A Mobile Cloud-Based eHealth Scheme

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.     

Seismic safety of lifelines—an optimum design method

Lifeline systems are vulnerable to two types of hazards arising from potential earthquake sources. These are the hazard of a fault-rupture strike on elements of a lifeline system and the hazard of overstress induced in different elements of the system because of the ground vibration. An optimum design method is presented in this paper for the design of a lifeline system for a maximum accepted probability of failure because of any of the two modes of failure. The method may be used to determine an optimum path between a number of fixed points which represent supply or demand stations in the system.     

Sustainable Basin-Scale Water Allocation with Hydrologic State-Dependent Multi-Reservoir Operation Rules

This study extends the PSO-MODSIM model, integrating particle swarm optimization (PSO) algorithm and MODISM river basin decision support system (DSS) to determine optimal basin-scale water allocation, in two aspects. The first is deriving hydrologic state-dependent (conditional) operating rules to better account for drought and high-flow periods, and the second is direct, explicit consideration of sustainability criteria in the model’s formulation to have a better efficiency in basin-scale water allocation. Under conditional operating rules, the operational parameters of reservoir target storage levels and their priority rankings were conditioned on the hydrologic state of the system in a priority-based water allocation scheme. The role of conditional operating rules and policies were evaluated by comparing water shortages associated with objective function values under unconditional and conditional operating rules. Optimal basin-scale water allocation was then evaluated by incorporating reliability, vulnerability, reversibility and equity sustainability indices into the PSO objective function. The extended model was applied for water allocation in the Atrak River Basin, Iran. Results indicated improved distribution of water shortages by about 7.5% using conditional operating rules distinguishing dry, normal and wet hydrologic states. Alternative solutions with nearly identical objective function values were found with sustainability indices included in the model.     

Green synthesis of silver nanoparticles using Glaucium corniculatum (L.) Curtis extract and evaluation of its antibacterial activity

The metal nanoparticles, due to interesting features such as electrical, optical, chemical and magnetic properties, have been investigated repeatedly. Also, the mentioned nanoparticles have specific uses in terms of their antibacterial activity. The biosynthesis method is more appropriate than the chemical method for producing the nanoparticles because it does not need any special facilities; it is also economically affordable. In the current study, the silver nanoparticles (AgNPs) were obtained by using a very simple and low‐cost method via Glaucium corniculatum (L.) Curtis plant extract. The characteristics of the AgNPs were investigated using techniques including: X‐ray diffraction, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy. The SEM and TEM images showed that the nanoparticles had a spherical shape, and the mean diameter of them was 53.7 and 45 nm, respectively. The results of the disc diffusion test used for measuring the anti‐bacterial activity of the synthesised nanoparticles indicated that the formed nanoparticles possessed a suitable anti‐bacterial activity.Inspec keywords: silver, nanoparticles, antibacterial activity, nanomedicine, nanofabrication, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectraOther keywords: green synthesis, silver nanoparticles, Glaucium corniculatum Curtis extract, antibacterial activity, metal nanoparticles, biosynthesis method, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, SEM, TEM, spherical shape, disc diffusion test, Ag     

Treatability of Alternative Fuel Oxygenates Using Advanced Oxidation, Air Stripping, and Carbon Adsorption

Methyl tert-butyl ether (MTBE) is a gasoline oxygenate that has become a significant threat to groundwater supplies across the United States. Due to its physiochemical properties it has proven difficult and costly to remove from contaminated sites. This study was conducted to determine whether the alternative oxygenates (AO)—diisopropyl ether (DIPE), ethyltert-butyl ether (ETBE), tert-amyl methyl ether (TAME), tert-butyl alcohol (TBA), and ethanol (EtOH)—present a more efficient and less costly option from a remediation standpoint. Air stripping, carbon adsorption, and ultraviolet/H2O2 and O3/H2O2 advanced oxidation processes were examined at pilot scale to develop design parameters from which technical and economic comparisons were made for each alternative oxygenate versus MTBE. The experimental results showed that the ether AOs—DIPE, TAME, and ETBE—were each more efficiently and more economically treated than MTBE. The alternative alcohol oxygenates—TBA and EtOH—were less efficiently and less economically treated by the processes studied. The paper details the effects of primary process parameters and properties of individual oxygenates on process efficiency.     

Gas holdup in two phase gas–liquid and three phase gas–liquid–solid production and transportation

The gas holdup is an important parameter that is needed for design and development of surface facilities and transportation pipelines in the field of petroleum engineering. There is no general model for prediction of this parameter in different systems and under different conditions. As a result, development of accurate and general models for prediction of this parameter in various situations is of great importance. This study presents new experimental gas holdup data in the kerosene+CO₂ and kerosene+N₂ systems. The experimental data were measured by using a bubble column setup. Moreover, a computer-based model namely PSO-ANFIS model is also developed for prediction of the gas holdup in different systems. A total of 818 experimental gas holdup data in various systems were utilized including the newly measured experimental data in the present work as well as experimental data from several published works in the literature. Results showed that the developed PSO-ANFIS model is accurate for prediction of experimental data with an R² value of 0.998 and average absolute relative deviation (AARD%) of 3.4%.     

Parkinson’s Disease Detection Using Biogeography-Based Optimization

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.     

A translinear principle based low-power high-precision RMS-to-DC converter in CMOS technology

Analog Integrated Circuits and Signal Processing - In the present study, a low-power high-precision current-mode CMOS true root mean square (RMS)-to-DC converter is presented based on the...     

User-sensor mutual authenticated key establishment scheme for critical applications in wireless sensor networks

Wireless Networks - Authenticated key establishment schemes allow the participants to authenticate each other and establish a secure session key among them. These schemes play an important role in...     

Multi-objective Phasor Measurement Unit Placement in Electric Power Networks: Integer Linear Programming Formulation

A multi-objective optimal phasor measurement unit placement model using integer linear programming is presented in this article. The proposed model simultaneously optimizes two objectives, i.e., minimization of phasor measurement unit numbers and maximization of measurement redundancy. To calculate the redundancy criteria, the single-line outage and the phasor measurement unit loss are considered simultaneously. A linear formulation is presented for both objective functions. Also herein, to address conflicting attributes and identify Pareto optimal solutions of the multi-objective optimal phasor measurement unit placement problem, a new multi-objective mathematical programming method is proposed. Finally, a new index, i.e., minimum distance to utopia point, is implemented to select the most preferred solution among the available Pareto front based options on the goal to achieve judicious decision makers. Two test systems, i.e., a modified 9-bus and an IEEE 118-bus test systems, are used to illustrate the effectiveness of the proposed framework.