. / This work was proposed with the objective to implement a computational tool to estimate the states (nodal complex voltages) of a power system and apply alternative methods for the processing of topological errors, parameter errors and/or gross errors in measurements, based on the geometric interpretation of the errors and the innovation concept of measurements. The method used to solve the state estimation problem is the weighted least squares. Through geometric interpretation, it has been demonstrated mathematically that the measurement error is composed by a detectable component and a non-detectable, however, the methodologies heretofore used for error processing consider only the detectable component of the error and, consequently, can fail. In an attempt to overcome this limitation and based on the concepts mentioned previously, an alternative approach to process such errors was studied and implemented based on the analysis of the components of the measurements errors. Firstly, it is tested if the set of measurements has errors using, for that, the value of the composed measurement error in its normalized way. Next, it diers if either an error has occurred, or if more than one type of error occurred. The correction to be made in the line parameter or the measurement with gross error is the correspondent composed normalized error. The proposed approach in this paper requires only a set of measures, and at the same instant. To validate the software, several simulations were performed in the IEEE 14-bus and 57-bus systems.

Introdução: A segurança do paciente é tema de grande importância pois muitos pacientes hospitalizados são vítimas de eventos adversos (EAs). Evento adverso é um incidente que resulta em dano desnecessário ao paciente, de caráter não intencional, e que está associado à assistência prestada, e não com a evolução natural da doença do indivíduo. As unidades de terapia intensiva (UTIs) são ambientes propícios à ocorrência de EAs, porém não há dados abrangentes sobre EAs em UTIs no Brasil. Além disso é preciso verificar se a ocorrência de EAs é fator de risco para morte em UTI, e quais são os fatores de risco para sua ocorrência. Objetivos: Identificar e caracterizar EAs em UTIs do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HC-FMUSP), avaliar se há relação entre ocorrência de EAs e morte em UTIs, e identificar quais os fatores de risco para a ocorrência de EAs nesses locais. Métodos: Estudo observacional do tipo coorte que analisou admissões consecutivas em UTIs no HC-FMUSP entre Junho e Agosto de 2009. Os casos foram acompanhados até a saída da UTI, seja alta ou óbito. Foram coletados dados sobre aspectos clínicos, escores de gravidade (APACHE II, SAPS II, SOFA), carga de trabalho de enfermagem (NAS) e intervenções realizadas. EAs foram identificados através da revisão de prontuários e observação dos profissionais médicos e de enfermagem, sendo classificados quanto ao tipo e grau de dano conforme classificação da Organização Mundial da Saúde. Foi feita análise multivariada com regressão logística para analisar se EAs são fatores de risco independentes para morte em UTI. Foi feita uma segunda análise multivariada com regressão logística para verificar quais são os fatores de risco para ocorrência de EAs com alto grau de dano (AGD). Resultados: Ocorreram 1126 EAs em 81,7% das 202 admissões estudadas. Os EAs mais frequentes foram os das categorias processo clínico/procedimento (54% dos EAs), medicação (25,8%), nutrição (13,9%), e infecção (5,5%). Quanto ao dano, 74,4% foram EAs leves, 19,4% moderados, 4,1% graves e 2,1% associados a óbito. A ocorrência de 4 a 6 EAs na internação mostrou-se um fator de risco para óbito em UTI (OR:18,517; IC95%:1,043-328,808; P=0,047), assim como a ocorrência de >= 7 EAs (OR:32,084; IC95%:1,849-556,684; P=0,017). Quanto aos tipos, a ocorrência de EA do tipo processo clínico/procedimento mostrou-se fator de risco para óbito em UTI (OR:9,311; IC95%:1,283-67,556; P=0,027), bem como a ocorrência de EA com AGD (OR:38,964; IC95%:5,620-270,151; P < 0,001). Foram identificados os seguintes fatores de risco para ocorrência de EAs com AGD: NAS médio de 70,1% a 82,3% (OR:6,301; IC95%:1,164- 34,117; P=0,033), NAS médio >= 82,4% (OR:9,068; IC95%:1,729-47,541; P=0,009), SOFA médio entre 4,5 a 6,7 (OR:6,934; IC95%:1,239-38,819; P=0,028), e um SOFA médio >= 6,8 (OR:10,293; IC95%:1,752-60,474; P=0,010). Conclusões: EAs acometeram muitas admissões das UTIs estudadas, sendo que mais da metade destes eventos foi do tipo processo clínico/procedimento. Cerca de 6% dos EAs foi considerado grave ou associado ao óbito do paciente. A ocorrência de EAs foi um fator de risco independente para óbito, principalmente EAs do tipo processo clínico/procedimento e EAs com AGD. Os fatores de risco para ocorrência de EAs com AGD foram a carga de trabalho de enfermagem e a gravidade do paciente / Introduction: Patient safety is a matter of great importance because many hospitalized patients are victims of adverse events (AEs). Adverse event is an unintentional incident that results in unnecessary patient harm, that is associated with the care provided, and not with the natural evolution of the individual\'s disease. The intensive care units (ICUs) are prone environments to the occurrence of AEs, but there is no comprehensive data on AEs in ICUs in Brazil. Is not known for sure if AEs are risk factors for death in ICUs, and what are the most important risk factors for AEs occurrence in ICUs. Objectives: To identify and characterize AEs in ICUs of the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), to evaluate relationship of AEs with death in ICUs, and to identify risk factors for the occurrence of AEs. Methods: This is an observational cohort study of consecutive admissions to ICUs of HC-FMUSP analyzed between June and August 2009. The cases were followed until discharge from the ICU, dead or alive. Data on clinical features, severity scores (APACHE II, SAPS II, SOFA), nursing workload (NAS) and interventions were collected. AEs were identified by reviewing medical records and observation of medical and nursing professionals, and they were classified according to type and degree of harm as classified by the World Health Organization. Multivariate analyzes were performed with logistic regression to examine whether EAs are independent risk factors for death in the ICU. A second multivariate logistic regression analysis was performed to verify what are the risk factors for the occurrence of AEs with high damage (HD). Results: There were 1126 AEs in 81.7% of 202 admissions studied. 1126 AEs occurred in 81.7% of 202 admissions studied. The most common AEs were the categories of clinical process / procedure (54% of AEs), medication (25.8%), nutrition (13.9%), and healthcare-associated infection (5.5%). The occurrence of 4-6 AEs at admission was a risk factor for death in the ICU (OR:18.517; 95%CI:1,043-328,808; P=0.047 ), as well as the occurrence of >= 7 AEs (OR:32.084; 95%CI:1,849-556,684; P=0.017). Regarding the types, the occurrence of AE of clinical process / procedure type was as risk factor for death in the ICU (OR:9.311; 95%CI:1,283-67,556; P=0.027) as well as the occurrence of AE with HD (OR:38.964; 95%CI:5,620-270,151; P < 0.001) . The following risk factors were identified for the occurrence of AEs with HD: mean NAS of 70.1% to 82.3% (OR:6.301; 95%CI:1,164-34,117; P=0.033), mean NAS >= 82.4% (OR:9.068; 95%CI:1,729-47,541; P=0.009), mean SOFA between 4.5 and 6.7 (OR:6.934; 95%CI:1,239 - 38,819; P=0.028), and mean SOFA >= 6,8 (OR:10.293; 95%CI:1,752-60,474; P=0.010). Conclusions: AEs occurred in many studied ICU admissions, and more than half of these events was clinical process / procedure type. About 6% of AEs were considered serious or associated with death of the patient. The occurrence of AEs was a independent risk factor for death, especially the clinical process / procedure type, and AEs with HD. Risk factors for the occurrence of AEs with HD were the nursing workload and the patient severity