Energy and load balancing routing protocol for IoT

Due to the limitation of node energy resources, the management of energy consumption is one of the most important problems of the internet of things (IoT). Therefore, many studies have tried to optimize and manage energy consumption by focusing on different techniques. Although each of these studies has improved and optimized energy consumption, there are many important problems, including maintaining traffic balance and energy consumption of network nodes. Therefore, a new method is necessary to maintain the load and energy balancing of network nodes. Therefore, this paper introduces energy and load balancing routing protocol for IoT (ELBRP) based on the development of the RPL routing protocol and the efficiency of data distribution technique. The ELBRP performance has three steps. In the first step, along with the process of sending DODAG information object (DIO) messages, the status of network nodes is evaluated. In the second step, the DODAG communication graph is formed according to the ELBRP. In the third step, data transmission is done according to the distribution technique with the goal of balancing traffic and energy. The simulation results using cooja simulator showed the superiority of ELBRP in improving energy consumption and successful delivery ratio, reducing delay and increasing the network lifetime compared to the similar methods.     

A meshless method for solving 1D time-dependent heat source problem

A novel meshless numerical procedure based on the method of fundamental solutions (MFS) and the heat polynomials is proposed for recovering a time-dependent heat source and the boundary data simultaneously in an inverse heat conduction problem (IHCP). We will transform the problem into a homogeneous IHCP and initial value problems for the first-order ordinary differential equation. An improved method of MFS is used to solve the IHCP and a finite difference method is applied for solving the initial value problems. The advantage of applying the proposed meshless numerical scheme is producing the shape functions which provide the important delta function property to ensure that the essential conditions are fulfilled. Numerical experiments for some examples are provided to show the effectiveness of the proposed algorithm.     

A modified particle swarm optimization for economic dispatch with non-smooth cost functions

This paper presents a new approach to economic dispatch (ED) problems with non-smooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have non-smooth cost functions with equality and inequality constraints, which makes the problem of finding the global optimum difficult when using any mathematical approaches. Since, standard PSO may converge at the early stage, in this paper, a modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the ED problems. To validate the results obtained by MPSO, standard particle swarm optimization (PSO) and guaranteed convergence particle swarm optimization (GCPSO) are applied for comparison. Also, the results obtained by MPSO, PSO and GCPSO are compared with the previous approaches reported in the literature. The results show that the MPSO produces optimal or nearly optimal solutions for the study systems.     

An efficient classifier to diagnose of schizophrenia based on the EEG signals

In this paper, electroencephalogram (EEG) signals of 13 schizophrenic patients and 18 age-matched control participants are analyzed with the objective of classifying the two groups. For each case, multi-channels (22 electrodes) scalp EEG is recorded. Several features including autoregressive (AR) model parameters, band power and fractal dimension are extracted from the recorded signals. Leave-one (participant)-out cross validation is used to have an accurate estimation for the separability of the two groups. Boosted version of Direct Linear Discriminant Analysis (BDLDA) is selected as an efficient classifier which applied on the extracted features. To have comparison, classifiers such as standard LDA, Adaboost, support vector machine (SVM), and fuzzy SVM (FSVM) are applied on the features. Results show that the BDLDA is more discriminative than others such that their classification rates are reported 87.51%, 85.36% and 85.41% for the BDLDA, LDA, Adaboost, respectively. Results of SVM and FSVM classifiers were lower than 50% accuracy because they are more sensitive to outlier instances. In order to determine robustness of the suggested classifier, noises with different amplitudes are added to the test feature vectors and robustness of the BDLDA was higher than the other compared classifiers.     

Taguchi Optimization of Solvent-Antisolvent Crystallization to Prepare Ammonium Perchlorate Particles

The sphericity and size of ammonium perchlorate (AP) particles significantly influence the properties of composite propellants. As the AP particles become more spherical, the accumulation coefficient increases, the viscosity during casting decreases, and the particle loading and burning rate increase. Hence, the production of micronized AP particles with an average size between 1 and 20 μm is important to increase the loading percentage of AP in the composite propellant. Here, the Taguchi experimental design was used to optimize the solvent-antisolvent crystallization (SAC) process for the preparation of micronized AP particles with higher sphericity. SAC parameters such as the type of antisolvent, the solvent-to-antisolvent ratio, the antisolvent temperature, the stirring speed, and the retention time were investigated at four levels. The type of antisolvent and the solvent-to-antisolvent ratio were found to mainly contribute to improving the sphericity and size of the AP particles, respectively.     

A new nickel metal organic framework (Ni-MOF) porous nanostructure as a potential novel electrochemical sensor for detecting glucose

Journal of Porous Materials - A Ni-MOF-based novel electrochemical sensor was synthesized with high surface area of 1381 m2/g, significant porosity of 1.14–9.6 nm and average...     

A hybrid algorithm for scheduling scientific workflows in IaaS cloud with deadline constraint

The Journal of Supercomputing - Scientific workflows are used to process large amounts of data and perform complex analyses; thus, they require powerful computing resources to produce the desired...     

A meshless method to the numerical solution of an inverse reaction–diffusion–convection problem

In this paper, the determination of the source term in a reaction–diffusion convection problem is investigated. First with suitable transformations, the problem is reduced, then a new meshless method based on the use of the heat polynomials as basis functions is proposed to solve the inverse problem. Due to the ill-posed inverse problem, the Tikhonov regularization method with a generalized cross-validation criterion is employed to obtain a numerical stable solution. Finally, some numerical examples are presented to show the accuracy and effectiveness of the algorithm.     

Albumin-based biomaterial for lung tissue engineering applications

The role of albumin-based biomaterials in tissue engineering (TE) cannot be overemphasized. The authors review the role of albumin in lungs scaffold grafting, which promotes cell seeding. Albumin grafted on decellularized lungs scaffold is presented as a great support material for cell-tissue interaction as well as for ease in attachment, growth, and differentiation when seeded with different types of cells. Albumin scaffold fabrication from different sources is a promising approach that may facilitate medical treatments from bench-to-bed, although the role of this scaffold in lungs surfactant proteins regeneration and binding needs to be fully elucidated.     

Synthesis of new electromagnetic nanocomposite based on modified Fe3O4 nanoparticles with enhanced magnetic,conductive, and catalytic properties

A new method for the fabrication of an electromagnetic nanocomposite based on Fe₃O₄ and polyaniline (PANI) is offered. The authors focused on improvement of the physical and electromagnetic properties of the nanocomposite using a new synthetic method. Supermagnetic Fe₃O₄ nanoparticles were synthesized through coprecipitation method. As a chemical modification, the third generation of poly (amidoamine) dendrimer was grafted on the surface of the nanoparticles. PANI was grafted from –NH₂ functional groups of dendrimer via in situ polymerization of aniline. Finally, Au nanoparticles were loaded on the nanocomposite and its catalytic activity for reduction reactions was studied.