Building a microscope for the data center

Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolutionof the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center andwith them, _and opportunities to optimize energy consumption. Havinga high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

A Spatial Econometrics Analysis for Road Accidents in Lisbon

This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation on data is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms. In all the cases no spatial autocorrelation was detected.

The AIDS epidemic in the Amazon region: a spatial case-control study in Rondonia, Brazil

OBJECTIVE To analyze spatial changes in the risk of AIDS and the relationship between AIDS incidence and socioeconomic variables in the state of Rondonia, Amazon region. METHODS A spatial, population case-control study in Rondonia, Brazil, based on 1,780 cases reported to the Epidemiological Surveillance System and controls based on demographic data from 1987 to 2006. The cases were grouped into five consecutive four-year periods. A generalized additive model was adjusted to the data; the dependent variable was the status of the individuals (case or control), and the independent variables were a bi-dimensional spline of the geographic coordinates and some municipality-level socioeconomic variables. The observed values of the Moran’s I test were compared to a reference distribution of values generated under conditions of spatial randomness. RESULTS AIDS risk shows a marked spatial and temporal pattern. The disease incidence is related to socioeconomic variables at the municipal level in Rondônia, such as urbanization and human capital. The highest incidence rates of AIDS are in municipalities along the BR-364 highway and calculations of the Moran’s I test show positive spatial correlation associated with proximity of the municipality to the highway in the third and fourth periods (p = 0.05). CONCLUSIONS Incidence of the disease is higher in municipalities of greater economic wealth and urbanization, and in those municipalities bisected by Rondônia’s main roads. The rapid development associated with the opening up of once remote regions may be accompanied by an increase in these risks to health.

Beach sand and the potential for infectious disease transmission: observations and recommendations

Recent studies suggest that sand can serve as a vehicle for exposure of humans to pathogens at beach sites, resulting in increased health risks. Sampling for microorganisms in sand should therefore be considered for inclusion in regulatory programmes aimed at protecting recreational beach users from infectious disease. Here, we review the literature on pathogen levels in beach sand, and their potential for affecting human health. In an effort to provide specific recommendations for sand sampling programmes, we outline published guidelines for beach monitoring programmes, which are currently focused exclusively on measuring microbial levels in water. We also provide background on spatial distribution and temporal characteristics of microbes in sand, as these factors influence sampling programmes. First steps toward establishing a sand sampling programme include identifying appropriate beach sites and use of initial sanitary assessments to refine site selection. A tiered approach is recommended for monitoring. This approach would include the analysis of samples from many sites for faecal indicator organisms and other conventional analytes, while testing for specific pathogens and unconventional indicators is reserved for high-risk sites. Given the diversity of microbes found in sand, studies are urgently needed to identify the most significant aetiological agent of disease and to relate microbial measurements in sand to human health risk.

Spatial study of homicide rates in the state of Bahia, Brazil, 1996-2010

OBJECTIVE To analyze the spatial distribution of homicide mortality in the state of Bahia, Northeastern Brazil. METHODS Ecological study of the 15 to 39-year old male population in the state of Bahia in the period 1996-2010. Data from the Mortality Information System, relating to homicide (X85-Y09) and population estimates from the Brazilian Institute of Geography and Statistics were used. The existence of spatial correlation, the presence of clusters and critical areas of the event studied were analyzed using Moran’s I Global and Local indices. RESULTS A non-random spatial pattern was observed in the distribution of rates, as was the presence of three clusters, the first in the north health district, the second in the eastern region, and the third cluster included townships in the south and the far south of Bahia. CONCLUSIONS The homicide mortality in the three different critical areas requires further studies that consider the socioeconomic, cultural and environmental characteristics in order to guide specific preventive and interventionist practices.

Temporal trends and spatial distribution of unsafe abortion in Brazil, 1996-2012

OBJECTIVE To analyze temporal trends and distribution patterns of unsafe abortion in Brazil. METHODS Ecological study based on records of hospital admissions of women due to abortion in Brazil between 1996 and 2012, obtained from the Hospital Information System of the Ministry of Health. We estimated the number of unsafe abortions stratified by place of residence, using indirect estimate techniques. The following indicators were calculated: ratio of unsafe abortions/100 live births and rate of unsafe abortion/1,000 women of childbearing age. We analyzed temporal trends through polynomial regression and spatial distribution using municipalities as the unit of analysis. RESULTS In the study period, a total of 4,007,327 hospital admissions due to abortions were recorded in Brazil. We estimated a total of 16,905,911 unsafe abortions in the country, with an annual mean of 994,465 abortions (mean unsafe abortion rate: 17.0 abortions/1,000 women of childbearing age; ratio of unsafe abortions: 33.2/100 live births). Unsafe abortion presented a declining trend at national level (R2: 94.0%, p < 0.001), with unequal patterns between regions. There was a significant reduction of unsafe abortion in the Northeast (R2: 93.0%, p < 0.001), Southeast (R2: 92.0%, p < 0.001) and Central-West regions (R2: 64.0%, p < 0.001), whereas the North (R2: 39.0%, p = 0.030) presented an increase, and the South (R2: 22.0%, p = 0.340) remained stable. Spatial analysis identified the presence of clusters of municipalities with high values for unsafe abortion, located mainly in states of the North, Northeast and Southeast Regions. CONCLUSIONS Unsafe abortion remains a public health problem in Brazil, with marked regional differences, mainly concentrated in the socioeconomically disadvantaged regions of the country. Qualification of attention to women’s health, especially to reproductive aspects and attention to pre- and post-abortion processes, are necessary and urgent strategies to be implemented in the country.

Temporal evolution and spatial distribution of maternal death

OBJECTIVE To analyze the temporal evolution of maternal mortality and its spatial distribution.METHODS Ecological study with a sample made up of 845 maternal deaths in women between 10 and 49 years, registered from 1999 to 2008 in the state of Rio Grande do Sul, Southern Brazil. Data were obtained from Information System on Mortality of Ministry of Health. The maternal mortality ratio and the specific maternal mortality ratio were calculated from records, and analyzed by the Poisson regression model. In the spatial distribution, three maps of the state were built with the rates in the geographical macro-regions, in 1999, 2003, and 2008.RESULTS There was an increase of 2.0% in the period of ten years (95%CI 1.00;1.04; p = 0.01), with no significant change in the magnitude of the maternal mortality ratio. The Serra macro-region presented the highest maternal mortality ratio (1.15, 95%CI 1.08;1.21; p < 0.001). Most deaths in Rio Grande do Sul were of white women over 40 years, with a lower level of education. The time of delivery/abortion and postpartum are times of increased maternal risk, with a greater negative impact of direct causes such as hypertension and bleeding.CONCLUSIONS The lack of improvement in maternal mortality ratio indicates that public policies had no impact on women’s reproductive and maternal health. It is needed to qualify the attention to women’s health, especially in the prenatal period, seeking to identify and prevent risk factors, as a strategy of reducing maternal death.

Indoor location using fingerprinting and fuzzy logic

Indoor location systems cannot rely on technologies such as GPS (Global Positioning System) to determine the position of a mobile terminal, because its signals are blocked by obstacles such as walls, ceilings, roofs, etc. In such environments. The use of alternative techniques, such as the use of wireless networks, should be considered. The location estimation is made by measuring and analysing one of the parameters of the wireless signal, usually the received power. One of the techniques used to estimate the locations using wireless networks is fingerprinting. This technique comprises two phases: in the first phase data is collected from the scenario and stored in a database; the second phase consists in determining the location of the mobile node by comparing the data collected from the wireless transceiver with the data previously stored in the database. In this paper an approach for localisation using fingerprinting based on Fuzzy Logic and pattern searching is presented. The performance of the proposed approach is compared with the performance of classic methods, and it presents an improvement between 10.24% and 49.43%, depending on the mobile node and the Fuzzy Logic parameters.ł

RSS and LEA adaptation for indoor location using fingerprinting

Fingerprinting is an indoor location technique, based on wireless networks, where data stored during the offline phase is compared with data collected by the mobile device during the online phase. In most of the real-life scenarios, the mobile node used throughout the offline phase is different from the mobile nodes that will be used during the online phase. This means that there might be very significant differences between the Received Signal Strength values acquired by the mobile node and the ones stored in the Fingerprinting Map. As a consequence, this difference between RSS values might contribute to increase the location estimation error. One possible solution to minimize these differences is to adapt the RSS values, acquired during the online phase, before sending them to the Location Estimation Algorithm. Also the internal parameters of the Location Estimation Algorithms, for example the weights of the Weighted k-Nearest Neighbour, might need to be tuned for every type of terminal. This paper focuses both approaches, using Direct Search optimization methods to adapt the Received Signal Strength and to tune the Location Estimation Algorithm parameters. As a result it was possible to decrease the location estimation error originally obtained without any calibration procedure.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Spatial operators for collaborative map handling

MSC Dissertation in Computer Engineering

Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina

OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors.METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed.RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070).CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.

Optimal location of supports in beam structures using genetic algorithms

Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed. © 2014 IEEE.

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

Optimal location of the workpiece in a PKM-based machining robotic cell

Most machining tasks require high accuracy and are carried out by dedicated machine-tools. On the other hand, traditional robots are flexible and easy to program, but they are rather inaccurate for certain tasks. Parallel kinematic robots could combine the accuracy and flexibility that are usually needed in machining operations. Achieving this goal requires proper design of the parallel robot. In this chapter, a multi-objective particle swarm optimization algorithm is used to optimize the structure of a parallel robot according to specific criteria. Afterwards, for a chosen optimal structure, the best location of the workpiece with respect to the robot, in a machining robotic cell, is analyzed based on the power consumed by the manipulator during the machining process.