International Journal Of Nonlinear Analysis And Applications
Volume:11 Issue: 1, Winter-Spring 2020

In this paper, some fixed point theorems for nonexpansive mappings in partially ordered spherically complete ultrametric spaces are proved. In addition, we investigate the existence of fixed points for nonexpansive mappings in partially ordered non-Archimedean normed spaces. Finally, we give some examples to discuss the assumptions and support our results.

Face recognition is still an active pattern analysis topic. Faces have already been treated as objects or textures, but human face recognition system takes a different approach in face recognition. People refer to faces by their most discriminant features. People usually describe faces in sentences like ``She's snub-nosed'' or ``he's got long nose'' or ``he's got round eyes'' and so like. These most discriminant features have been extracted by comparing a face with average face formed in one's mind. We have mathematically formulated the approach and placed importance upon the most discriminant features. We have explained feature processing and classification parts in details. We also explained the train and test phases of the proposed algorithm. We have compared the proposed classification part with 1-NN classifier to show the strength of the algorithm and reported the results. We have also compared the whole proposed algorithm with a well-known face recognition method, Eigenfaces and achieved promising results in different cases.

Multi-transmitter multi-receiver passive radar, which locates target in the surveillance area by the reflected signals of the available opportunistic transmitter from the target, is of interest in many applications. In this paper, we investigate different signal processing scenarios in multi-transmitter multi-receiver passive radar. These scenarios include decentralized processing of reference and surveillance signals, decentralized processing of surveillance signals, and centralized processing of surveillance signals that have different advantages, disadvantages, and requirements. A variety of possible measurements including TDOA, GROA, AOA and their combinations are presented under different scenarios. The Cramer Rao lower band (CRLB) is presented for different signal processing scenarios for the error of the target localization. The efficiency of the target localization for different signal processing scenarios and types of measurements has been investigated by the CRLB. As shown in the simulation results, the combined use of the measurements is always better than their single use. Also centralized and decentralized processing of surveillance signals, by arranging the receiver sensors in the far distances, can have better efficiency than close distance arrangements.

In this work, we investigate the following Kirchhoff-type equation with variable exponent nonlinearities u_{tt}-M(‖∇u‖²)△u+|u_{t}|^{p(x)-2}u_{t}=|u|^{q(x)-2}u. We proved the blow up of solutions in finite time by using modified energy functional method.

In this paper, we prove strong convergence results for a modified Mann iterative process for a new class of I- nearly weak uniformly L-Lipschitzian mappings in a real Banach space. The class of I-nearly weak uniformly L-Lipschitzian mappings is an interesting generalization of the class of nearly weak uniformly L-Lipschitzian mappings which inturn is a generalization of the class of nearly uniformly L-Lipschitzian mappings which inturn generalises uniformly L-Lipschitzian mappings. Our theorems include some very recent results in fixed point theory and applications, in the context of nearly uniformly L-Lipschitzian mappings.

In this paper, we first establish a new fixed point theorem for a Meir-Keeler type condition. As an application, we derive a simultaneous generalization of Banach contraction principle, Kannan's fixed point theorem, Chatterjea's fixed point theorem and other fixed point theorems. Some new fixed point theorems are also obtained.

In this paper, two games that play a role in creating a cancer tumor and suppression are studied using evolutionary game theory and its different modes are analyzed. The first game is the competition between a cancer cell and a healthy cell to receive food through the blood. In the second game, the interaction between the two oncogenes Ras and Myc is examined for cellular deformation

In this study, considering the importance of how to exploit renewable natural resources, we analyzea shing model with nonlinear harvesting function in which the players at the equilibrium pointdo a static game with complete information that, according to the calculations, will cause a wasteof energy for both players and so the selection of cooperative strategies along with the agreementbetween the players is the result of this research.

One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorithm is proposed which uses support vector machine classifier and cuckoo search algorithm in combination with the genetic algorithm in order to select the optimal features. In the proposed method, at first, a set of characteristics based on the Cepstral, Spectral and Fourier coefficients of the speech signal is extracted and then with the proposed hybrid algorithm, the operation of selecting the optimal feature set is performed. The results of the experiments on the famous Berlin's emotional speech database showed that using this proposed method for selecting the features, increases the classification accuracy to about 93%.

In the past three decades, the use of smart methods in medical diagnostic systems has attracted the attention of many researchers. However, no smart activity has been provided in the field of medical image processing for diagnosis of bladder cancer through cystoscopy images despite the high prevalence in the world. In this paper, a multilayer neural network was applied to classify blad- der cystoscopy images. One of the most important issues in training phase of neural networks is determining the learning rate. Because selecting too small or large learning rate leads to slow con- vergence, volatility and divergence, respectively. Therefore, an algorithm is required to dynamically change the convergence rate. In this respect, an adaptive method was presented for determining the learning rate so that the multilayer neural network could be improved. In this method, the learning rate is determined using a coefficient based on the difference between the accuracy of training and validation according to the output error. In addition, the rate of changes is updated according to the level of weight changes and output error. Another challenge in neural networks is determining the initial weights. In cystoscopy images, randomized initial weights should not be used due to a small number of images collected. Therefore, the genetic algorithm (GA) is applied to determine the initial weight. The proposed method was evaluated on 540 bladder cystoscopy images in three classes of  blood in urine, benign and malignant masses. Based on the simulated results, the proposed method achieved a 7% decrease in error and increased the convergence speed of the proposed method in the classification of cystoscopy images, compared to the other competing methods.

This study was conducted aimed at providing a sustainable multi-objective model of supply chain location, inventory, routing under uncertainty with a passive defense approach, in which the Upgral model was first introduced to the world. The Upgral Paradigm is an integrated model for the location-inventory-routing problem in a four-level supply chain where parameters such as demand, facility cost and inventory costs are taken into account uncertain as triangular fuzzy numbers (TFNs). In this study, the characteristics and capabilities of passive defense in the supply chain, such as "logistical flow rate", "backup path security", "the possibility of resource and equipment deployment", and the dispersion principle were considered for location to increase the resilience of supply chain. The model was solved using Whale Optimization Algorithm (WOA) and NSGA-II meta-heuristic algorithm. First, a four-objective mathematical model was proposed for the problem the objectives of which were: 1) minimizing supply chain costs; 2) maximizing social responsibility or social benefits; 3) minimizing environmental impacts; and 4) minimizing risk. Moreover, the experimental sample problems were solved in three small, medium, and large groups using the WOA Algorithm. The results of solving this algorithm were compared with the results of NSGA-II one according to the indices including quality, dispersion, uniformity and solution time indices to prove the efficiency of the algorithm. Based on the results, the WOA algorithm had a higher ability to achieve higher quality and near-optimal solutions than NSGA-II algorithm in all cases. The dispersion index values indicated that the WOA Algorithm performed better in exploring and extracting the feasible region. In addition, with respect to the results of the uniformity and the solution time indices, it was found that the NSGA-II Algorithm had a lower solution time than the WOA Algorithm and the answer space more uniformly.

Nature-inspired metaheuristic algorithms have been a topic of interest for researchers to solve optimization problems in engineering designs and real-world applications, due to their simplicity and flexibility. This paper presents a new nature-inspired search algorithm called Woodpecker Mating Algorithm (WMA) and applies it to challenging problems in structural optimization. The WMA is a population-based metaheuristic algorithm that mimics the mating behavior of woodpeckers. It was inspired by the drumming sound intensity. In WMA, the population of woodpeckers is divided into male and female groups. The female woodpeckers approach the male woodpeckers based on the intensity of their drum sound. An efficiency comparison was drawn between the WMA algorithm and other metaheuristic algorithms by employing 19 benchmark functions(including unimodal, multimodal and composite functions). Moreover, the performance of WMA is compared with 8 of the best meta-heuristic algorithms using 13 high dimensional multimodal and unimodal benchmark functions. The assessments and statistical results indicate that the WMA algorithm offers promising results and is capable of outperforming the most recent and popular algorithms proposed in the literature in most of the employed benchmark functions. Moreover, a statistically significant difference was observed compared to the other assessed algorithms. The proposed algorithm produced significant results for a non-convex, inseparable, and scalable problems.

In this paper, we give some sufficient conditions under which perturbations preserve Hilbert-Schmidtframes. Also show that the canonical dual of a perturbed Hilbert-Schmidt frame is a perturbationof the canonical dual (alternative dual respectively) of the original Hilbert-Schmidt frame and dis-cuss best approximation in the set of all dual Hilbert-Schmidt frames. Next, we apply the wovenprinciple to Hilbert-Schmidt frames and study the stability of weaving Hilbert-Schmidt frames underperturbations. Finally, we present sufficient conditions under which perturbations preserve weavingHilbert-Schmidt frames and weaving dual Hilbert-Schmidt frames.

The flow of fluids including micron particles in micro channels and manufacturing microfluidics tools have been one of the important topics in last decades and are utilized in different industries. The research procedure is experimental in this work. The experimental tests are carried out on the flow in a convergent-divergent microchannel having 200 $mu$m height. The utilized experimental method in this research is particle tracking based on the xerography technique, observation, record and data processing. The results showed that the velocity of the particles in Y-direction has a great effect on their motion in the convergent-divergent channel. Study of the particles' sedimentation in different Reynolds showed that it can be eliminated the destructive effect of channel obstruction using convergent-divergent channel which is originated from increasing sedimentation in low Reynolds. The shear stress and velocity gradient are two main factors of the particles' velocity in the convergent-divergent channel. The results showed that the shear stress has an excessive impact on the particles' velocity than the velocity gradient. Moreover, besides the upper and bottom walls, side walls affect the particles' velocity. The flow of fluids including micron particles in micro channels and manufacturing microfluidics tools have been one of the important topics in last decades and are utilized in different industries. The research procedure is experimental in this work. The experimental tests are carried out on the flow in a convergent-divergent microchannel having 200 $mu$m height. The utilized experimental method in this research is particle tracking based on the xerography technique, observation, record and data processing. The results showed that the velocity of the particles in Y-direction has a great effect on their motion in the convergent-divergent channel. Study of the particles' sedimentation in different Reynolds showed that it can be eliminated the destructive effect of channel obstruction using convergent-divergent channel which is originated from increasing sedimentation in low Reynolds. The shear stress and velocity gradient are two main factors of the particles' velocity in the convergent-divergent channel. The results showed that the shear stress has an excessive impact on the particles' velocity than the velocity gradient. Moreover, besides the upper and bottom walls, side walls affect the particles' velocity.

In this paper, we introduce the (G; )􀀀Ciric-Reich-Rus contraction on metric space endowed with agraph, such that (X; d) is a metric space, and V (G) is the vertices of G coincides with X. We givean example to show that our results generalize some known results

‎In this paper‎, ‎we propose a new method‎, ‎with different approach and economical computing‎, ‎that presents explicit formulas for the exact solutions of a large class DAEs in Hessenberg forms‎. ‎First‎, ‎we illustrate the method for linear time-varying DAEs in Hessenberg forms‎, ‎in order to show the different approach and also we present an algorithm for proposed method that shows the method is as economic as possible‎. ‎Then‎, ‎we describe that the method is efficient for larger classes including special case of non-linear DAEs in Hessenberg forms‎. ‎Some examples are presented to illustrate the proposed method‎.

Nowadays, effort estimation in software development is of great value and significance in project management. Accurate and appropriate cost estimation not only helps customers trust to invest but also has a significant role in logical decision making during project management. Different models of cost estimation are presented and employed to the date, but the models are application specific. In this paper, a three-phase hybrid approach is proposed to overcome the problem. In the first phase, features are selected using a combination of genetic algorithm and the perceptron neural network. In the second phase, impact factors are associated to each selected feature using multiple linear regression methods which act as coefficients of influence for each feature. In the last and the third phase, the feature weights are optimized by Imperialist Competitive Algorithm. To compare the proposed model for effort estimation with state-of-the-art models, three datasets are chosen as benchmark, namely COCOMO, Maxwell and Albrecht. The datasets are standard and publicly available for assessment. The experiments show promising results and average performance is improved by the proposed model for MMRE performance criterion on the datasets by 23%, 38% and 35%, respectively.

Data envelopment Analysis) DEA) is a nonparametric method that aims to use scientific methods in order to investigate the performance of Decision Making Unit (DMU). One of the interesting subjects in DEA is estimation of congestion of DMUs. Congestion problem has an important role in economy because the congestion mostly occurs in the input which is itself cost based, thus by eliminating congestion, the cost reduces as well. Therefore, detecting and reducing congestion both have many benefits. Many methods have been proposed to detect congestion in DEA. In this paper, we are going to present a new method to identify congestion based on the definition of congestion. The proposed method in this paper has the following advantages compare with other methods; Firstly, it is less complicated than other methods. Secondly, our method is able to identify the congestion and its degree correctly.thirdly the new model identifies the congestion of all units. Finally, the proposed method in this paper has non-radial movement.

Plate girders structures is a major industry, much used in the systems covered by these beams, reduce deflection and decrease the maximum bending moment can be considered as a development methodology that way, by the cross beams or braced beams element perpendicular to the girders is provided. In this paper, the effect of stiffness and distance elements development (braced beams) are studied. Differential equation of degree four governing the behavior of the partial structures a quadratic relationship is determined by solving the following mathematical transformations and the fundamental equations are derived. The resulting equations are solved by a practical problem and the answer to the problem. The modeling results are compared with the SAP2000 program shows that highly accurate implementation and compliance. It is thus stiffness changing elements within the cross can be different amounts of stress, bending moment and improved cover and roof system and regulation forces to be calculated. In the proposed method by changing several parameters affecting. Calculate the amount of stress and reduced bending moments and an optional stress adjustment achieved. Other factors, including the backing, boundary conditions, a subsidiary of loading and shooting the junction depth of the main beam are effective in regulating stress.

In this paper, a boundary version of Caratheodory's inequality on the right half plane is investigated.Z(s) is an analytic function dened in the right half of the s-plane.We derive inequalities for themodulus of Z(s) function, jZ′(0)j, by assuming the Z(s) function is also analytic at the boundarypoint s = 0 on the imaginary axis and nally, the sharpness of these inequalities is proved.

In this paper, the new methodology of interconnection network among the various corporations whichare the members of a single nancial group is studied and developed. For the rst time, each companyis observed individually and the cognitive risk factors of each are monitored by new introducedindexes. The risk contagion effect on the main node of the holding is calculated respectively. Thenew indexes help the management to monitor the entire nancial group performance. Also guide themain node of the holdings to make appropriate decisions relating to any investment, prot returningand risk of the nancial group nodes. It is shown, if a company defaults to meet its obligations,how much this will affect the other companies of the network and the main node of the holding.With the use of new developed methodological indexes, the topology of the nancial group networkis displayed graphically for the rst time and the mathematical structure is developed as well.Finally, the illustrative results are apparent in a new introduced software which is coded and testedwith real data and the results show high accuracy.

Conventional dynamic models in economics are usually expressed in discrete or continuous time. A new modelling technique-time scales calculus-unifies both of these approaches into a general framework. We present and construct a dynamic optimization problem from economics in which the utility function is $phi_{h}$-concave and the value function and constraints are on different time scales. The calculus of variations and optimal control are employed, with the aid of the newly introduced diamond-$phi_{h}$ dynamic calculus by the authors [12] on time scales, to obtain a solution. The Hermite-Hadamard inequality with the diamond-$phi_{h}$ dynamic integral follows a proof of the new model. The new diamond-$phi_{h}$ time scale model unifies various related existing models involving general and more complex time domains.

Let G be an abelian group with a metric d, E be a normed space and f : G → E be a given function.We define difference C 3,1 f by the formulaC 3,1 f(x,y) = 3f(x + y) + 3f(x − y) + 48f(x) − f(3x + y) − f(3x − y)for every x,y ∈ G. Under some assumptions about f and C 3,1 f, we show that if C 3,1 f is Lipschitz,then there exists a cubic function C : G → E such that f − C is Lipschitz with the same constant.Moreover, we study the approximation of the equality C 3,1 f(x,y) = 0 in the Lipschitz norms.

Local and global based methods are two main trends for face recognition. Local approaches extract salient features by processing different parts of the image whereas global approaches find a general template for face of each person. Unfortunately, most global approaches work under controlled environments and they are sensitive to changes in the illumination. On the other hand, local approaches are more robust but finding their optimal parameters is a challenging task. This work proposes a new local-based approach that automatically tunes its parameters. The proposed method incorporates different techniques. In the first step, convolutional neural network (CNN) is employed as a trainable feature extraction procedure. In the second step, different metaheuristic methods are merged with CNN so that its best structure is found automatically. Finally, in the last step the decision is made by employing proper multi-class support vector machine (SVM). In this fashion a fully automated system is developed that is self-tuned and do not need manual adjustments. Simulation results demonstrate efficacy of the proposed method.

Web spam is one of the significant problems facing search engines. It wastes sources and time, decreases the quality of results and leads to user discontent. The two main approaches to the detection spam web pages are link and content-based analysis. In this study, we mainly focus on content-based analysis in both user-visible text and the source code of a web page to propose a set of features for web spam detection. we explore the relationship between types and frequency of HTML (HyperText Markup Language) tags used in a web page source code. We also examine the structure of the URL as the other source of information. Finally, the content of a web page visible to the user is considered semantically in order to identify relevance among the number of the existing topics in the text as well as the coherence of a text using Latent Dirichlet Allocation. Experimental results show that the proposed features increases the index of balanced accuracy from 0.33 to 0.69 and improves the web spam detection rate.

The relationship between the variables e.g. economic growth, energy consumption, foreign direct investment, and the growth of pollution are complex issues, and important for the countries, which are planning a sustainable development strategy. On the other hand, considering the effects of geopolitical spillover on environmental economic issues, this paper studies the effective economic factors on carbon dioxide emissions in the developing and developed countries over the period 1993–2016, by employing the approach of the spatial regime panel. Results show that there are spatial effects and spatial heterogeneity between the variables. Accordingly, in this paper, we employed the regression approach of the spatial regime panel. Results show that the how variables affect the spatial regimes varies, and countries that have the structure of the first or second regime have different effects in terms of size and significance of the coefficients. So that in the study of the effect of spatial autoregression variable in the developing countries in the first spatial structure regime, there are neighboring effects of carbon dioxide emissions; while in the second spatial structure regime, there is no neighboring effects in the dependent variable.

Since doing any transaction in online environment requires mutual trust, thus, according to an electronic-environment that lack face-to-face meeting of both parties and the possibility of visible and physical touch of what is being traded, the security and trust will lead to doing transaction with the acceptance of risk. This issue is the major challenge in gaining trust in e-commerce. In this paper, decision-making in e-commerce was modeled and then the level of trust in e-commerce was assessed using CP-Nets by identifying, introducing and evaluating the variables affecting decision-making. The results of the study indicate that corporate factors and business model have the greatest impact on customers' decision-making to trust or distrust in e-commerce for fulfilment of every e-transactions.

Maintenance scheduling of power generators is of particular importance for power grids from both economic and reliability aspects. In this paper, the discrete firefly algorithm is implemented for maintenance scheduling of generators. This project utilizes the combination of the discrete firefly algorithm, as the main tool, and heuristic methods, as the secondary tool, for constructing initial solutions and searching the solution space. The paper investigates a case study consisting of a 32-generator problem formulated as a mixed-integer problem. The performance of the proposed method is compared with those in the literature and its strengths and weaknesses are discussed. The obtained results showed that performance of the proposed algorithm is not highly affected by its parameters’ values and is capable of providing multiple efficient maintenance schedules in a desirable time.

As the penetration of distributed generation sources increases at the distribution level, the necessity of designing microgrids is highlighted. Microgrids can operate in either islanded (separated from the utility grid) or grid-connected mode. Apart from the technical and economic benefits of microgrids, they may cause some protection issues in distribution systems. The most important of these issues is the difference between the short circuit levels in islanded and grid-connected operation modes. In this paper, an intelligent overcurrent relay that can adapt to the microgrid operation mode is proposed; that is, the relay detects the microgrid operation mode by means of an adaptive algorithm. The proposed adaptive method optimizes the accuracy and speed of the algorithm for detecting the microgrid operation mode. Then, the optimal settings that have been already stored in the relay are activated according to the microgrid operation mode. All internal processes of the relay use the voltage and current sampled at the relay location. As a result, the relay can be used in all networks without communication infrastructures. Finally, the proposed method is implemented in a sample microgrid. The superiority of the intelligent relay performance over conventional overcurrent relays is shown by numerical results.

In this article, we secure couple of exciting common xed point theorems via simulation functions in Branciari metric spaces context. These results improve, complement and generalize the recent xed point theorems of Aydi et al. [Results Math., 71(2017), no. 1-2, 73-92] and few others also. Our ndings are aptly endorsed by some interesting non-trivial examples which also illustrate the usefulness of these generalizations. Finally, we discuss an application of our conceived results to a certain type of integral equations.

In this paper, Darbo fixed-point theorem is employed as a mathematical tool to examine existence of the solution of some nonlinear functional stochastic integral equations which arise in many physical, chemical and biological problems. Throughout this paper, we consider (C[0, 1]; ∥.∥ ) as Banach space equipped with uniform norm.

Many organizations (including banks) have a multi-step process and their operations are a continuous process in successive periods. The Taguchi method is an efficient way to optimize a single quality response. However, in practice most products / processes have more than one qualitative response. Recently, the multi-answer question in the Taguchi method has attracted considerable research attention. Therefore, this study presents an efficient approach to multi-response problem solving in Taguchi method using hybrid data envelopment analysis (DEA) model. Each experiment is discussed in the Taguchi Orthogonal Array (OA) as a decision unit (DMU) with multiple input and / or output response sets. Each DMU is evaluated by a hybrid model. The sequential DUM productivity value is then used to decide the optimal factor levels for the multi-response problem. The computational results showed that the proposed approach provides the most anticipated improvement in PCA, DEA (DEAR) and other available techniques. The suggestion may be of great help to managers in solving multi-response problems in production programs in the Taguchi method. Many organizations (including banks) have a multi-step process and their operations are a continuous process in successive periods. The Taguchi method is an efficient way to optimize a single quality response. However, in practice most products / processes have more than one qualitative response. Recently, the multi-answer question in the Taguchi method has attracted considerable research attention. Therefore, this study presents an efficient approach to multi-response problem solving in Taguchi method using hybrid data envelopment analysis (DEA) model. Each experiment is discussed in the Taguchi Orthogonal Array (OA) as a decision unit (DMU) with multiple input and / or output response sets. Each DMU is evaluated by a hybrid model. The sequential DUM productivity value is then used to decide the optimal factor levels for the multi-response problem. The computational results showed that the proposed approach provides the most anticipated improvement in PCA, DEA (DEAR) and other available techniques. The suggestion may be of great help to managers in solving multi-response problems in production programs in the Taguchi method.

In late December 2019, a novel coronavirus nominated SARS-CoV-2 which causing the disease Covid-19 appeared in Wuhan, China. This viral pneumonia such a creeping death took the lives of many people in the whole world. In this brief, we have used nonlinear effect of changing the temperature to destroy COVID-19 from an infected body.

The motivation behind this paper is to study a class of nondifferentiable multiobjective fractional programming problem in which each component of objective functions contains a term including the support function of a compact convex set. For a differentiable function, we consider the class of second-order (F,alpha,rho,d)-type-I convex functions. Further, we formulate unified (mixed type) dual models and derive duality relations under aforesaid assumptions.

Singer and Wermer proved that if A is a commutative Banach algebra and d: A → A is a continuous derivation, then d(A) ⊆ rad(A), where rad(A) denotes the Jacobson radical of A. In this paper, we establish a new proof of that theorem. Moreover, we prove that every continuous Jordan derivation on a finite dimensional Banach algebra, under certain conditions, is identically zero. As another objective of this article, we study {g, h}-derivations on algebras. In this regard, we prove that if f is a {g, h}-derivation on a unital algebra, then f, g and h are generalized derivations. Additionally, we achieve some results concerning the automatic continuity of {g, h}-derivations on Banach algebras. In the last section of the article, we introduce the concept of a {g, h}-homomorphism and then we present a characterization of it under certain conditions.

In this paper, we give a proof of the results of Miculescu and Mihail [J. Fixed Point Theory Appl. 19, 2153-2163 (2017)] and Suzuki [J. Inequal. Appl. 2017, Paper No. 256, 11 p.] in extended $b$-metric spaces. Also we give some applications of our result.

The growth amount of information on the Web makes it difficult for many web users to make decision and choose either information or goods. Thus, a recommender system is an approach that helps users to obtain their needs according to her/his preference within a massive amount of information rapidly without waste of time. The main advantage of using a recommender system in any online shopping or social media like Amazon, Netflix and Facebook is to increase the percentage of overall profits, customer satisfaction and retention. In this paper, we introduce an approach to increase the accuracy and to improve the performance of collaborative filtering recommender system. In this paper a hybrid approach is proposed to improve the performance of video collaborative filtering recommender system based on clustering and evolutionary algorithm. Proposed approach combines k-means clustering algorithm and two different evolutionary algorithms which are Accelerated Particle Swarm Optimization Algorithm (APSO) and Forest Optimization Algorithm (FOA). The main aim of this paper is to increase the accuracy of recommendation of user-based collaborative filtering video recommender system. Evaluation and computational results on the MovieLens dataset show that the proposed method has a better performance than the other related methods.

The sustainable development denotes the balanced status among various dimensions of development that aims to improve conditions of quality of life for the human. Urban sustainable development is deemed as the ideal objective for the planners and urban development directors in order to exploit suitably from the resources and to establish balanced relationship among human and community and nature. The present research mainly aims to extract and measure parameters of urban sustainable development in 4 regions in Aleshtar city (Lorestan Province- Iran). This study is an applied research in terms of goal and descriptive- analytical type in terms of methodology and based on librarian and field studies. The selected parameters were collected at two phases by study on backgrounds (research projects, statistical newsletters and books) and employing votes and comments from experts (using Delphi technique and extraction from comments of academic theorists and directors of relevant organizations) and they were merged together using Delphi technique. Parameters were weighted and analyzed by means of two models (TOPSIS and AHP-Fuzzy) after extraction and they were interpolated by GIS software and using Semivariogram tool. The research findings show that Region-3 has the highest rank (weight value= 0.627). After this region, Regions 2, 4 and 1 have devoted subsequent preferences with weighted values of 0.602, 0.578 and 0.541, respectively. Some strategies are suggested in order to moderate parameters of urban sustainability throughout regions of Aleshtar city including rising awareness of city dwellers about urban sustainable development plans, making the inhabitants familiar with parameters of a suitable city and creation and developing of a dynamic transportation system and establishing healthy housing in Regions 1, 2 and 4, increasing area of green space, establishing healthcare administration in Aleshtar Municipality and creating healthcare- medical institutes and centers etc.

The motor is the base of learning and mental processes. This shows the importance of motor impairment in people with specific learning disorder. The purpose of this study is to compare the grasping, pulling& releasing movements in children with specific learning disorder with normal children. The present study is descriptive, casual comparative (post facto), in terms of its methodology. The study population includes all elementary school students in Tehran, studying in the academic year of 2014-15. A sample of 40 children with specific learning disorder and 40 normal children is selected using available sampling method. Subjects are homogenized in terms of age and grade. Then the researcher-made test of fundamental movement is administered on them. Data are analyzed using multivariate analysis of variance. The findings show a significant difference in the grasping, pulling& releasing movements between two groups. According to the findings, it can be concluded that the grasping, pulling& releasing movements of children with specific learning disorder are defective compared to normal children. The first behavioral response of the child is a type of movement that is significant in the learning process. The fundamental movements of children with specific learning disorder are much different from that of normal children, the rehabilitation of which can improve the focus and attention of these children. Findings of the present study can be useful to psychologists, families and schools.

This study examines the identification of economic indicators (direct and indirect costs) of occupational accidents. The purpose of this study is to propose a structural equation model for the systematic management of incident costs. The research is applied-developmental design. The statistical population of the study was 10,000 experts in the oil, gas and petrochemical industries, 370 of whom were randomly selected using Morgan table. Thus, the researcher distributed 450 questionnaires, of which 384 questionnaires were analyzed. The research tools included the researcher-made questionnaires. In the first stage, this questionnaire was evaluated using fuzzy Delphi method and from 51 initial indicators, we reached 46 final indicators. Data analysis was performed using SPSS and SmartPLS software. The  results showed that emergency action  factors (dealing with incident / initial costs of accidents, costs of investigation and examination of accidents, costs related to damages and compensation, costs of work and incident (alternative costs of individuals), products production costs / service production, cost of marketing activities , retaining reputation and work credit, and finally the factor of restarting work activities are the ability to measure economic variables (direct and indirect costs) of occupational accidents. The fit indices of the model showed that the study model had acceptable fit.