Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes

The advent of services such as cloud computing, social networks and e-commerce has led to an increased demand for computer resources from data centers. Prominent issues for data center designers are sustainability, cost, and dependability, which are each significantly affected by the redundant architectures required to support these services. Within this context, models are important tools for designers when attempting to quantify these issues before implementing the final architecture. This paper proposes a set of models for the integrated quantification of the sustainability impact, cost, and dependability of data center power and cooling infrastructures. This is achieved with the support of an environment called ASTRO. The approach taken to perform the system dependability evaluation employs a hybrid modeling strategy which recognizes the advantages of both stochastic Petri nets and reliability block diagrams. Additionally, an energy flow model is proposed to estimate the environmental impact and cost of data center architectures whilst respecting the energy constraints of each device. This work also presents a case study which analyzes the environmental impact and dependability metrics as well as the operational energy cost of real-world data center power and cooling architectures within the context of the energy mixes of the US and Brazil.     

Performability modeling of electronic funds transfer systems

Dependability is a paramount requirement for computer systems, since failures can cause a serious economic impact and jeopardize profitability. This paper considers electronic funds transfer (EFT) systems, where computing resources must be used efficiently in order to achieve high availability and reliability for a high quality of the offered service. The design of fault-tolerant computer systems requires their model-based performability evaluation. A stochastic Petri net model of EFT architecture and behavior is presented to evaluate the impact of availability and reliability issues on computational resources. An industrial case study shows the practical usability of the proposed models and techniques.     

Daily Reference Evapotranspiration for Hyper-Arid to Moist Sub-Humid Climates in Inner Mongolia,China: II. Trends of ET<Subscript>o</Subscript> and Weather Variables and Related Spatial Patterns

This study focuses on assessing trends of reference evapotranspiration (ET_o) considering aridity. Weather data sets of 54–62 years of Inner Mongolia, a Chinese Province where climate varies from hyper-arid in the West to wet sub-humid in the East, were used. Trends were analyzed for ET_o computed with the FAO Penman-Monteith method (PM-ET_o) using full data sets of maximum and minimum temperature (T_max and T_min), sunshine duration (SD) used to compute net radiation, relative humidity (RH) and wind speed (WS). Trends were also assessed for ET_o computed with the Hargreaves-Samani temperature eq. (ET_{o HS}) and the Penman-Monteith equation with temperature estimates of solar radiation and actual vapour pressure (ET_{o PMT}). In addition, trends relative to T_max, T_min, SD, RH and WS were assessed. Trends for PM-ET_o show to vary with aridity, with decreasing trends in the areas marked by aridity in the West and increased trends in less arid and sub-humid areas in the East. The detected trends are well explained by the trends in weather variables which consist of large increasing trends of T_max and T_min and of decreasing trends for SD, RH and WS. Therefore, negative trends of ET_o occur where impacts of increases in temperature and decreases in RH are smaller than impacts of declining SD and WS; otherwise, when warming influences are larger it results a positive trend for ET_o. Trends were coherent when considering seasonality influences. Contrarily, results for the temperature methods, ET_{o PMT} and ET_{o HS,} always identified increased trends for ET_o due to warming effects. These results show that it is inappropriate to assess ET_o trends when using simplified temperature methods.     

Prevalence, knowledge, treatment and control of arterial hypertension in Oporto, Portugal

The aim of this study was to assess the prevalence, awareness, treatment and control of hypertension among subjects above the age of 39 years living in the urban area of Oporto, Portugal. One hundred and seventy seven individuals from the community were selected by random digit dialing. Each subject was asked about his/her personal history of hypertension, antihypertensive treatment and had his/her blood pressure measured. The prevalence of hypertension was 57.1%, defined by systolic blood pressure (SBP) > or = 140 mm Hg and/or diastolic blood pressure (DBP) > or = 90 mm Hg and/or administration of current the antihypertensive medication. If the values defining hypertension were SBP > or = 160 mm Hg, and DBP > or = 95 mm Hg the prevalence would be 37.9%. The overall prevalence of hypertension was higher in females, but a slightly higher non significant value was found in males in the fifth and sixth decades. Among hypertensives, 62.7% were aware of their condition, 56.7% were treated, 84.2% of hypertensives treated were controlled (SBP < 160 mm Hg and DBP < 95 mm Hg) and 44.7% were very well controlled (SBP < 140 mm Hg and DBP < 90 mm Hg). The question "Are you hypertensive?" had a sensitivity of 62.7%, a specificity of 83.6% and an accuracy of 75.7%. In the preliminary results of this study of an urban population with a high prevalence of hypertension, the awareness of hypertension is similar to that described in the United States of America twenty years ago, the percentage of hypertensives treated is similar to the American percentage fifteen years ago and the percentage of hypertensives treated and controlled is close to the current American percentage.     

MineCap: super incremental learning for detecting and blocking cryptocurrency mining on software-defined networking

Annals of Telecommunications - Covert mining of cryptocurrency implies the use of valuable computing resources and high energy consumption. In this paper, we propose MineCap, a dynamic online...     

Flexible Wearable Pre-fractal Antennas for Personal High-Temperature Monitoring

Wireless Personal Communications - This paper proposed a new flexible and wearable antennas design based on teragon pre-fractal geometry until the third level, for monitoring high-temperature in...     

Availability and reliability modeling of VM migration as rejuvenation on a system under varying workload

Software Quality Journal - Cloud computing serves as a platform for diverse types of applications, from low-priority to critical. Some of these applications require high levels of system...     

Comparing SPI and RDI Applied at Local Scale as Influenced by Climate

Drought and wetness events were studied in the Northeast Algeria with SPI and RDI. The study area includes a variety of climatic conditions, ranging from humid in the North, close to the Mediterranean Sea, to arid in the South, near the Sahara Desert. SPI only uses precipitation data while RDI uses a ratio between precipitation and potential evapotranspiration (PET). The latter was computed with the Thornthwaite equation, thus using temperature data only. Monthly precipitation data were obtained from 123 rainfall stations and monthly temperature data were obtained from CFSR reanalysis gridded temperature data. Both data sets cover the period 1979–80 to 2013–14. Using ordinary kriging, the gridded temperature data was interpolated to all the locations having precipitation data, thus providing to compute SPI and RDI with the same observed rainfall data for the 3-, 6- and 12-month time scales. SPI and RDI were therefore compared at station level and results and have shown that both indices revealed more sensitive to drought when applied in the semi-arid and arid zones. Differently, more wetness events were detected by RDI in the more humid locations. Comparing both indices, they show a coherent and similar behavior, however RDI shows smaller differences among climate zones and time-scales, which is an advantage relative to the SPI and is likely due to including PET in RDI.     

Appearance Modelling of Living Human Tissues

The visual fidelity of realistic renderings in Computer Graphics depends fundamentally upon how we model the appearance of objects resulting from the interaction between light and matter reaching the eye. In this paper, we survey the research addressing appearance modelling of living human tissue. Among the many classes of natural materials already researched in Computer Graphics, living human tissues such as blood and skin have recently seen an increase in attention from graphics research. There is already an incipient but substantial body of literature on this topic, but we also lack a structured review as presented here. We introduce a classification for the approaches using the four types of human tissues as classifiers. We show a growing trend of solutions that use first principles from Physics and Biology as fundamental knowledge upon which the models are built. The organic quality of visual results provided by these Biophysical approaches is mainly determined by the optical properties of biophysical components interacting with light. Beyond just picture making, these models can be used in predictive simulations, with the potential for impact in many other areas.     

Characterization of organic material in coal by proton-decoupled 13C nuclear magnetic resonance with magic-angle spinning

¹³C n.m.r. spectra have been obtained on ten solid coal samples of various types and on three coal-derived materials, using high-power proton decoupling, cross polarization and magic-angle spinning, and provide valuable information on the carbon distribution between aromatic and non-aromatic structures in the sample. Apparent carbon aromaticities, f_a′, have been determined and have been correlated with H/C ratios and as one factor in fuel values. Both solvent refining and reverse combustion (see introduction) are found to increase the aromatic fraction. These techniques should be very useful in characterizing and optimizing coal-conversion processes.