Statistical Computing In R

A licence is granted for personal study and classroom use. Redistribution in any other form is prohibited. Languages shape the way we think, and determine what we can think about (Benjamin Whorf.). This latest revision has corrected several errors. I plan, in due course, to post a new document that will largely replace this now somewhat dated document, taking more adequate account of recent changes and enhancements to the R system and its associated packages since 2002.

The critical density of a freeway link is subject to changes over time owing to such circumstances as environmental conditions (snow, rain, etc.) and traffic incidents. Because of the critical density's impacts on the performance of some ramp metering strategies that make use of it as a threshold value for control action, it is necessary to trace the real value of the critical density. Hence, methodologies for the online estimation of critical density using the extended Kalman filter (EKF) and Kalman filter (KF) are proposed in this paper. Basically, critical density is chosen as the state variable to be determined using the system output, namely the measurement of traffic flow on the downstream freeway link. These methods are compared with a similar methodology by Smaragdis et al. ( ) using the same traffic conditions implemented in a macroscopic simulation model based on MATLAB. Then, these proposed methods are evaluated in microscopic simulation environments using PARAMICS. In tracing timedependent changes of real critical occupancy effectively, the results indicate that both methods (using KF and EKF) provide better performance compared with the case where constant critical occupancy is used for all the scenarios tested. Our paper contributes to state of the art by using a novel on-line parameter estimation techniques combined with two different feedback based ramp metering strategies namely ALINEA and MIXCROS and then by testing this new approach in a highly stochastic microscopic simulation environment that can be considered a close representation of real-world conditions. TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal.

This study investigated the impact of dust samples from Romania on small-scale silicon-based photovoltaic (PV) devices through field and laboratory experiments. Nonhomogeneous layers of natural dust were intentionally applied to the surfaces of three crystalline and amorphous silicon mini units, with dust film depth measured using an ultrasonic coating thickness gauge. Indoor testing employed a Xenon solar simulator. Key findings reveal significant deterioration in PV electrical characteristics, with maximum losses of 45.35% and 38.14% in maximum power and short-circuit current under outdoor conditions. Indoors, maximum losses were 32.02% and 33.38% for the same parameters. Temperature increases were a maximum of 2.3 • C outdoors and 0.9 • C indoors at the back surface and 3.7 • C and 1.3 • C at the front surface, respectively. The back surface proved to be a better thermal representative due to lower randomness in measured temperature values. Field experiments demonstrated greater reliability than laboratory ones despite using professional equipment. The lack of standardized indoor testing practices is believed to contribute to this discrepancy. The significance of this study lies in updating the literature with experimental studies simulating a relatively extreme condition involving dust thickness densities of 0.01936 and 0.02287 µm mm-2. This scenario is not precluded from occurring in Europe with the escalating impacts of climate change.

R topics documented: ablineclip.......................................... 4 add.ps............................................ 6 addtable2plot........................................ 7 arctext............................................ 9 axis.break.......................................... 10 axis.mult........................................... 12 barlabels........................................... 13 barNest........................................... 14 barNest.svymean...................................... 17 barNest.svyprop....................................... 18 barp............................................. 20 1 2 R topics documented: battleship.plot........................................ 23 bin.wind.records...................................... 24

A licence is granted for personal study and classroom use. Redistribution in any other form is prohibited. Languages shape the way we think, and determine what we can think about (Benjamin Whorf.). This latest revision has corrected several errors. I plan, in due course, to post a new document that will largely replace this now somewhat dated document, taking more adequate account of recent changes and enhancements to the R system and its associated packages since 2002.

The immunization program must be sustained yearly because new babies are born every year new vaccines are
being introduced, and a high level of population immunity to illnesses must be maintained. OBJECTIVES: To assess
immunization among Children under 6 years in urban and rural for the years 2020-2022. The study was conducted to
statistical and analyse the number of children in a primary care centre, and to evaluate the use of geographic information
system technology as a tool for spatial mapping of the vaccine coverage method and analysis by interpolation in two ways
and statistical analysis in R language programming, as well as the analysis vaccinations table in Excel. Data were gathered
from Health Department Dhi Qar. The governorate is distinguished by its huge size (13738.67 km²). divided into 15
administrative units. The number of health centres' immunization services available is about 95 centres and the number of
children is about 308207. Outcome: the study found that the immunization services were (4 -7 % in 5 health sectors) class
weak, (8-11% in 2 health sectors) class below moderate, and (12-15 % in 1 health sector) class moderate, and (18-22 % in
2 health sector) class strong. The common reasons for non-immunization it was a lack of information and lack of attention
from the parents and Child disease added to that (COVID-19). Identify urban areas with low immunization coverage thanks
to the spatial mapping of immunization coverage. Conclusions: Vaccine coverage in the region needs to be improved
further, which can be accomplished by educating mothers, the exclusion of unvaccinated children from school is a critical
factor in ensuring the success of the program.

Atajos personalizados o funciones A veces es útil tener un acceso directo para una expresión R larga. Un ejemplo común de esta configuración es un enlace activo para acceder al último resultado de expresión de nivel superior sin tener que escribir .Last.value : makeActiveBinding(".", function(){.Last.value}, .GlobalEnv) Debido a que .Rprofile es solo un archivo R, puede contener cualquier código R arbitrario. Pre-carga de los paquetes más útiles. Esta es una mala práctica y, por lo general, debe evitarse porque separa el código de carga de paquetes de los scripts donde se usan esos paquetes. Ver también Consulte la help(Startup) para ver los diferentes scripts de inicio y otros aspectos. En particular, también se pueden cargar dos archivos de Profile todo el sistema. El primero, Rprofile , puede

You know the SET statement and the MERGE statement. Is there more to it? Well, yeah there are a few more tricks to know. We will discuss random access to SAS data sets, based on observation numbers or indices and we will create a “look ahead ” to see what is in the next observation (more or less the opposite of the LAG function). We will explain how to prevent the well-known note in the SAS Log: “MERGE statement has more than one data set with repeats of BY values”. Then it is time to move on to the UPDATE and MODIFY statements. We will discuss their features and the differences between these statements and SET and MERGE.

R topics documented: ablineclip.......................................... 4 addtable2plot........................................ 5 arctext............................................ 6 axis.break.......................................... 7 axis.mult........................................... 8 barNest........................................... 10 barNest.svymean...................................... 12 barNest.svyprop....................................... 14 barp............................................. 15 bin.wind.records...................................... 18 boxed.labels......................................... 19

R topics documented: ablineclip.......................................... 4 add.ps............................................ 6 addtable2plot........................................ 7 arctext............................................ 9 axis.break.......................................... 10 axis.mult........................................... 12 barlabels........................................... 13 barNest........................................... 14 barNest.svymean...................................... 17 barNest.svyprop....................................... 18 barp............................................. 20 1 2 R topics documented: battleship.plot........................................ 23 bin.wind.records...................................... 24

Supplemental material, sj-pdf-2-sgo-10.1177_21582440211040121 for Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance by Rikkert M. van der Lans, Ridwan Maulana, Michelle Helms-Lorenz, Carmen-María Fernández-García, Seyeoung Chun, Thelma de Jager, Yulia Irnidayanti, Mercedes Inda-Caro, Okhwa Lee, Thys Coetzee, Nurul Fadhilah, Meae Jeon and Peter Moorer in SAGE Open

Supplemental material, sj-pdf-2-sgo-10.1177_21582440211040121 for Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance by Rikkert M. van der Lans, Ridwan Maulana, Michelle Helms-Lorenz, Carmen-María Fernández-García, Seyeoung Chun, Thelma de Jager, Yulia Irnidayanti, Mercedes Inda-Caro, Okhwa Lee, Thys Coetzee, Nurul Fadhilah, Meae Jeon and Peter Moorer in SAGE Open

Machine learning blends concepts and techniques from many different traditional fields, such as mathematics, statistics, and computer science. As such, there are many ways to learn the discipline. Considering its theoretical foundations in mathematics and statistics, newcomers would do well to attain some degree of mastery of the formal specifications of basic machine learning techniques. There are many excellent books that focus on the fundamentals, the classic work being Hastie, Tibshirani, and Friedman's The Elements of Statistical Learning ([HTF09]; full references can be found in the Works Cited). 1 But another important part of the hacker mantra is to learn by doing. Many hackers may be more comfortable thinking of problems in terms of the process by which a solution is attained, rather than the theoretical foundation from which the solution is derived. From this perspective, an alternative approach to teaching machine learning would be to use "cookbook"-style examples. To understand how a recommendation system works, for example, we might provide sample training data and a version of the model, and show how the latter uses the former. There are many useful texts of this kind as well, and Segaran's Programming Collective Intelligence is one recent example [Seg07]. Such a discussion would certainly address the how of a hacker's method of learning, but perhaps less of the why. Along with understanding the mechanics of a method, we may also want to learn why it is used in a certain context or to address a specific problem. 1. The Elements of Statistical Learning can now be downloaded free of charge at http://www-stat.stanford .edu/~tibs/ElemStatLearn/.

Depends mvtnorm, lattice, R (> = 2.4.1) Description This package implements a methodology for the design and analysis of dose-response studies that combines aspects of multiple comparison procedures and modeling approaches (Bretz,Pinheiro and Branson, 2005, Biometrics 61, 738-748). The package provides tools for the analysis of dose finding trials as well as a variety of tools necessary to plan a trial to be conducted with the MCPMod methodology. ***NOTE** * The MCPMod package will not be further developed, all future development of the MCP-Mod methodology will be done in the DoseFinding R-package. ***NOTE***

Description The Function performs a parallel analysis using simulated polychoric correlation matrices. The nth-percentile of the eigenvalues distribution obtained from both the randomly generated and the real data polychoric correlation matrices is returned. A plot comparing the two types of eigenvalues (real and simulated) will help determine the number of real eigenvalues that outperform random data. The function is based on the idea that if real data are non-normal and the polychoric correlation matrix is needed to perform a Factor Analysis, then the Parallel Analysis method used to choose a non-random number of factors should also be based on randomly generated polychoric correlation matrices and not on Pearson correlation matrices. Version 1.1.1, fixed a minor bug in the regarding the estimated time needed to complete the simulation. Also in this version, the function is now able to manage supplied data.matrix in which variables representing factors (i.e.,variables with ordered...

Declaration of Originality This dissertation presents the results of research conducted at the Royal Botanic Gardens, Sydney, of the Botanic Gardens and Domain Trust and the Faulty of Agriculture and Environment, The University of Sydney. The content is, to the best of my knowledge, original and contains no work formally published or written by another person except where dully acknowledged. This thesis does

To understand how statistical and other types of reasoning are coordinated with actions to reduce uncertainty, we conducted a case study in vocational education that involved statistical hypothesis testing. We analyzed an intern's research project in a hospital laboratory in which reducing uncertainties was crucial to make a valid statistical inference. In his project, the intern, Sam, investigated whether patients' blood could be sent through pneumatic post without influencing the measurement of particular blood components. We asked, in the process of making a statistical inference, how are reasons and actions coordinated to reduce uncertainty? For the analysis, we used the semantic theory of inferentialism, specifically, the concept of webs of reasons and actions-complexes of interconnected reasons for facts and actions; these reasons include premises and conclusions, inferential relations, implications, motives for action, and utility of tools for specific purposes in a particular context. Analysis of interviews with Sam, his supervisor and teacher as well as video data of Sam in the classroom showed that many of Sam's actions aimed to reduce variability, rule out errors, and thus reduce uncertainties so as to arrive at a valid inference. Interestingly, the decisive factor was not the outcome of a t test but of the reference change value, a clinical chemical measure of analytic and biological variability. With insights from this case study, we expect that students can be better supported in connecting statistics with context and in dealing with uncertainty.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

SUMMARY This report presents an Advanced Real-time ramp Metering System, ARMS, which consists of three levels of control algorithms integrated for exible control of freeway ramp metering systems. The objective of ARMS is to provide real-time control of a system of ramp meters both to reduce the onset of congestion and to explicitly address congestion resolution.

A simulation study is a useful tool in examining how validly item response theory (IRT) models can be applied in various settings. Typically, a large number of replications are required to obtain the desired precision. However, many standard software packages in IRT, such as MULTILOG and BILOG, are not well suited for a simulation study requiring a large number of replications because they were developed as a stand-alone software package that is best suited for a single run. This article demonstrated how built-in R functions can be used to automate the simulation study using the stand-alone software packages in IRT. For a demonstration purpose, MULTILOG was used in the example codes in the appendices, but the overall framework of a simulation study and the builtin R functions used in this article can be applied for a simulation study using other stand-alone software packages as well.

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m 2 on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R 2 values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment.

Models to predict ramp meter queue length from traffic detector data are potentially useful tools in improving traffic operations and safety. Existing research, however, has been based on microscopic simulation or relied on extensive calibration of Kalman filter and related models to produce reliable queue length estimates. This research seeks to develop methodologies for improving and simplifying the calibration process of existing queue length models by applying loop detector data including volume, occupancy, and the metering rate data for ramp meters along I-15 in Utah. A conservation model and several variations of a Kalman filter model generated estimated queues that were compared to observed queue lengths in 60 s bins. A modified Kalman filter model and a new heuristic model derived from cluster analysis—the models that yielded the best results—provided queue length estimates that were generally within approximately eight vehicles of the observed queue length. Using the ramp m...

16. ABSTRACT A major challenge for implementing queue control has been to accurately estimate on-ramp queue lengths, particularly during saturated onramp conditions, when the vehicle queue extends around or beyond the ramp entrance. The main outcome of the research was the development and field test verification of an accurate on-ramp queue length estimation algorithm based on vehicle re-identification, which performs reliably even under severe on-ramp saturated conditions. Four different queue estimation methodologies were studied using wireless magnetic sensors installed on a single lane loop on-ramp. Queue length estimation based on (i) occupancy measurements at ramp entrance, (ii) vehicle counts at on-ramp entrance and exit, (iii) speed measurements at ramp entrance, and (iv) vehicle re-identification were considered. These queue estimation methods were evaluated using available raw and processed sensor data, retrieved from the test site through mobile data communication and dow...

Scatterplot3d is an R package for the visualization of multivariate data in a three dimensional space. R is a "language for data analysis and graphics". In this paper we discuss the features of the package. It is designed by exclusively making use of already existing functions of R and its graphics system and thus shows the extensibility of the R graphics system. Additionally some examples on generated and real world data are provided, as well as the source code and the help page of scatterplot3d.

Heavy ramp volumes on urban freeway frontage roads can cause operating problems at adjacent diamond interchanges if the spacing between the cross street and the ramps is not adequate. Spacing requirements from diamond interchanges were studied for both exit ramps and entrance ramps. Exit ramps should provide sufficient storage for the vehicles queued at the cross street as well as an adequate distance for the weaving and braking maneuvers performed by exiting vehicles. Entrance ramps should provide sufficient spacing to prevent queueing through the cross-street intersection. Studies were made on several Texas freeways to provide data to be used to determine spacing requirements. Volume and queue counts were conducted to determine realistic volumes. These studies were used to determine design criteria and to further justify the analytic exit- and entrance-ramp models presented. /Authors/

The study investigated the knowledge of Ghanaian mothers on birth spacing, how this knowledge influenced their attitudes and birth spacing practices and possible implications for maternal health and child nutrition. A total of 200 mothers attending antenatal and/or postnatal clinics at a hospital in Accra participated in the study. A structured questionnaire with both open and close ended questions was used to collect information on socio-demographic characteristics of respondents, knowledge on birth spacing, attitudes towards birth spacing and the practices of birth spacing. The results revealed that a greater proportion of women (98%) had heard about birth spacing, however only a few (10%) had in depth knowledge. The top three birth spacing methods known by most respondents were pills (83%), followed by the male or female condom (72%) and abstinence (56%). The study sample used a variety of birth spacing methods with majority using various short-term contraceptives e.g. the pill, ...

Supplemental material, Beauducel_Kersting_Supplement_R1 for Identification of Facet Models by Means of Factor Rotation: A Simulation Study and Data Analysis of a Test for the Berlin Model of Intelligence Structure by André Beauducel and Martin Kersting in Educational and Psychological Measurement

Principal component analysis (PCA) has been successfully applied in large scale process monitoring. However, classical PCA has some drawbacks: one of these aspects is the inability to deal with parameter-varying processes, where it interprets the natural changes in the process as faults, resulting in numerous false alarms. These false alarms threaten the credibility of the monitoring system. Therefore, recursive PCA (RPCA) algorithms are recommended. The most important challenge faced by these algorithms is the high computation costs, due to repeated eigenvalue decomposition (EVD) or singular value decomposition (SVD). Motivated by this issue, we present two RPCA algorithms that will greatly reduce the computation cost. The first algorithm is based on first-order perturbation analysis (FOP), which is a rank-one update of the eigenvalues and their corresponding eigenvectors of a sample covariance matrix. The second one is based on the data projection method (DPM), which is a simple and reliable approach for adaptive subspace tracking. The effectiveness of the presented RPCA algorithms is evaluated with an application of monitoring a nonisothermal continuous stirred tank reactor (CSTR) system. The results show the efficiency of these approaches compared to the classical PCA.

Acute Lower Respiratory Infections (ALRIs) account for 5.8 million deaths globally and 50% of these deaths occur in sub-Saharan Africa. In this paper, we examined the prevalence and determinants of ALRIs among children under-five years in 28 sub-Saharan African countries. We used data from the most recent (2011-2016) Demographic and Health Surveys of the 28 countries. Women aged 15-49 (N = 13,495) with children under-five years participated in the study. Data were extracted and analysed using STATA version 14.2. Bivariate and multivariate analyses were done to establish associations between the outcome and explanatory variables. The prevalence of ALRI for all the countries was 25.3%. Congo (39.8%), Gabon (38.1%), Lesotho (35.2%), and Tanzania (35.2%) were the countries with the highest prevalence of ALRIs. The results from the multivariate analyses showed that children aged 24-59 months (AOR = 1.15; 95% CI = 1.04-1.28), and children who received intestinal parasite in the 6 months preceding the survey (AOR = 1.11; 95% CI = 1.02-1.22) had higher odds of developing ALRIs. However, children whose mothers were employed (AOR = 0.77; 95% CI = 0.64-0.94) and those whose households used improved toilet facilities (AOR = 0.72; 95% CI = 0.64-0.97) had lower odds of contracting ALRIs. Our findings underscore the need for stakeholders in health in the various sub-Saharan African countries, especially those worst affected by ALRIs to implement programmes and develop policies at different levels aimed at reducing infections among children under-five years. Such strategies should specifically focus on improving the administration of medications for intestinal worms, health education to mothers with children under five on ALRIs and improving the sanitation situations of households through the provision of improved toilet facilities.

Smart cities, participatory sensing as well as location data available in communication systems and social networks generates a vast amount of heterogeneous mobility data that can be used for traffic management. This chapter gives an overview of the different data sources and their characteristics and describes a framework for utilizing the various sources efficiently in the context of traffic management. Furthermore, different types of traffic models and algorithms are related to both the different data sources as well as some key functionalities of active traffic management, for example short-term prediction and control.

In Ghana, diarrhoea is one of the leading causes of childhood morbidity and mortality. The objective of this study was to examine maternal and child level factors associated with diarrhoea among children in Ghana. A weighted group of 4,821 mother-child dyads was used for the analysis. The analysis was restricted to mothers with children under 2 years of age. Multivariate logistic regression analysis was performed on the pooled data. The pooled prevalence of diarrhoea among the children was 18 per cent. It was found that children older than five months, rural children, children whose mothers had 24 months or more preceding birth interval, and those houses' floors made of unimproved materials were more likely to have had experienced diarrhoea. While children with mothers who obtained secondary or higher education and those had access to unimproved sources of drinking water reported less occurrence of diarrhoea. Maternal and child factors have some effects on the occurrence of diarrhoea among children less than two years in Ghana. To decrease the prevalence of childhood diarrhoea in the country, more educative programmes are required for mothers whose children are more likely to having frequent episodes of diarrhoea.

This course introduces students to the logic of social inquiry. The first half covers the fundamentals of research. Students learn how to identify puzzles, formulate research questions, and review the literature for the answers previous studies offer. The second half focuses on how scholars design new research to build on existing works to advance knowledge further. Accordingly, the weekly classes in the second half assist students in writing their own research proposals, which employ qualitative, quantitative, experimental or mixed methods. The classes cover the philosophies that underlie each method, and demonstrate how methods can often complement each other. Students thus learn how to utilize the strengths of each method, while developing a more encompassing perspective on social research.

Supplemental material, sj-pdf-2-sgo-10.1177_21582440211040121 for Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance by Rikkert M. van der Lans, Ridwan Maulana, Michelle Helms-Lorenz, Carmen-María Fernández-García, Seyeoung Chun, Thelma de Jager, Yulia Irnidayanti, Mercedes Inda-Caro, Okhwa Lee, Thys Coetzee, Nurul Fadhilah, Meae Jeon and Peter Moorer in SAGE Open

Active traffic management aims to dynamically manage congestion based on existing and predicted traffic conditions. A challenge in this is that it is not usually possible to process data in real-time and use the output in control algorithms or in traveler information systems. A solution to this is to predict the traffic state based on assessments of current and past measurements. The work described in this paper develops an adaptive forecasting method to predict traffic speeds using dynamic linear models with Bayesian inference from a priori distributions. This study incorporates speeds collected from radar based sensors and validates the results with data collected from Bluetooth traffic monitoring technology. The highly adaptive model is confirmed with estimated traffic speeds during inclement weather and multiple incidents.

Smart cities, participatory sensing as well as location data available in communication systems and social networks generates a vast amount of heterogeneous mobility data that can be used for traffic management. This chapter gives an overview of the different data sources and their characteristics and describes a framework for utilizing the various sources efficiently in the context of traffic management. Furthermore, different types of traffic models and algorithms are related to both the different data sources as well as some key functionalities of active traffic management, for example short-term prediction and control.

Acute Lower Respiratory Infections (ALRIs) account for 5.8 million deaths globally and 50% of these deaths occur in sub-Saharan Africa. In this paper, we examined the prevalence and determinants of ALRIs among children under-five years in 28 sub-Saharan African countries. We used data from the most recent (2011-2016) Demographic and Health Surveys of the 28 countries. Women aged 15-49 (N = 13,495) with children under-five years participated in the study. Data were extracted and analysed using STATA version 14.2. Bivariate and multivariate analyses were done to establish associations between the outcome and explanatory variables. The prevalence of ALRI for all the countries was 25.3%. Congo (39.8%), Gabon (38.1%), Lesotho (35.2%), and Tanzania (35.2%) were the countries with the highest prevalence of ALRIs. The results from the multivariate analyses showed that children aged 24-59 months (AOR = 1.15; 95% CI = 1.04-1.28), and children who received intestinal parasite in the 6 months preceding the survey (AOR = 1.11; 95% CI = 1.02-1.22) had higher odds of developing ALRIs. However, children whose mothers were employed (AOR = 0.77; 95% CI = 0.64-0.94) and those whose households used improved toilet facilities (AOR = 0.72; 95% CI = 0.64-0.97) had lower odds of contracting ALRIs. Our findings underscore the need for stakeholders in health in the various sub-Saharan African countries, especially those worst affected by ALRIs to implement programmes and develop policies at different levels aimed at reducing infections among children under-five years. Such strategies should specifically focus on improving the administration of medications for intestinal worms, health education to mothers with children under five on ALRIs and improving the sanitation situations of households through the provision of improved toilet facilities.

This paper develops an automatic freeway bottleneck identification and visualization algorithm using a combination of image processing techniques and traffic flow theory. Unlike previous studies that are based solely on loop detector data, the proposed method can use traffic measurements from various sensing technologies. Four steps are included in the proposed algorithm. First, the raw spatiotemporal speed data are transformed into binary matrices using image binarization techniques. Second, two post-processer filters are developed to clean the binary matrices by filtering scattered noise cells and localized congested regions. Subsequently, the roadway geometry information is used to remove the impact of acceleration zones downstream of bottlenecks and thus locate bottlenecks more precisely. Finally, the major characteristics of bottlenecks including activation and deactivation points, shockwave speeds and traffic delay caused by bottleneck are automatically extracted and visualize...

L'analyse et la mesure de la qualite de vie peuvent se faire via deux approches differentes et complementaires. La premiere est tournee vers l'analyse des niveaux de satisfaction de la vie a l'aide d'enquetes aupres des individus. La seconde, a laquelle nous nous interessons ici, vise a analyser les conditions de vie des personnes et s'appuie sur des donnees nationales. L'enjeu de cette approche consiste a creer des indices composites des conditions de vie. Dans cet objectif, les methodes de reduction de dimension sont particulierement adaptees car elles permettent de construire de nouvelles variables qui resument "au mieux" l'information contenue dans les variables initiales. Selon Noll [1], les composantes de la qualite de vie sont reliees a differents themes (groupes de variables) dont les plus souvent cites sont "Les conditions familiales", "Les conditions economiques", "Les conditions de logement", "L'...