ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / There are increasing demands, particularly from government agencies, to perform uncertainty analysis in order to assign accuracy bounds to telemetered data from environmental measuring transducers (pressure, acceleration, force, strain, temperature, etc.). Several requirements must be fulfilled before measurement uncertainty analysis is justified. These requirements include good measurement system design practices such as adequate low- and high-frequency response and data-sampling rates, appropriate anti-aliasing filter selection^(1), proper grounding and shielding, and many more. In addition, there are applications (e.g., flight test) in which the environment of the transducer varies with time and/or location. In these applications, it is a requisite that data-validation be performed to establish that an individual transducer responds only to the environmental stimulus that it is intended to measure. Without this validation component designed into the telemetry system, assigned accuracy bounds can be totally meaningless. This paper presents examples and describes techniques for data validation of signals from environmental measuring transducers.

When presented in a practical format, real-time transit information can improve sustainable travel methods by enhancing the transit experience. Larger shifts towards public transportation have cascading effects on the environment, health and urban form. The research will identify the positive shift realized by the continued development of a set of real-time transit information tools, specifically in the Seattle region. In addition, it will analyze real-time prediction errors and their effects on the rider experience. Three years after the development of location-aware mobile applications for OneBusAway - a suite of real-time information tools - a survey of current users was conducted by the author in 2012 in order to compare the results to a 2009 study. The results show significant positive shifts in satisfaction with transit, perceptions of safety and ridership frequency as a result of the increased use of real-time arrival information. However, the research will also provide a perspective of the margin of error riders come to expect and the negative effects resulting from inaccuracies with the real-time data. While riders on average will ride less when they have experienced errors, a robust issue-reporting system as well as the resolution of the error can mitigate the initial negative effects. In response, the research provides a framework for a crowd-sourced error reporting process in order to improve the level of accuracy by means of a Transit Ambassador Program. Finally, a pilot program developed by the author is assessed against this framework and insight is provided within the context of the real-time information system.

Mindfulness exercises have been reported to increase performance for a number of different populations; however there are no reports that have investigated the effects of brief mindfulness exercises on data collection. This study will exposed participants to a brief mindfulness exercise and subsequently measure participants’ ability to accurately take data on high rate behavior. A concurrent multiple baseline design was used with three participants. During baseline phases participants recorded data on the occurrence of congruent and incongruent stimuli within a Stroop presentation. Treatment phases contained a brief mindful eating video and then participants completed the Stroop presentation. Data sheets completed by the participants were scored for overall accuracy, as well as accuracy for congruent and incongruent stimuli. Participants completed a Mindful Attention Awareness Scale (MAAS) at the end of all sessions. Results indicated that MAAS scores increased during mindfulness sessions for all participants when compared to baseline phases. Overall accuracy as well as accuracy for congruent and incongruent stimuli in the Stroop presentation increased for all three participants compared to baseline sessions. The findings from this research have potential applications for improving performance for data collection methods and increasing self-reported mindfulness.

One of the major applications of wireless sensor networks is to sense accurate and reliable data from the physical environment with or without a priori knowledge of data statistics. To extract accurate data from the physical environment, we investigate spatial data correlation among sensor nodes to develop data accuracy models. We propose three data accuracy models namely Estimated Data Accuracy (EDA) model, Cluster based Data Accuracy (CDA) model and Distributed Cluster based Data Accuracy (DCDA) model with a priori knowledge of data statistics. Due to the deployment of high density of sensor nodes, observed data are highly correlated among sensor nodes which form distributed clusters in space. We describe two clustering algorithms called Deterministic Distributed Clustering (DDC) algorithm and Spatial Data Correlation based Distributed Clustering (SDCDC) algorithm implemented under CDA model and DCDA model respectively. Moreover, due to data correlation in the network, it has redundancy in data collected by sensor nodes. Hence, it is not necessary for all sensor nodes to transmit their highly correlated data to the central node (sink node or cluster head node). Even an optimal set of sensor nodes are capable of measuring accurate data and transmitting the accurate, precise data to the central node. This reduces data redundancy, energy consumption and data transmission cost to increase the lifetime of sensor networks. Finally, we propose a fourth accuracy model called Adaptive Data Accuracy (ADA) model that doesn't require any a priori knowledge of data statistics. ADA model can sense continuous data stream at regular time intervals to estimate accurate data from the environment and select an optimal set of sensor nodes for data transmission to the network. Data transmission can be further reduced for these optimal sensor nodes by transmitting a subset of sensor data using a methodology called Spatio-Temporal Data Prediction (STDP) model under data reduction strategies. Furthermore, we implement data accuracy model when the network is under a threat of malicious attack.

Submitted by Jadson Francisco de Jesus SILVA (jadson@uefs.br) on 2018-07-10T21:32:58Z No. of bitstreams: 1 Disserta??o final.pdf: 1336744 bytes, checksum: 0ff78b681298bc287f0b8d2f291a3106 (MD5) / Made available in DSpace on 2018-07-10T21:32:58Z (GMT). No. of bitstreams: 1 Disserta??o final.pdf: 1336744 bytes, checksum: 0ff78b681298bc287f0b8d2f291a3106 (MD5) Previous issue date: 2016-06-10 / Intestinal constipation is the most common intestinal motility disorder in the world. The objective of the current study was to evaluate the prevalence, associated factors and reliability of data on intestinal constipation in children at six months of age, according to the maternal impression; Having as main products two articles: "Intestinal constipation in children at six months of age, according to maternal report of arrested gut" and "Prevalence and factors associated with intestinal constipation at six months of age". This was a cross-sectional analysis of a cohort of live births, who followed mother-infant pairs through monthly home visits in the first six months of life. The power of the current study was 91.36%. The dependent variable was constipation of the child reported according to the maternal impression. The other variables were related to the maternal, infant and eating habits of the child. The database was entered in the statistical software SPSS (Statistical Package for the Social Sciences) version 10.0, later validated in the statistical software EPIDATA and analyzed with the help of the program STATA, version 12.0. Pearson's chi-square test was used, and their respective 95% confidence intervals (95% CI). The multivariate analysis was performed using Poisson regression in a hierarchical analysis model, adopting the significance level of 20% (p <0.20), and maintaining in the final model the variables that showed association with the dependent variable At the level of statistical significance p <0.05. To evaluate the concordance between the maternal impression and the characteristics of the intestinal habit, the kappa index was used. Among the 1,134 infants studied, 12.3% of the population had intestinal constipation at six months of age. In the bivariate analyzes, there was statistical significance for the liquidized food variable (p = 0.00) and after multivariate analysis it was verified that these foods were a risk factor for intestinal constipation RP = 1.50 (95% CI: 1.07 -2.11, p = 0.00). According to the kappa index, the agreement between the maternal impression that the child was evacuating every day was considered moderate (kappa = 0.55); (Kappa = 0, 18) and the stool appearance was substantial (kappa = 0.67). This study found prevalence of functional constipation in children at six months of age, similar to other studies developed in Brazil and the world, based on the maternal report. It is noteworthy that children who consumed liquefied foods were more likely to develop intestinal constipation. Regarding the reliability of the maternal impression, it was concluded that the characteristics of greater agreement corresponded to the appearance of hardened stools and to the daily frequency of bowel movements, emphasizing that the maternal report on the attached intestine can be a good indicator to recognize cases of intestinal constipation Six months of age. This project was approved by the Research Ethics Committee - CEP / UEFS - Protocol 077/2006 and the Higher Council for Teaching, Research and Extension - CONSEPE / UEFS - Protocol 154/2007, CAAE - 49106715.8.0000.0053. / A constipa??o intestinal ? o dist?rbio de motilidade intestinal mais frequente em todo o mundo. O objetivo do atual estudo foi avaliar a preval?ncia, os fatores associados e a confiabilidade dos dados sobre a constipa??o intestinal de crian?as aos seis meses de idade, conforme a impress?o materna; tendo como principais produtos dois artigos: ?Constipa??o intestinal em crian?as aos seis meses de idade, segundo relato materno de intestino preso? e ?Preval?ncia e fatores associados ? constipa??o intestinal aos seis meses de idade?. Tratou-se de uma an?lise transversal de uma coorte de nascidos vivos, que seguiu duplas m?e-filho mediante visitas domiciliares mensais, nos primeiros seis meses de vida. O poder do atual estudo foi de 91,36%. A vari?vel dependente foi constipa??o intestinal da crian?a relatada segundo a impress?o materna. As demais vari?veis foram referentes ?s caracter?sticas maternas, infantis e aos h?bitos alimentares da crian?a. O banco de dados foi digitado no software estat?stico SPSS (Statistical Package for the Social Sciences) vers?o 10.0, validados posteriormente no software estat?stico EPIDATA e analisados com ajuda do programa STATA, vers?o 12.0. Foi utilizado teste de qui-quadrado de Pearson, e seus respectivos intervalos de 95% de confian?a (IC95%). A an?lise multivariada foi realizada por meio de regress?o de Poisson em um modelo de an?lise hier?rquica, adotando-se o n?vel de signific?ncia de 20% (p < 0,20), e mantidas no modelo final as vari?veis que apresentaram associa??o com a vari?vel dependente em n?vel de signific?ncia estat?stica p<0,05. Para avaliar a concord?ncia entre a impress?o materna e as caracter?sticas do h?bito intestinal foi utilizado o ?ndice kappa. Dentre os 1.134 lactentes estudados, 12,3% da popula??o apresentou constipa??o intestinal aos seis meses de idade. Nas an?lises bivariadas, houve signific?ncia estat?stica para a vari?vel dos alimentos liquidificados (p=0,00) e ap?s an?lise multivariada verificou-se que esses alimentos foram fator de risco para a constipa??o intestinal RP=1,50 (IC95%:1,07?2,11; p=0,00). Segundo o ?ndice kappa, a concord?ncia entre a impress?o materna de que a crian?a evacuava todos os dias foi considerada moderada (kappa=0,55); quanto ? frequ?ncia de evacua??es semanais, a concord?ncia foi ligeira (kappa=0,18) e quanto ao aspecto das fezes, foi substancial (kappa=0,67). Este trabalho encontrou preval?ncia de constipa??o funcional de crian?as aos seis meses de idade, similar a outros estudos desenvolvidos no Brasil e no mundo, com base no relato materno. Destaca-se que as crian?as que consumiam alimentos liquidificados tinham mais chances de desenvolver constipa??o intestinal. Quanto ? confiabilidade da impress?o materna, conclui-se que as caracter?sticas de maior concord?ncia foram correspondentes ao aspecto de fezes endurecidas e ? frequ?ncia di?ria de evacua??es, salientando que o relato materno sobre o intestino preso pode ser um bom indicador para reconhecer casos de constipa??o intestinal aos seis meses de idade. Esse projeto foi aprovado pelo Comit? de ?tica em Pesquisa - CEP/UEFS - Protocolo 077/2006 e Conselho Superior de Ensino, Pesquisa e Extens?o - CONSEPE/UEFS - Protocolo 154/2007, CAAE - 49106715.8.0000.0053.

No description available.

Decisions concerning IT systems are often made without adequate decision-support. This has led to unnecessary IT costs and failures to realize business benefits. The present thesis presents a framework for analysis of four information systems properties relevant to IT decision-making. The work is founded on enterprise architecture, a model-based IT and business management discipline. Based on the existing ArchiMate framework, a new enterprise architecture framework has been developed and implemented in a software tool. The framework supports modeling and analysis of data accuracy, service performance, service availability and application usage. To analyze data accuracy, data flows are modeled, the service availability analysis uses fault tree analysis, the performance analysis employs queuing networks and the application usage analysis combines the Technology Acceptance Model and Task-Technology Fit model. The accuracy of the framework's estimates was empirically tested. Data accuracy and service performance were evaluated in studies at the same power utility. Service availability was tested in multiple studies at banks and power utilities. Data was collected through interviews with system development or maintenance staff. The application usage model was tested in the maintenance management domain. Here, data was collected by means of a survey answered by 55 respondents from three power utilities, one manufacturing company and one nuclear power plant. The service availability studies provided estimates that were accurate within a few hours of logged yearly downtime. The data accuracy estimate was correct within a percentage point when compared to a sample of data objects. Deviations for four out of five service performance estimates were within 15 % from measured values. The application usage analysis explained a high degree of variation in application usage when applied to the maintenance management domain. During the studies of data accuracy, service performance and service availability, records were kept concerning the required modeling and analysis effort. The estimates were obtained with a total effort of about 20 man-hours per estimate. In summary the framework should be useful for IT decision-makers requiring fairly accurate, but not too expensive, estimates of the four properties. / <p>QC 20120912</p>

<p>HIV/AIDS is the largest and most serious global epidemic in the recent times. To date, the epidemic has affected approximately 40 million people (range 33 &ndash / 46 million) of whom 67%, that is, an estimated 27 million people are in the Sub Saharan Africa. The Sub Saharan Africa is also reported to have the highest regional prevalence of 7.2% compared to an average of 2% in other regions. A medical cure for HIV/AIDS remains elusive but use of antiretroviral therapy (ART) has resulted in improvement of quality and quantity of life as evidenced by the reduction of mortality and morbidity associated with the infection, hence longer and good quality life for HIV/AIDS patients on ART.</p>

Video image detection system (VDS) equipment provides real-time traffic data for monitored highways directly to the traffic management center (TMC) of the Georgia Department of Transportation. However, at any given time, approximately 30 to 35% of the 1,600 camera stations (STNs) fail to work properly. The main reasons for malfunctions in the VDS system include long term road construction activity and operational limitations. Thus, providing alternative data sources for offline VDS stations and developing tools that can help detect problems with VDS stations can facilitate the successful operation of the TMC. To estimate the travel speed of non-working STNs, this research examined global positioning system (GPS) data from vehicles using the ATMS-monitored freeway system as a potential alternative measure to VDS. The goal of this study is to compare VDS speed data for the estimation of the travel speed on freeways with GPS-equipped vehicle trip data, and to assess the differences between these measurements as a potential function of traffic and roadway conditions, environmental, conditions, and driver/vehicle characteristics. The difference between GPS and VDS speeds is affected by various factors such as congestion level (expressed as level of service), onroad truck percentage, facility design (number of lanes and freeway sub-type), posted speed limit, weather, daylight, and time of day. The relationship between monitored speed difference and congestion level was particularly large and was observed to interact with most other factors. Classification and regression tree (CART) analysis results indicated that driver age was the most relevant variable in explaining variation for the southbound of freeway dataset and freeway sub-type, speed limit, driver age, and number of lane were the most influential variables for the northbound of freeway dataset. The combination of several variables had significant contribution in the reduction of the deviation for both the northbound and the southbound dataset. Although this study identifies potential relationships between speed difference and various factors, the results of the CART analysis should be considered with the driver sample size to yield statistically significant results. Expanded sampling with larger number of drivers would enrich this study results.

<p>HIV/AIDS is the largest and most serious global epidemic in the recent times. To date, the epidemic has affected approximately 40 million people (range 33 &ndash / 46 million) of whom 67%, that is, an estimated 27 million people are in the Sub Saharan Africa. The Sub Saharan Africa is also reported to have the highest regional prevalence of 7.2% compared to an average of 2% in other regions. A medical cure for HIV/AIDS remains elusive but use of antiretroviral therapy (ART) has resulted in improvement of quality and quantity of life as evidenced by the reduction of mortality and morbidity associated with the infection, hence longer and good quality life for HIV/AIDS patients on ART.</p>