HACMAC: A reliable human activity-based medium access control for implantable body sensor networks

Chronic care is an eminent application of implantable body sensor networks (IBSN). Performing physical activities such as walking, running, and sitting is unavoidable during the long-term monitoring of chronic-care patients. These physical activities cripple the radio frequency (RF) signal between the implanted sensor nodes. This is because various body postures shadow the RF signal. Although shadowing itself may be short, a prolonged activity will significantly increase the effect of the RF-shadowing. This effect dampens the communication between implantable sensor nodes and hence increases the chance of missing life-critical data. To overcome this problem, in this paper we propose a link quality-aware medium access control (MAC) protocol called HACMAC, which adapts the access mechanism during different human activities based on the wireless link-quality. Our simulation results show that compared with the access mechanism suggested by the IEEE 802.15.6 standard, the reliability of the wireless communication is increased using HACMAC even while transmitting at a strongly low transmission power of 25µW effective isotropic radiated power (EIRP) set by the IEEE 802.15.6 standar

Design of an efficient battery model using evolutionary algorithms.

Batteries play a vital role in current scenario of energy storage, even though many techniques of energy storage are available, since the time taken to start delivering the stored energy is very less. The battery life time depends upon its charging and discharging characteristics, which are in turn, depend on the internal parameters of battery. These parameters include resistance, capacitance and open circuit voltage. The amount of energy stored in the battery can be calculated by estimating these parameters. In this paper, an optimized model for Lithium ion batteries is presented using evolutionary algorithms to estimate the internal parameters of the battery over different charging and discharging rates. A sample EIG make, 2.5 V, 8 Ahr Lithium ion battery is modeled using two evolutionary algorithms such as genetic algorithm and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for different charging and discharging rates. The results of two algorithms are compared with the catalog values given by the manufacturer in order to identify the appropriate algorithm for battery modeling and validation. This paper concludes that battery characteristics obtained by CMA-ES algorithm match with the measured manufacturer characteristics

An integrated optimization approach to locate the D-STATCOM in power distribution system to reduce the power loss and total cost

The optimization problem with a single objective can obtain a single solution, called an optimal solution. It maximizes or minimizes the performance of a particular objective function to a given constraint. But, in the case of the multi-objective optimization, different objectives can be simultaneously optimized. Thus, this paper recommends a multi-objective optimization methodology for simultaneously perform the two objective functions such as resizing and optimal placement of Distributed Static Compensator (DSTATCOM) for reducing the power loss, total cost and enhancing the voltage profile. For these purposes, an integrated approach of two optimization algorithm called Multi-objective Ant Colony Optimization (MACO) and Bacterial Foraging Optimization Algorithm (BFOA) are used. The prime intention of this work is to bring down the power loss, total cost and enhance the voltage profile by placing the DSTATCOM device in an optimal location. Here, IEEE-30 and IEEE-69 bus systems are considered to appraise the recital of the recommended approach. Moreover, the effectiveness of the MACO-BFOA approach is evaluated and compared with other multi-objective algorithms. From this analysis, it is observed that when compared to these techniques, the proposed system provides the minimized power loss and total cost

Capacity Fade Modeling of Li-Ion Battery using Evolutionary Algorithm

Renewable sources are seasonal and cannot be considered as available energy source as their generation varies with time. The insufficient forecasting techniques lead to thought of storage of energy. Even though many techniques of energy storage are available, batteries play a vital role as the time taken to start delivering the stored energy is very less. The life period of the battery depends upon the charging and discharging characteristics which in turn depend on the internal parameters such as life period, charge rate, discharge rate of the battery. The energy stored in the battery can be calculated by finding these parameters. In this paper these parameters are estimated for a Sony lithium ion battery by evolutionary algorithm CMA-ES under different Charging and discharging rates. As the batteries are charged and discharged there is capacity loss in the battery. This loss is modelled by modified Arrhenius equation on practical conditions. Capacity loss of the sample battery is modelled for five different cycles starting from 50th cycle to 100th cycle in an interval of 10 cycles. The results are validated with those of manufacturer catalogue. The optimized battery capacity loss are found to coincide with the measured values

Water Network Optimization with Wastewater Regeneration Models

The conventional water network synthesis approach greatly simplifies wastewater treatment units by using fixed recoveries, creating a gap for their applicability to industrial processes. This work describes a unifying approach combining various technologies capable of removing all the major types of contaminants through the use of more realistic models. The following improvements are made over the typical superstructure-based water network models. First, unit-specific shortcut models are developed in place of the fixed contaminant removal model to describe contaminant mass transfer in wastewater treatment units. Shortcut wastewater treatment cost functions are also incorporated into the model. In addition, uncertainty in mass load of contaminants is considered to account for the range of operating conditions. Furthermore, the superstructure is modified to accommodate realistic potential structures. We present a modified Lagrangean-based decomposition algorithm in order to solve the resulting nonconvex mixed-integer nonlinear programming (MINLP) problem efficiently. Several examples are presented to illustrate the effectiveness and limitations of the algorithm for obtaining the global optimal solutions.The authors would like to acknowledge financial support from the National Science Foundation for financial support under grant CBET-1437668, the program “Estancias de movilidad en el extranjero “Jose Castillejo” para jóvenes doctores” (JC2011-0051) of the Spanish Ministerio de Educación, and from the University of Alicante (GRE11-19)

Biocontrol Agents Induce Disease Resistance in Phyllanthus niruri Linn against Damping-Off Disease Caused by Rhizoctonia solani

Five isolates each of Trichoderma viride and Pseudomonas fluorescens and four isolates of Bacillus subtilis were evaluated for their ability to control Rhizoctonia solani, the causal agent of damping off of Phyllanthus niruri. Among the isolates tested, TVUV10 (T. viride), PFMMP (P. fluorescens) and BSG3 (B. subtilis) showed maximum in vitro inhibition of mycelial growth of R. solani. Isolate PFMMP was also very effective in reducing disease incidence in greenhouse conditions. The effective isolates were evaluated for their ability to induce defense reactions in P. niruri plants. Earlier and increased activity of phenylalanine ammonia lyase, peroxidase, polyphenoloxidase and total phenolics were observed in the biocontrol-agent pretreated P. niruri plants challenged with R. solani. Isolate PFMMP caused early and increased synthesis of all defense related enzymes and total phenol. The present study showed that isolates TVUV10, PFMMP and BSG3 of T. viride, P. fluorescens and B. subtilis respectively are good candidates for the control of R. solani in P. niruri

The impacts of urban air pollution on Malaysian traffic police: A framework for evaluation of real-time monitoring system on its usability

The respiratory health of Malaysian Traffic Police has been compromised by working in heavy traffic and congested junctions with bad air for long hours. A wireless outdoor individual exposure device is vital to track their exposure, however, the efficacy of the system remains uncertain. While existing techniques exist to examine the efficacy of such system, there is a lack of methodology for engaging multiple assessment methods to evaluate the degree of user experience. This paper aims to propose a methodological framework tool for a quantitative evaluation of the wireless outdoor individual exposure indicator system prototype. A systematic search was conducted in major electronic databases (MEDLINE, Web of Science, Google), grey literature sources and all relevant data in the field. A three-stage framework consisting of simulation real-time monitoring, in-field testing, and usability testing is assembled. The three-stage framework proposed serves as a generic approach for evaluating the prototype with the purpose of tracking individual outdoor exposure. The method is capable of describing the complete evaluation process, from the accuracy and performance of the sensor to the extent of the end-user experience. Using the three-stage approach, future researchers may be able to create a monitoring system that is relevant to their needs

Large Proteins Have a Great Tendency to Aggregate but a Low Propensity to Form Amyloid Fibrils

The assembly of soluble proteins into ordered fibrillar aggregates with cross-β structure is an essential event of many human diseases. The polypeptides undergoing aggregation are generally small in size. To explore if the small size is a primary determinant for the formation of amyloids under pathological conditions we have created two databases of proteins, forming amyloid-related and non-amyloid deposits in human diseases, respectively. The size distributions of the two protein populations are well separated, with the systems forming non-amyloid deposits appearing significantly larger. We have then investigated the propensity of the 486-residue hexokinase-B from Saccharomyces cerevisiae (YHKB) to form amyloid-like fibrils in vitro. This size is intermediate between the size distributions of amyloid and non-amyloid forming proteins. Aggregation was induced under conditions known to be most effective for amyloid formation by normally globular proteins: (i) low pH with salts, (ii) pH 5.5 with trifluoroethanol. In both situations YHKB aggregated very rapidly into species with significant β-sheet structure, as detected using circular dichroism and X-ray diffraction, but a weak Thioflavin T and Congo red binding. Moreover, atomic force microscopy indicated a morphology distinct from typical amyloid fibrils. Both types of aggregates were cytotoxic to human neuroblastoma cells, as indicated by the MTT assay. This analysis indicates that large proteins have a high tendency to form toxic aggregates, but low propensity to form regular amyloid in vivo and that such a behavior is intrinsically determined by the size of the protein, as suggested by the in vitro analysis of our sample protein