Minimizing the number of tardy jobs and maximum earliness in the single machine scheduling using an artificial immune system

Nowadays, the importance of timely delivery, which is based on the just in time concept, has caused a number of criteria related to scheduling problems to be taken into consideration. One of the most important of these criteria is maximum earliness to control final costs and number of tardy jobs in an attempt to win customer satisfaction. In this paper, the strongly NP-hard problem of the single machine scheduling with two criteria, i.e., maximum earliness and number of tardy jobs, has been considered. For this purpose, artificial immune system which is inspired by the immunology theory in biology has been used. This algorithm is applied to different instances of small to large sizes and the obtained results is compared with those obtained from a heuristic method and a genetic algorithm reported in the literature. Computational results show a significant preference for the algorithm proposed in this paper.     

Classification of normal/abnormal PCG recordings using a time–frequency approach

The early and accurate diagnosis of cardiovascular diseases (CVDs) are of great importance as they allow early and proper medical treatment and therefore result in reducing the chance of the CVDs being developed to an acute level. In medical procedures, the first step in examining the cardiovascular function is the auscultation of the heart. However, the correct medical diagnosis based on the heart sounds through a stethoscope requires a lot of expertise and, in some cases, needs referral of the patient to a cardiologist. This is not only time-consuming but also imposes a financial burden on the medical system. Thus, automated detection and analysis of the recorded heart sound auscultation has received a lot of attentions in recent years. This study presents a new time–frequency (T–F) based approach for classifying phonocardiogram (PCG) signals into normal and abnormal. In the proposed methodology, each PCG recording is first segmented into the 4 fundamental heart cycles, i.e. S1, systole, S2, and diastole. From each state, a set of T–F features are extracted with the aim of identifying their characteristics in the T–F domain. The features are then applied to a support vector machine to classify the PCG signal into normal or abnormal. The performance of the proposed method is evaluated using the 2016 PhysioNet challenge database and compared with that of the best performing existing methods. The experimental results using tenfold cross-validation show that the proposed method outperforms the existing methods in terms of sensitivity, specificity, and accuracy.

     

Trends of biofuel cells for smart biomedical devices

Due to the increasing demand for monitoring diseases such as rising heart rate, diabetes, and ocular disorders wearable and implantable biomedical devices seems too essential for patients not only in the hospital but also at home or during working time. Researchers mostly try to offer valuable information on the conditions of patients as non-invasive, by using comfort biomedical device with a minimum side effect. So, small and self-powered with high sensitivity biomedical devices are recommended, among different power sources that introduced for devices, biofuel cells would be produced as power source for a range of medical devices because of its capability to generate sufficient power output compared to the primary power source. The nature of the electrode reaction and the nature of the biochemical reactions are some of the important parameters that are considered for the classification of fuel cells. Enzymatic biofuel cells due to high activity at mild conditions widely applied in pacemaker; glucometer; and smart contact lenses when compared to other kinds of biofuel cells. On the other hand, short lifespan is one of important limitations in this type of biofuel cells. So, the easiest way to overcome these challenges is to apply non-enzymatic ones. Recent studies have attempted to issue novel method for fabrication of non-enzymatic biofuel cell in order to produce a new generation which are inexpensive, disposable, selective, and sensitive in properties. However, consideration of researchers to the development of self-powered biomedical devices by using body fluids or providing electricity storage is rising.     

Electrodeposition of Ni–Fe micro/nano urchin-like structure as an efficient electrocatalyst for overall water splitting

The usage of active electrocatalysts is a useful approach to accelerate the kinetics of electrochemical reactions and to enhance the efficiency of water splitting. To fabricate active electrocatalysts, the creation of new structures that can be easily constructed has always been a research interest. Ni–Fe based alloys are generally known as active OER catalyst. However, in this study, a novel Ni–Fe micro/nano urchin-like structure is reported to be active for both HER and OER. This is the first report of the fabrication of this morphology by a fast, one-step, and affordable electrodeposition method as an efficient HER/OER electrocatalyst. The optimized Ni–Fe coating on Cu substrate demonstrated promising HER activity with low overpotentials of ?124 and ?243 mV at the current densities of ?10 and ?100 mA cm^?2, respectively. Moreover, the fabricated Ni–Fe urchin-like catalyst is highly active toward OER, requiring overpotentials of only 292 and 374 mV to deliver 10 and 100 mA cm^?2. The unique structure of the synthesized coating with an abundant number of micro/nano-scale cones is suggested to play a vital role in the superior HER/OER activity of the catalyst. This article introduces a cost-effective method for the fabrication of a novel urchin-like Ni–Fe alloy as a highly active bifunctional water splitting electrocatalyst.     

Synthesis of a novel Zn-MOF/PVA nanofibrous composite as bioorganic material: Design,systematic study and an efficient arsenic removal

Metal organic framework (Zn-MOF)/polyvinyl alcohol (PVA) nanofibrous composite new material has been fabricated using electrospinning and is characterized by a variety of physicochemical analyses, including Fourier transmitting infrared spectroscopy, X-ray powder diffraction (XRD), scanning electron microscopy-energy dispersive spectroscopy, nitrogen adsorption surface, and thermo gravimetric-derivative of thermogravimetry. In this study, the effects of a systematic study including a fractional factorial design were studied for arsenic removal. The results showed that although conventional methods have a high level of arsenic removal, the fractional factor method results in a relatively high level of absorption of arsenic. This high level of arsenic removal allows the potential use of nano adsorbents in various environmental fields. The systematic study developed in this study can be used as a novel protocol to eradicate pollution from different areas, including water, air, and soil.     

An efficient neurodynamic model to solve nonconvex nonlinear optimization problems and its applications

This paper presents a recurrent neural network for solving nonconvex nonlinear optimization problems subject to nonlinear inequality constraints. First, the p-power transformation is exploited for local convexification of the Lagrangian function in nonconvex nonlinear optimization problem. Next, the proposed neural network is constructed based on the Karush–Kuhn–Tucker (KKT) optimality conditions and the projection function. An important property of this neural network is that its equilibrium point corresponds to the optimal solution of the original problem. By utilizing an appropriate Lyapunov function, it is shown that the proposed neural network is stable in the sense of Lyapunov and convergent to the global optimal solution of the original problem. Also, the sensitivity of the convergence is analysed by changing the scaling factors. Compared with other existing neural networks for such problem, the proposed neural network has more advantages such as high accuracy of the obtained solutions, fast convergence, and low complexity. Finally, simulation results are provided to show the benefits of the proposed model, which compare to or outperform existing models.     

Effect of inulin formulation on the microstructure and viscoelastic properties of low‐fat mayonnaise containing modified starch

Combinations of three types of inulin differing in the degree of polymerization, that is, short, medium, and long chained (0–10%), and modified starch (0–3%) with different composition ratios were prepared according to the D‐optimal design of experiments. The microstructural and rheological characteristics of the prepared samples were analyzed to study the effect of the inulin composition on the low‐fat mayonnaise. Rheological characterizations, including oscillatory frequency sweep tests, transient creep, and stress relaxation analysis, were carried out on the samples. An optical microscope was used to observe the microstructure. According to the results, the effects of all types of inulin were precarious in the presence of starch (≥1.5%). In fact, a relationship was found between the inulin type and concentration and also the starch content in all of the prepared samples; with increasing starch content (≥1.5%), inulin chain length, and concentration of long‐chain inulin (≥5%), the elastic properties of the emulsion were improved and showed a higher resistivity against deformation. Furthermore, a more packed structure with a larger average particle diameter and dominant monodispersity were observed under such conditions. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 801‐809, 2013     

Cane molasses fermentation for continuous ethanol production in an immobilized cells reactor by Saccharomyces cerevisiae

Sodium-alginate immobilized yeast was employed to produce ethanol continuously using cane molasses as a carbon source in an immobilized cell reactor (ICR). The immobilization of Saccharomyces cerevisiae was performed by entrapment of the cell cultured media harvested at exponential growth phase (16 h) with 3% sodium alginate. During the initial stage of operation, the ICR was loaded with fresh beads of mean diameter of 5.01 mm. The ethanol production was affected by the concentration of the cane molasses (50, 100 and 150 g/l), dilution rates (0.064, 0.096, 0.144 and 0.192 h^?1) and hydraulic retention time (5.21, 6.94, 10.42 and 15.63 h) of the media. The pH of the feed medium was set at 4.5 and the fermentation was carried out at an ambient temperature. The maximum ethanol production, theoretical yield (Y_E/S), volumetric ethanol productivity (Q_P) and total sugar consumption was 19.15 g/l, 46.23%, 2.39 g l^?1 h^?1 and 96%, respectively.     

Hyperelastic model analysis of stress‐strain behavior in polybutadiene/ethylene‐propylene diene terpolymer nanocomposites

Micromechanics of elastomer nanocomposite samples based on polybutadiene (BR), ethylene‐propylene diene terpolymer (EPDM) hyperelastic matrixes prepared via melt compounding was investigated using uniaxial tensile analysis. Constitutive hyperelastic models, including Polynomial, Yeoh, Ogden, Arruda‐Boyce, and Van der Waals were used to determine material parameters in incompressible isotropic elastic strain‐energy functions on the basis of a nonlinear least squares optimization method by fitting the data obtained from uniaxial classic experiments. Effect of nanoclay (0, 3, 5, 7, and 10 phr) content on the simulation accuracy was investigated. Simulation results compared with the experimental data suggested that the Ogden model as the most consistent model investigated here. J. VINYL ADDIT. TECHNOL., 23:21–27, 2017. © 2015 Society of Plastics Engineers     

An efficient and controllable ultrasonic-assisted microwave route for flower-like Ta(V)–MOF nanostructures: preparation,fractional factorial design,DFT calculations,and high-performance N<Subscript>2</Subscript> adsorption

With respect to different applications of metal–organic framework (MOF) in the medical, industrial and environmental fields, it is very important to choose a new structure that can be synthesized by fast, eco-friendly and affordable methods with distinctive properties so that the properties could be systematically controlled. In this study, new Ta–MOF nanostructures are synthesized by novel methods of microwave (Mw) and ultrasonic assisted microwave (UAMw) in environmental conditions. The final products are characterized by relevant techniques. Although in the both methods, the synthesized products have favourable properties; the use of the UAMw method would produce samples with distinct features such as high thermal stability of 240 °C, average particle size distribution (PSD) of 23 nm and significant specific surface area (SSA) of 2012 m²/g. For a better comprehension of the Ta–MOF formation, computational studies are performed using DFT calculations. In order to investigate the effect of the synthesis parameters on different features of the products, the fractional factorial design is used. The results of analysis of variance confirm that the parameters such as Mw power, Mw duration, ultrasonic temperature, ultrasonic power and ultrasonic duration have a significant effect on PSD and SSA of Ta–MOF samples. Due to the fractional factorial design of the experiments, response surface methodology would optimize the probability of producing samples with the small PSD of 15 nm and high SSA of 2588 m²/g; this desirable amount would provide situations to use these compounds in diverse fields.