828 resultados para visual data analysis


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Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radiofrequency electromagnetic field (RF-EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount of personal exposure data, which can be obtained for several RF-EMF sources. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression on order statistics) method, summary statistics can be calculated by fitting an assumed distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust ROS with a naïve approach, where values below the detection limit were replaced by the value of the detection limit. For the total RF-EMF exposure, differences between the naïve approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF-EMF sources were considerably overestimated with the naïve approach. This results in an underestimation of the exposure range in the population, which may bias the evaluation of potential exposure-response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based on a naïve approach. Nevertheless, estimates of source-specific medians or even lower percentiles depend on the assumed data distribution and should be considered with caution.

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Turrialba is one of the largest and most active stratovolcanoes in the Central Cordillera of Costa Rica and an excellent target for validation of satellite data using ground based measurements due to its high elevation, relative ease of access, and persistent elevated SO2 degassing. The Ozone Monitoring Instrument (OMI) aboard the Aura satellite makes daily global observations of atmospheric trace gases and it is used in this investigation to obtain volcanic SO2 retrievals in the Turrialba volcanic plume. We present and evaluate the relative accuracy of two OMI SO2 data analysis procedures, the automatic Band Residual Index (BRI) technique and the manual Normalized Cloud-mass (NCM) method. We find a linear correlation and good quantitative agreement between SO2 burdens derived from the BRI and NCM techniques, with an improved correlation when wet season data are excluded. We also present the first comparisons between volcanic SO2 emission rates obtained from ground-based mini-DOAS measurements at Turrialba and three new OMI SO2 data analysis techniques: the MODIS smoke estimation, OMI SO2 lifetime, and OMI SO2 transect techniques. A robust validation of OMI SO2 retrievals was made, with both qualitative and quantitative agreements under specific atmospheric conditions, proving the utility of satellite measurements for estimating accurate SO2 emission rates and monitoring passively degassing volcanoes.

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Water resource depletion and sanitation are growing problems around the world. A solution to both of these problems is the use of composting latrines, as it requires no water and has been recommended by the World Health Organization as an improved sanitation technology. However, little analysis has been done on the decomposition process occurring inside the latrine, including what temperatures are reached and what variables most affect the composting process. Having better knowledge of how outside variables affect composting latrines can aid development workers on the choice of implementing such technology, and to better educate the users on the appropriate methods of maintenance. This report presents a full, detailed construction manual and temperature data analysis of a double vault composting latrine. During the author’s two year Peace Corps service in rural Paraguay he was involved with building twenty one composting latrines, and took detailed temperature readings and visual observations of his personal latrine for ten months. The author also took limited temperature readings of fourteen community member’s latrines over a three month period. These data points were analyzed to find correlations between compost temperatures and several variables. The two main variables found to affect the compost temperatures were the seasonal trends of the outside temperatures, and the mixing and addition of moisture to the compost. Outside seasonal temperature changes were compared to those of the compost and a linear regression was performed resulting in a R2-value of 0.89. Mixing the compost and adding water, or a water/urine mixture, resulted in temperature increases of the compost 100% of the time, with seasonal temperatures determining the rate and duration of the temperature increases. The temperature readings were also used to find events when certain temperatures were held for sufficient amounts of time to reach total pathogen destruction in the compost. Four different events were recorded when a temperature of 122°F (50°C) was held for at least 24 hours, ensuring total pathogen destruction in that area of the compost. One event of 114.8°F (46°C) held for one week was also recorded, again ensuring total pathogen destruction. Through the analysis of the temperature data, however, it was found that the compost only reached total pathogen destruction levels during ten percent of the data points. Because of this the storage time recommendation outlined by the World Health Organization should be complied with. The WHO recommends storing compost for 1.5-2 years in climates with ambient temperatures of 2-20°C (35-68°F), and for at least 1 year with ambient temperatures of 20-35°C (68-95°F). If these storage durations are obtainable the use of the double vault composting latrine is an economical and achievable solution to sanitation while conserving water resources.

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Principal Component Analysis (PCA) is a popular method for dimension reduction that can be used in many fields including data compression, image processing, exploratory data analysis, etc. However, traditional PCA method has several drawbacks, since the traditional PCA method is not efficient for dealing with high dimensional data and cannot be effectively applied to compute accurate enough principal components when handling relatively large portion of missing data. In this report, we propose to use EM-PCA method for dimension reduction of power system measurement with missing data, and provide a comparative study of traditional PCA and EM-PCA methods. Our extensive experimental results show that EM-PCA method is more effective and more accurate for dimension reduction of power system measurement data than traditional PCA method when dealing with large portion of missing data set.

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Dr. Rossi discusses the common errors that are made when fitting statistical models to data. Focuses on the planning, data analysis, and interpretation phases of a statistical analysis, and highlights the errors that are commonly made by researchers of these phases. The implications of these commonly made errors are discussed along with a discussion of the methods that can be used to prevent these errors from occurring. A prescription for carrying out a correct statistical analysis will be discussed.

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The term visual field corresponds to the angular field of view that is seen by the eyes when they are fixed on a point straight-ahead. In neurological patients--e.g. stroke, trauma, or tumour patients--visual field function can be restricted, depending on lesion site and size. In contrast, the term "functional visual field" describes the area of visual field responsiveness under more ordinary viewing conditions. The visual exploration, i.e. the capacity to explore and analyze our visual world, is dependent on the integrity of the visual system and the oculomotor system which has to move the fovea from one object of interest to the next. In this paper, we present a new method to assess the functional visual field, conceptualized as the area that a patient actively scans with eye movements to detect predefined targets placed on everyday scenes. This method allows us to compare three levels of visual field function: (a) the spatial distribution of successful search (hits, i.e. which targets did the patient find?), (b) the spatial distribution of fixations (i.e. where did the patient preferentially search for targets?), and (c) the retinotopic level (i.e. the visual field assessed by perimetry). By integrating these three levels, one can evaluate functional outcomes of visual field disorders. Of particular importance is the question of how a patient compensates for a visual field loss with appropriate eye movements. A further clinical application of this method is the comparison of pre- with post-treatment data. Patients with visual field disorders usually undergo specific exploration trainings, aimed at enhancing the number and amplitude of saccades towards the region of the visual field deficit. The first experiences and clinical application with this method are presented here.

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Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

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This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

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Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

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Objectives: In fast ball sports like beach volleyball, decision-making skills are a determining factor for excellent performance. The current investigation aimed to identify factors that influence the decisionmaking process in top-level beach volleyball defense in order to find relevant aspects for further research. For this reason, focused interviews with top players in international beach volleyball were conducted and analyzed with respect to decision-making characteristics. Design: Nineteen world-tour beach volleyball defense players, including seven Olympic or world champions, were interviewed, focusing on decision-making factors, gaze behavior, and interactions between the two. Methods: Verbal data were analyzed by inductive content analysis according to Mayring (2008). This approach allows categories to emerge from the interview material itself instead of forcing data into preset classifications and theoretical concepts. Results: The data analysis showed that, for top-level beach volleyball defense, decision making depends on opponent specifics, external context, situational context, opponent's movements, and intuition. Information on gaze patterns and visual cues revealed general tendencies indicating optimal gaze strategies that support excellent decision making. Furthermore, the analysis highlighted interactions between gaze behavior, visual information, and domain-specific knowledge. Conclusions: The present findings provide information on visual perception, domain-specific knowledge, and interactions between the two that are relevant for decision making in top-level beach volleyball defense. The results can be used to inform sports practice and to further untangle relevant mechanisms underlying decision making in complex game situations.

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OBJECTIVES To identify the timing of significant arch dimensional increases during orthodontic alignment involving round and rectangular nickel-titanium (NiTi) wires and rectangular stainless steel (SS). A secondary aim was to compare the timing of changes occurring with conventional and self-ligating fixed appliance systems. METHODS In this non-primary publication, additional data from a multicenter randomised trial initially involving 96 patients, aged 16 years and above, were analysed. The main pre-specified outcome measures were the magnitude and timing of maxillary intercanine, interpremolar, and intermolar dimensions. Each participant underwent alignment with a standard Damon (Ormco, Orange, CA) wire sequence for a minimum of 34 weeks. Blinding of clinicians and patients was not possible; however, outcome assessors and data analysts were kept blind to the appliance type during data analysis. RESULTS Complete data were obtained from 71 subjects. Significant arch dimensional changes were observed relatively early in treatment. In particular, changes in maxillary inter-first and second premolar dimensions occurred after alignment with an 0.014in. NiTi wire (P<0.05). No statistical differences in transverse dimensions were found between rectangular NiTi and working SS wires for each transverse dimension (P>0.05). Bracket type had no significant effect on the timing of the transverse dimensional changes. CONCLUSIONS Arch dimensional changes were found to occur relatively early in treatment, irrespective of the appliance type. Nickel-titanium wires may have a more profound effect on transverse dimensions than previously believed. CLINICAL SIGNIFICANCE On the basis of this research orthodontic expansion may occur relatively early in treatment. Nickel-titanium wires may have a more profound effect on transverse dimensions than previously believed.

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Because of the impact that mathematical beliefs have on an individual’s behaviour, they are generally well researched. However, little mathematical belief research has taken place in the field of adult education. This paper presents preliminary results from a study conducted in this field in Switzerland. It is based on Ernest’s (1989) description of mathematics as an instrumental, Platonist or problem solving construct. The analysis uses pictures drawn by the participants and interviews conducted with them as data. Using a categorising scheme developed by Rolka and Halverscheid (2011), the author argues that adults’ mathematical beliefs are complex and especially personal aspects are difficult to capture with said scheme. Particularly the analysis of visual data requires a more refined method of analysis.

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PRINCIPALS Over a million people worldwide die each year from road traffic injuries and more than 10 million sustain permanent disabilities. Many of these victims are pedestrians. The present retrospective study analyzes the severity and mortality of injuries suffered by adult pedestrians, depending on whether they used a zebra crosswalk. METHODS Our retrospective data analysis covered adult patients admitted to our emergency department (ED) between 1 January 2000 and 31 December 2012 after being hit by a vehicle while crossing the road as a pedestrian. Patients were identified by using a string term. Medical, police and ambulance records were reviewed for data extraction. RESULTS A total of 347 patients were eligible for study inclusion. Two hundred and three (203; 58.5%) patients were on a zebra crosswalk and 144 (41.5%) were not. The mean ISS (injury Severity Score) was 12.1 (SD 14.7, range 1-75). The vehicles were faster in non-zebra crosswalk accidents (47.7 km/n, versus 41.4 km/h, p<0.027). The mean ISS score was higher in patients with non-zebra crosswalk accidents; 14.4 (SD 16.5, range 1-75) versus 10.5 (SD13.14, range 1-75) (p<0.019). Zebra crosswalk accidents were associated with less risk of severe injury (OR 0.61, 95% CI 0.38-0.98, p<0.042). Accidents involving a truck were associated with increased risk of severe injury (OR 3.53, 95%CI 1.21-10.26, p<0.02). CONCLUSION Accidents on zebra crosswalks are more common than those not on zebra crosswalks. The injury severity of non-zebra crosswalk accidents is significantly higher than in patients with zebra crosswalk accidents. Accidents involving large vehicles are associated with increased risk of severe injury. Further prospective studies are needed, with detailed assessment of motor vehicle types and speed.

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Noble gas analysis in early solar system materials, which can provide valuable information about early solar system processes and timescales, are very challenging because of extremely low noble gas concentrations (ppt). We therefore developed a new compact sized (33 cm length, 7.2cm diameter, 1.3 L internal volume) Time-of-Flight (TOF) noble gas mass spectrometer for high sensitivity. We call it as Edel Gas Time-of-flight (EGT) mass spectrometer. The instrument uses electron impact ionization coupled to an ion trap, which allows us to ionize and measure all noble gas isotopes. Using a reflectron set-up improves the mass resolution. In addition, the reflectron set-up also enables some extra focusing. The detection is via MCPs and the signals are processed either via ADC or TDC systems. The objective of this work is to understand the newly developed Time-Of-Flight (TOF) mass spectrometer for noble gas analysis in presolar grains of the meteorites. Chapter 1 briefly introduces the basic idea and importance of the instrument. The physics relevant to time-of-flight mass spectrometry technique is discussed in the Chapter 2 and Chapter 3 will present the oxidation technique of nanodiamonds of the presolar grains by using copper oxide. Chapter 4 will present the details about EGT data analysis software. Chapter 5 and Chapter 6 will explain the details about EGT design and operation. Finally, the performance results will be presented and discussed in the Chapter 7, and whole work is summarized in Chapter 8 and also outlook of the future work is given.