352 research outputs found
Experimental Analysis of a Mobile Health System for Mood Disorders
No full textDepression is one of the leading causes of disability. Methods are needed to quantitatively classify emotions in order to better understand and treat mood disorders. This research proposes techniques to improve communication in body sensor network (BSN) that gathers data on the affective states of the patient. These BSNs can continuously monitor, discretely quantify, and classify a patient's depressive states. In addition, data on the patient's lifestyle can be correlated with his/her physiological conditions to identify how various stimuli trigger symptoms. This continuous stream of data is an improvement over a snapshot of localized symptoms that a doctor often collects during a medical examination. Our research first quantifies how the body interferes with communication in a BSN and detects a pattern between the line of sight of an embedded device and its reception rate. Then, a mathematical model of the data using linear programming techniques determines the optimal placement and number of sensors in a BSN to improve communication. Experimental results show that the optimal placement of embedded devices can reduce power cost up to 27% and reduce hardware costs up to 47%. This research brings researchers a step closer to continuous, real-time systemic monitoring that will allow one to analyze the dynamic human physiology and understand, diagnosis, and treat mood disorders
Battery-Aware Power Management Techniques for Wearable Haptic Nodes
No full textHaptic feedback provides an eective means of transferring
information through tactile stimulation. In this work we
look into the use of tactors for haptic feedback in body-worn
contexts where individuals are allowed to move around. In
this context it is crucial to design low power systems that al-
low the activation of multiple tactors at the same time with
limited battery power. We investigate how to minimize tac-
tor power consumption by tuning the characteristics of their
excitatory signal and present an activation policy to maxi-
mize the number of tactors that can be simultaneously pow-
ered by a battery under a tight peak current constraint.The
proposed optimizations reduce power consumption and al-
low a much higher number of simultaneously active tactors.
Furthermore, we provide a design strategy whereby design-
ers can tune the maximum number of simultaneously allowed
active tactors based on battery and system requirements
Dynamic Reconfiguration in Sensor Networks with Regenerative Energy Sources
No full textIn highly power constrained sensor networks, harvesting energy from the environment makes prolonged or even perpetual execution feasible. In such energy harvesting systems, energy sources are characterized as being regenerative. Regenerative energy sources fundamentally change the problem of power scheduling for embedded devices. Instead of the problem being one of maximizing the lifetime of the system given a total amount of energy, as in traditional battery powered devices, the problem becomes one of preventing energy depletion at any given time.
Coupling relatively computationally intensive applications, such as video processing applications, with the constrained FPGAs that are feasible on power constrained embedded systems, makes dynamic reconfiguration essential. It provides the speed comparable to a hardware implementation, but it also allows the dynamic reconfiguration to meet the multiple application needs of the system. Different applications can be loaded on the FPGA, as the system's needs change over time. The problem becomes how to schedule the dynamic reconfiguration to appropriately make use of the regenerative energy source, to ensure the proper availability of energy for the system over time.
In this paper, we present a methodology for carrying out dynamic reconfiguration for regenerative energy sources, based on statistical analysis of tasks and supply energy. The approach is evaluated through extensive simulations. Additionally, we have evaluated our implementation on our regenerative energy, dynamically reconfigurable prototype, known as the MicrelEye. Our approach is shown to miss 57.7% less deadlines on average than the current approach for reconfiguration with regenerative energy sources
Phosphorus optimization for simultaneous nitrate-contaminated groundwater treatment and algae biomass production using Ettlia sp.
No full textThe effects of phosphorus concentration on the cell growth, nutrient assimilation, photosynthetic parameters, and biomass recovery of Ettlia sp. were evaluated with batch experiments using groundwater, 50 mg/L of N-NO3 ？, and different concentrations of P-PO4 3？: 0.5, 2.5, 5, and 10 mg/L. The maximum biomass productivity and phosphorus removal rate were 0.2 g/L/d and 5.95 mg/L/d, respectively, with the highest phosphorus concentration of 10 mg/L. However, a phosphorus concentration of 5 mg/L (N:P = 10) was sufficient to ensure an effective nitrogen removal rate of 11 mg/L/d, maximum growth rate of 0.88/d, and biomass recovery of 0.72. The appropriate hydraulic retention time was considered as 4 days on a large scale to meet the effluent limitation demands of water. While nitrogen depletion had a significant effect on the photosynthetic parameters and ratio of chlorophyll a to dry cell weight during the stationary phase, the effect of phosphorus was negligible during the cultivation.
Hydrogen producer microalgae in interaction with hydrogen consumer denitrifiers as a novel strategy for nitrate removal from groundwater and biomass production
No full textLow-soluble and hazardous hydrogen gas which is used in current water denitrification processes was substituted by microalgae as a novel approach for biological nitrate removal. Bioremediation of nitrate-contaminated groundwater was evaluated by three batch cultures of hydrogen consumer denitrifiers (HCD), microalgae, and HCD-microalgae consortium at a similar inoculated total biomass of about 0.025 g. Microalgae contained three species of Chlorella vulgaris, Ettlia sp., and Chlamydomonas reinhardtii with an initial cell number of 60 × 104 cell/mL and subsequently C. vulgaris as dominant strain. High nitrate concentration of about 221 mg/L was entirely removed in hydrogen-injected denitrification bioreactor containing HCD in <24 h with N removal rate of 86 mg/L/d. However, it released sCOD into the environment and did not remove phosphorus efficiently. The consortium of HCD and microalgae could offset the lack of hydrogen for dissimilation of nitrate and produced N removal rate of 78 mg/L/d at lowest HCD/microalgae inoculated mass ratio of 0.26. Microalgae played the main role for assimilation of phosphorus and mitigation of the produced sCOD in both photobioreactors containing microalgae alone or their consortium with HCD. The maximum biomass productivity of 0.32 g/L/d and settling efficiency of 0.6 were obtained at highest inoculated HCD/microalgae mass ratio of 2.33. However, the performance of the consortium in terms of nitrate removal was better in lower ratio of HCD/microalgae, which can be applied in large-scale application.
The surveying of soil and groundwater pollution in a petroleum refinery and the potential of bioremediation for oil decontamination
No full textPublished online: 30 Oct 2013Soil contamination with crude oil is an important worldwide issue and the remediation of oil contaminated soils, sediments and groundwater is a major environmental challenge. In the target area of this survey, which is a petroleum refinery near Tehran, soil and groundwater pollution, and its source, contaminated area, and distribution of pollution were studied by means of different measurements. Oil content and volatile organic compounds were measured to determine soil and groundwater contamination. The investigations showed that the contamination of soil which is mainly silt and clay has reached to the groundwater which is around 20 m underground and formed an oily layer mainly containing gasoline, kerosene, and gas oil with different thicknesses in the whole area. The free oil existing over the groundwater table could be removed by physical ways such as pump and treat method but decontamination of soil is more complex. Due to long-lasting contamination of the field, the existence of accumulated indigenous microorganisms and the probable ability of them to effectively biodegrade pollutants by man-assisted interventions are expected. In this survey in order to clarify the contamination problem, some experiments have been done on the region soil and groundwater. Besides, the feasibility assessment of bioremediation in the investigated area is performed.M. Zargar, M. H. Sarrafzadeh, B. Taheri, and O. Tavakol
Optimization of the Production of Biosurfactant From Iranian Indigenous Bacteria for the Reduction of Surface Tension and Enhanced Oil Recovery
No full textThe optimum conditions for biosurfactant production by Iran's isolates were examined. The Taguchi method was used to identify nutritional requirements in the medium using four parameters; that is, carbon source, nitrogen, phosphorous, and salt concentrations. The use of whey, oil, and sucrose as carbon sources; NaCl as salt source; (Na2HPO4, NaH2PO 4) as phosphorous source; and (NH4)2SO 4 as nitrogen source was examined to determine bacteria optimum conditions. According to the Taguchi method using the sucrose source, the optimal conditions for Bacillus subtilis were 50 g/L NaCl, 13.53 g/L (Na 2HPO4, NaH2PO4), and 1 g/L (NH 4)2SO4; for Bacillus cereus they were 25 g/L NaCl, 13.53 g/L (Na2HPO4, NaH2PO4), and 1 g/L (NH4)2SO4; and for Pseudomonas putida they were 25 g/L NaCl, 13.53 g/L (Na2HPO4, NaH 2PO4), and 1 g/L (NH4)2SO 4. Oil displacement experiments in the micromodel at optimum conditions showed around 25% recovery of residual oil with added supernatant of Bacillus subtilis. Copyright © Taylor & Francis Group, LLC.H. Amani, M. Haghighi, M. H. Sarrafzadeh, M. R. Mehrnia, and F. Shahmirzae
Leveraging Social System Networks in Ubiquitous High-Data-Rate Health Systems
No full textSocial system networks with high data rates and limited storage will discard data if the system cannot connect and upload the data to a central server. We address the challenge of limited storage capacity in mobile health systems during network partitions with a heuristic that achieves efficiency in storage capacity by modifying the granularity of the medical data during long intercontact periods. Patterns in the connectivity, reception rate, distance, and location are extracted from the social system network and leveraged in the global algorithm and online heuristic. In the global algorithm, the stochastic nature of the data is modeled with maximum likelihood estimation based on the distribution of the reception rates. In the online heuristic, the correlation between system position and the reception rate is combined with patterns in human mobility to estimate the intracontact and intercontact time. The online heuristic performs well with a low data loss of 2.1%-6.1%
Biomass quantification and 3-D topography reconstruction of microalgal biofilms using digital image processing
No full textAn accurate and non-invasive technique for online biomass quantification of microbial attached growth is needed. In this research, image processing through Red-Green-Blue (RGB) analysis is used to assess biomass thickness from simple macroscopic images captured from microalgal biofilms by a digital camera. The results show that the green (G) vector in images of an Ettlia sp. biofilm can estimate the biomass concentration with R2 = 0.994 through an exponential correlation. Moreover, the R2 coefficient for the biofilm thickness measurement using the G vector is 0.973, which shows the high potential of this method. Furthermore, using the mathematical correlation between the G index and the biofilm thickness, it is possible to reconstruct the 3-D topography of a microalgal biofilm and to calculate the quantitative parameters, such as biomass yield and thickness, at every specific point of the biofilm. RGB analysis can easily determine the biofilm concentration and 3-D topography with satisfactory accuracy. This is promising technique for biofilm quantification and can be used in different applications, such as wastewater treatment by moving a bed biofilm reactor (MBBR), which was formerly possible only through sophisticated techniques.
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