A dynamic coalition formation game for search efficient adaptive overlay construction in unstructured peer-to-peer networks

A great number of recent works deal with improving search in peer-to-peer systems, specifically by clustering peers into semantic groups. When the process of clustering is predetermined and static, it suffers from lack of adaptation to highly dynamic peer-to-peer environments. We model the problem as a non-superadditive coalition game with non-transferable utility characteristic function, and propose a distributed dynamic coalition formation algorithm through myopic best-reply with experiment rule to solve the coalition formation problem. Coalitions are formed by peers with similar interests considering geographical proximity. The overlay network is dynamically reconfigured over time based on the changes in the interests or locations of the individual peers. The convergence of the proposed algorithm using “core solution” concept is studied. The simulation results show that the proposed algorithm can efficiently reduce the search time, although the overhead of the overlay adaptation is slightly higher.     

Numerical simulation of two-dimensional sine-Gordon solitons via a local weak meshless technique based on the radial point interpolation method (RPIM)

In this paper the meshless local radial point interpolation method (LRPIM) is adopted to simulate the two-dimensional nonlinear sine-Gordon (S-G) equation. The meshless LRPIM is one of the “truly meshless” methods since it does not require any background integration cells. In this case, all integrations are carried out locally over small quadrature domains of regular shapes, such as circles or squares in two dimensions and spheres or cubes in three dimensions. A technique is proposed to construct shape functions using radial basis functions. These shape functions which are constructed by point interpolation method using the radial basis functions have delta function property. The time derivatives are approximated by the time-stepping method. In order to eliminate the nonlinearity, a simple predictor-corrector scheme is performed. Numerical results are obtained for various cases involving line and ring solitons. Also the conservation of energy in undamped sine-Gordon equation is investigated.     

Solving a category of two-dimensional fractional optimal control problems using discrete Legendre polynomials

In this paper, we formulate a numerical method to approximate the solution of two-dimensional optimal control problem with a fractional parabolic partial differential equation (PDE) constraint in the Caputo type. First, the optimal conditions of the optimal control problems are derived. Then, we discretize the spatial derivatives and time derivatives terms in the optimal conditions by using shifted discrete Legendre polynomials and collocations method. The main idea is simplifying the optimal conditions to a system of algebraic equations. In fact, the main privilege of this new type of discretization is that the numerical solution is directly and globally obtained by solving one efficient algebraic system rather than step-by-step process which avoids accumulation and propagation of error. Several examples are tested and numerical results show a good agreement between exact and approximate solutions.     

Combination of Chemical Coagulation and Photo-Fenton Oxidation Process for the Treatment of Beet Sugar Industry Wastewater: Optimization of Process Conditions by Response Surface Methodology

The beet sugar industry generates large volumes of wastewater with high levels of chemical oxygen demand (COD) and color content, which are discharged into the nearby environment without adequate treatment. The aim of this study was to investigate the treatment possibility of this wastewater by using the photo-Fenton oxidation combined with a coagulation process. Central composite design and response surface methodology were used to evaluate the relationships between color and COD reduction and the photo-Fenton oxidation parameters (i.e. Fenton’s reagent dosage, pH, and reaction time).

The combined treatment results showed 59% of COD and 83.9% of color removal were obtained at optimum conditions (pH: 6.2; Fe²⁺ dosage: 20 ppm; H₂O₂ dosage: 1500 ppm; and reaction time of 15 min). Finally, the results of gel permeation chromatography showed that low molecular weight fraction of the wastewater impurities is more degraded than high molecular weight fraction during oxidation/coagulation process. Therefore, the results obtained from this study showed that an appropriate combined method for the treatment of beet sugar industry wastewater can be designed and implemented.     

Development and characterization of a Persian gum–sodium caseinate biocomposite film accompanied by Zingiber officinale extract

Nowadays, instead of synthetic polymers, ecofriendly biopolymers are being widely used as packaging materials; this minimizes packaging waste and environmental pollution. In this study, we aimed to characterize edible films based on sodium caseinate (SC) with the simultaneous use of Zingiber officinale extract (ZOE) and Persian gum (PG). The functional, structural, morphological, and physicochemical aspects of manufactured samples were investigated. Response surface methodology was used to optimize the use of PG (0–1%) and ZOE (0–500 ppm) in the production of the edible films. Fourier transform infrared spectroscopy analysis was carried out to confirm the SC–PG–ZOE interactions. Statistical analysis revealed that the addition of ZOE led to a significant increase in the tensile strength and elongation at break (EB). However, the addition of PG, regardless of ZOE addition, decreased EB. In addition, the incorporation of ZOE into the biopolymer matrix improved the water resistance, water vapor permeability (WVP), and water solubility (WS), whereas the incorporation of PG reduced the transparency. Our findings indicated that minimum of transparency and EB and minimum of WVP and WS were obtained at 0.6% for PG and 360 ppm for ZOE. Therefore, the results of this study suggest a new biocomposite with desirable characteristics and promising potential for producing edible films. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47215.     

Combination of meshless local weak and strong (MLWS) forms to solve the two dimensional hyperbolic telegraph equation

In this paper a numerical approach based on the truly meshless methods is proposed to deal with the second-order two-space-dimensional telegraph equation. In the meshless local weak–strong (MLWS) method, our aim is to remove the background quadrature domains for integration as much as possible, and yet to obtain stable and accurate solution. The MLWS method is designed to combine the advantage of local weak and strong forms to avoid their shortcomings. In this method, the local Petrov–Galerkin weak form is applied only to the nodes on the Neumann boundary of the domain of the problem. The meshless collocation method, based on the strong form equation is applied to the interior nodes and the nodes on the Dirichlet boundary. To solve the telegraph equation using the MLWS method, the conventional moving least squares (MLS) approximation is exploited in order to interpolate the solution of the equation. A time stepping scheme is employed to approximate the time derivative. Another solution is also given by the meshless local Petrov-Galerkin (MLPG) method. The validity and efficiency of the two proposed methods are investigated and verified through several examples.     

An Intelligent HealthCare Monitoring Framework for Daily Assistant Living

Human Activity Recognition (HAR) plays an important role in life care and health monitoring since it involves examining various activities of patients at homes, hospitals, or offices. Hence, the proposed system integrates Human-Human Interaction (HHI) and Human-Object Interaction (HOI) recognition to provide in-depth monitoring of the daily routine of patients. We propose a robust system comprising both RGB (red, green, blue) and depth information. In particular, humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency map. To track the movement of humans, we proposed orientation and thermal features. A codebook is generated using Linde-Buzo-Gray (LBG) algorithm for vector quantization. Then, the quantized vectors generated from image sequences of HOI are given to Artificial Neural Network (ANN) while the quantized vectors generated from image sequences of HHI are given to K-ary tree hashing for classification. There are two publicly available datasets used for experimentation on HHI recognition: Stony Brook University (SBU) Kinect interaction and the University of Lincoln's (UoL) 3D social activity dataset. Furthermore, two publicly available datasets are used for experimentation on HOI recognition: Nanyang Technological University (NTU) RGB-D and Sun Yat-Sen University (SYSU) 3D HOI datasets. The results proved the validity of the proposed system.     

Pedestrian Physical Education Training Over Visualization Tool

E-learning approaches are one of the most important learning platforms for the learner through electronic equipment. Such study techniques are useful for other groups of learners such as the crowd, pedestrian, sports, transports, communication, emergency services, management systems and education sectors. E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and methods. Many of them are currently working on this domain to fulfill the requirements of industry and the environment. In this paper, we proposed a method for pedestrian behavior mining of aerial data, using deep flow feature, graph mining technique, and convocational neural network. For input data, the state-of-the-art crowd activity University of Minnesota (UMN) dataset is adopted, which contains the aerial indoor and outdoor view of the pedestrian, for simplification of extra information and computational cost reduction the pre-processing is applied. Deep flow features are extracted to find more accurate information. Furthermore, to deal with repetition in features data and features mining the graph mining algorithm is applied, while Convolution Neural Network (CNN) is applied for pedestrian behavior mining. The proposed method shows 84.50% of mean accuracy and a 15.50% of error rate. Therefore, the achieved results show more accuracy as compared to state-of-the-art classification algorithms such as decision tree, artificial neural network (ANN).     

Mathematical modeling of polyethylene terephthalate pyrolysis in a spouted bed

A model has been developed for pyrolysis of polyethylene terephthalate (PET) in a spouted bed reactor based on the conservation equations for heat, mass, and momentum transports. A spouted bed has been constructed and the kinetic parameters have been obtained within the temperature range of 723–833 K, using two particle size ranges, (0.1–1.0) × 10^?3 and (1.0–3.0) × 10^?3 m. The model' predictions for the radial distributions of temperature and concentration confirm the excellent mixing of particles. Thus, spouted beds are appropriate equipments for performing kinetic studies of PET pyrolysis. The inlet gas temperature and the mass of PET highly affect PET conversion. The amount of inert particles has a negligible effect on the conversion and it can be reduced as far as a stable spouting is preserved. The gas flow suffices to eliminate the external heat and mass‐transfer limitations. It can be reduced to the minimum value to decrease the energy consumption. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1900–1911, 2015