Sampling

Ce mémoire vise à analyser les différentes formes de l’appropriation musicale à travers, notamment, un travail de définitions. Nous tenterons plus précisément de déterminer l’influence de l’environnement technoculturel sur l’appropriation, et plus particulièrement comment ces formes ont évolué en passant de la graphosphère à l’audiovidéosphère.

Surface monitoring by using swabs forms a regular part of environmental monitoring of cleanrooms. There are different factors that affect swab recovery, from tip type to enumeration method. One factor, for swabs where the microorganisms are detached from the swab tip and which are then membrane filtered, is the period of vortex mixing. This paper discusses microbial surface sampling, and the factors that affect swab recovery. The paper presents some experimental data where vortex times are considered for a range of microorganisms. The study outcome indicates that 15 seconds vortex mixing is sufficient to obtain microbial recoveries from the swab tip above 50%.

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available on the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests ass...

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of ...

Sampling from large networks represents a fundamental challenge for social network research. In this paper, we explore the sensitivity of different sampling techniques (node sampling , edge sampling, random walk sampling, and snowball sampling) on social networks with attributes. We consider the special case of networks (i) where we have one attribute with two values (e.g., male and female in the case of gender), (ii) where the size of the two groups is unequal (e.g., a male majority and a female minority), and (iii) where nodes with the same or different attribute value attract or repel each other (i.e., homophilic or heterophilic behavior). We evaluate the different sampling techniques with respect to conserving the position of nodes and the visibility of groups in such networks. Experiments are conducted both on synthetic and empirical social networks. Our results provide evidence that different network sampling techniques are highly sensitive with regard to capturing the expected centrality of nodes, and that their accuracy depends on relative group size differences and on the level of homophily that can be observed in the network. We conclude that uninformed sampling from social networks with attributes thus can significantly impair the ability of researchers to draw valid conclusions about the centrality of nodes and the visibility or invisibility of groups in social networks.

ISDM (Integrated Social Network Decision Models) is a methodology and tool kit which supports full planning cycles for SSTR, disaster relief and humanitarian missions in cross-cultural environments.  ISDM guides users in developing a decision model that enhances the efficient collection and analysis of model-related data, especially from non-cooperative populations. ISDM also guides users in useful analysis while seamlessly accounting for missing or incomplete data; finally reintegrating the findings into the decision model for understanding.
As part of our continued testing of ISDM, we conducted a one-day “flash” study at UCLA to verify that the entire system could function both rapidly and effectively as a single integrated unit.  The study involved one graduate student and several undergraduate students, none of whom had any prior exposure to the ISDM methodology or toolkit.  We presented them with a scenario in which an academic institution was greatly concerned about the pervasiveness of cheating on tests.  The scenario required the student team to address the problem of potential strategies, resources and inherent uncertainties by gathering data from students on campus.
The “flash” study dramatically demonstrated how rapidly ISDM could be used by untrained users as a complete process that begins with an uncertainty to be understood and ends with a confident decision based on robust analysis of empirical data.  The entire process for our “flash” study was completed in a fraction of a day!  The process steps comprised: (1) problem understanding; (2) survey generation; (3) data collection; (4) analysis; and (5) selecting an optimal strategy based on the new intelligence and enhanced understanding of the situation.

This paper proposes a stochastic programming model and solution algorithm for solving supply chain network design problems of a realistic scale. Existing approaches for these problems are either restricted to deterministic environments or can only address a modest number of scenarios for the uncertain problem parameters. Our solution methodology integrates a recently proposed sampling strategy, the sample average approximation (SAA) scheme, with an accelerated Benders decomposition algorithm to quickly compute high quality solutions to large-scale stochastic supply chain design problems with a huge (potentially infinite) number of scenarios. A computational study involving two real supply chain networks are presented to highlight the significance of the stochastic model as well as the efficiency of the proposed solution strategy.

Sediment traps were deployed on the Northwest Shelf (NWS) of Australia in November 1996, to determine fluxes of organic matter and inorganic elements from the photic zone to deeper waters in a transect extending from Exmouth Shelf to Exmouth Plateau. Infiltrex II water samplers collected particulate and dissolved organics from the water column near the trap sites. Surface sediments and sediment cores were also collected over the study region. Lipid biomarkers were used to determine the sources of organic carbon and its cycling processes on the NWS.Dry weight fluxes from the traps ranged from 124 to 616 mg m−2 day−1and particulate organic carbon (POC) fluxes ranged from 22 to 42 mg m−2 day−1. The biogenic lipids consisted of biomarkers indicative of marine zooplankton, phytoplankton and bacteria, plus traces of land plant markers. A large contribution of unresolved complex material (UCM), which is indicative of petroleum, was detected at four times the biogenic hydrocarbon flux at shallow stations, and up to seven times the biogenic hydrocarbon flux at the most offshore station.There is essentially no river input, and only trace aeolian-derived material to contribute to primary production on the NWS of Australia. Most of the organic matter produced are rapidly recycled in the water column and the small fraction of lipids that settle to the sediments is already partially degraded and undergoes further rapid degradation in the surface sediments. Natural oil seeps also provide utilisable organic carbon to the system. The production and vertical flux rates of organics determined in this study are comparable to those reported in studies of shallow traps in oceanic areas from long-term studies in the Arabian Sea, and other coastal margins such as the Bay of Biscay (France) and California (USA).In offshore areas, most “living” lipid materials passed through the GFF filters thus invalidating POC estimates based on high volume sampling. To adequately assess living (particulate) carbon, gentle filtration of low volume seawater samples is more accurate, as shown by this solid phase absorption study of individual lipid biomarkers.

A baseline survey of small and medium scale poultry enterprises were carried out in Enugu and Lagos States of Nigeria. The primary purpose of the study is to determine the prospects for the commercialization of the poultry industry in Nigeria. Multi-stage sampling method was employed in the selection of representative small and medium scale poultry farms and farmers from the two target states. Characteristics of both small and medium-scale poultry farms, baseline performance indicators as well as needs assessment of poultry farmers, among other information, were elicited and documented. It was established that the identified constraints, notwithstanding, small and medium scale poultry production holds great potential for commercialistion. It was recommended that there is the need for provision of gender-sensitive technologies (eg hatcheries, feed mills, processing equipment etc), formation of cooperatives by poultry farmers, public-private partnership, capacity building of poultry f...

Since Flint returned to its pre-crisis source of drinking water close to 25,000 water samples have been collected and tested for lead and copper in more than 10,000 residences. This paper presents the first analysis and time trend modeling of lead data, providing new insights about the impact of this intervention. The analysis started with geocoding all water lead levels (WLL) measured during an 11-month period following the return to the Detroit water supply. Each data was allocated to the corresponding tax parcel unit and linked to secondary datasets, such as the composition of service lines, year built, or census tract poverty level. Only data collected on residential parcels within the City limits were used in the analysis. One key feature of Flint data is their collection through two different sampling initiatives: (i) voluntary or homeowner-driven sampling whereby concerned citizens decided to acquire a testing kit and conduct sampling on their own (non-sentinel sites), and (ii) State-controlled sampling where data were collected bi-weekly at selected sites after training of residents by technical teams (sentinel sites). Temporal trends modeled from these two datasets were found to be statistically different with fewer sentinel data exceeding WLL thresholds ranging from 10 to 50 g/L. Even after adjusting for housing characteristics the odds ratio (OR) of measuring WLL above 15 g/L at non-sentinel sites is significantly greater than 1 (OR=1.480) and it increases with the threshold (OR= 2.055 for 50 g/L). Joinpoint regression showed that the city-wide percentage of WLL data above 15 g/L displayed four successive trends since the return to Detroit Water System. Despite the recent improvement in water quality, the culprit for differences between sampling programs needs to be identified as it impacts exposure assessment and might influence whether there is compliance or not with the Lead and Copper Rule.