Biometric identification using fingertip electrocardiogram signals

In this research work, we present a newly fingertip electrocardiogram (ECG) data acquisition device capable of recording the lead-1 ECG signal through the right- and left-hand thumb fingers. The proposed device is high-sensitive, dry-contact, portable, user-friendly, inexpensive, and does not require using conventional components which are cumbersome and irritating such as wet adhesive Ag/AgCl electrodes. One of the other advantages of this device is to make it possible to record and use the lead-1 ECG signal easily in any condition and anywhere incorporating with any platform to use for advanced applications such as biometric recognition and clinical diagnostics. Furthermore, we proposed a biometric identification method based on combining autocorrelation and discrete cosine transform-based features, cepstral features, and QRS beat information. The proposed method was evaluated on three fingertip ECG signal databases recorded by utilizing the proposed device. The experimental results demonstrate that the proposed biometric identification method achieves person recognition rate values of 100% (30 out of 30), 100\(\%\) (45 out of 45), and 98.33\(\%\) (59 out of 60) for 30, 45, and 60 subjects, respectively.     

Approximation algorithms in partitioning real-time tasks with replications

Today is an era where multiprocessor technology plays a major role in designs of modern computer architecture. While multiprocessor systems offer extra computing power, it also opens a new range of opportunities to improve fault-robustness. This paper focuses on a problem of achieving fault-tolerance using replications in real-time, multiprocessor systems. In the problem, multiple replicas, or copies, of a computing task are executed on distinct processors to resist potential processor failures and computing faults. Two greedy, approximation heuristics, named Worst Fit Increasing K-Replication and First Fit Increasing K-Replication, are studied to maximise the number of real-time tasks assigned on a system with identical processors, respecting to the tasks’ replicating and timely requirements. Worst case performance is analysed by using an approximation ratio between the algorithms and an optimal solution. We mathematically prove that the ratios of using both algorithms are infinitely close to 2. Simulations are performed on a large set of testing cases which can be used to bring to light the average performance of using the algorithms in practice. The results show that both heuristic algorithms provide simple but fast and effective solutions to solve the problem.     

Synthesis and characterization of 2‐hydroxyethylmethacrylate/2‐(3‐indol‐yl)ethylmethacrylamide‐based novel hydrogels as drug carrier with in vitro antibacterial properties

In this study, a new cationic monomer 2‐(3‐indol‐yl)ethylmethacrylamide (IEMA) derived from tryptamine was synthesized in a single step and characterized by Fourier transform infrared (FTIR), ¹H‐NMR, and ¹³C‐NMR. Then, one‐step preparation of novel poly[2‐hydroxyethylmethacrylate‐c‐2‐(3‐indol‐yl)ethylmethacrylamide], or p(HEMA‐c‐IEMA), copolymeric hydrogels has been performed successfully with IEMA and 2‐hydroxyethylmethacrylate (HEMA) as monomers using free radical aqueous polymerization. The hydrogels were characterized with scanning electron microscopy, FTIR, elemental analysis, thermogravimetric analysis, and texture profile analysis instruments. p(HEMA‐c‐IEMA) hydrogels were used for swelling, diffusion, drug release, and antibacterial activity studies. The drug‐release behavior of the hydrogels was determined as a function of time at 37 °C in pH 1.2 and 7.2. The swelling and drug‐release studies showed that an increased IEMA amount caused a higher increase in swelling and drug‐release values. Additionally, zero‐order, first‐order, and Higuchi equation kinetic models were applied to the drug‐release data, and the data fit well in the Higuchi model, and the Peppas power‐law model was applied to the release mechanism. Finally, the antibacterial activities of the hydrogels were screened against Gram‐positive bacteria (Bacillus cereus and Staphylococcus aureus) and Gram‐negative bacteria (Escherichia coli and Salmonella typhimurium). © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45550.     

Analysis and modeling of drying behavior of knitted textile materials

Drying properties of textiles in summer and/or after any kind of physical activity resulted in sweating is of great importance for garments with high clothing comfort. This study analyzes the drying behavior of knitted fabrics produced from various fibers at different ambient air conditions. Drying kinetics and modeling of fabrics dried in standard environmental conditions were investigated in the first part. Polyester and lyocell fabrics were found to be the fastest drying samples. A two-stage modeling that is a combination of linear approach and thin-layer equations was used, and the best fitted equation was found to be the logarithmic one. The two-stage model was also proved to predict the drying rate. The second part included the effects of ambient humidity on drying times and rates. Drying time of polyester and polyester blended fabrics was affected by the increase in the humidity to a great extent. Furthermore, a quadratic function was found to be highly correlated with the computed data, so it was proposed to define the drying behavior by ambient air humidity and drying time.     

Blood glucose level prediction for diabetes based on modified fuzzy time series and particle swarm optimization

Blood glucose control is an essential goal for the patients who have Type‐1 diabetes (T1D). The prediction of the blood glucose levels for the next 30‐minute is crucial. If the predicted blood glucose level is in the critical ranges, and these predictions can be known in advance, then the patients can take the necessary cautions to prevent from it. In this article, we propose a modified fuzzy particle swarm optimization algorithm for the prediction of blood glucose levels of 30‐minute after the last measurement. We form the average and patient‐specific models to predict the blood glucose level of the patients. Both models are tested on two different datasets which contain patients with T1D. The experimental results are evaluated in terms of root mean squared error and Clarke error grid analysis metrics. The results indicate that our proposed modified algorithm is feasible to be applied to the prediction of blood glucose levels. In addition, this approach can assist patients with T1D for their blood glucose control.     

Excess Molar Isentropic Compressibilities,Excess Molar Volumes,and Excess Sound Speeds of the 1-Propanol + Diethyl Ether + 1-Octanol Ternary Mixture and Constituent Binary Mixtures at 298.15 K

The sound speeds and densities of the 1-propanol + diethyl ether + 1-octanol ternary mixture and constituent binary mixtures, 1-propanol + diethyl ether, 1-propanol + 1-octanol, and diethyl ether + 1-octanol, have been measured at 298.15 K as a function of composition. Isentropic compressibilities, molar isentropic compressibilities, excess molar isentropic compressibilities, excess molar volumes, and excess sound speeds have been calculated from the experimental density and sound speed data. Excess molar volumes, excess molar isentropic compressibilities, and excess sound speeds of the binary mixtures were fitted to the Redlich–Kister equation. By using the free length theory (FLT), Schaaff’s collision factor theory (CFT), Nomoto’s relation (NR), Van Deal’s ideal mixing relation (IMR), and Junjie’s relation (JR), sound-speed values of the investigated mixtures were calculated. These values were compared with the experimental sound-speed results.     

Wear response of glass fiber and ceramic tile-reinforced hybrid epoxy matrix composites

Iranian Polymer Journal - This study presents the tribological behavior of epoxy matrix composites containing two different fillers. The composites contain fillers with different particle sizes...