Abstract: Publication date: May 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 3 S. Jahan Personal identification or verification is a very common requirement in modern society specially to access restricted area or resources. Biometric identification specially faces identification or recognition in a controlled or an uncontrolled scenario has become one of the most important and challenging area of research. Images often are represented as high-dimensional vectors or arrays. Operating directly on these vectors would lead to high computational costs and storage demands. Also working directly with raw data is difficult, challenging or even impossible sometimes. Dimensionality reduction has become a necessity for pre-processing data, representation and classification. It aims to represent data in a low-dimensional space that captures the intrinsic nature of the data. In this article we have applied a Supervised distance preserving projection (SDPP) technique, Semidefinite Least Square SDPP (SLS-SDPP), we have proposed recently to reduce the dimension of face image data. Numerical experiments conducted on very well-known face image data sets both on gallery images and blurred images of various level demonstrate that the performance of SLS-SDPP is promising in comparison to two leading approach Eigenface and Fisherface. PubDate: May 2018

Abstract: Publication date: May 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 3 Aydin Teymourifar Gurkan Ozturk and Ozan Bahadir Many evolutionary algorithms have been used to solve multi-objective scheduling problems. NSGA-II is one of them that is based on the Pareto optimality concept and generally obtains good results. However, it is possible to improve its performance with some modifications. In this paper, two modified NSGA-II algorithms have been suggested for solving the multi-objective flexible job shop scheduling problem. The neighborhood structures defined for the problem are integrated into the algorithms to create better generations during the iterations. Also, their initial populations are created with an effective heuristic. In the first modified NSGA-II, after the creation of the offspring population, a neighbor of each individual in the parent population is constructed, and then one of them is selected according to the domination state of the solutions. Then the populations are merged to create a new population. In the second modified NSGA-II, only the solutions on the first and second fronts of the parent population and also their neighbors are merged with the offspring population. Other operators of the algorithms like the non-dominated sorting and calculating the crowding distances are as the classic NSGA-II. A comparison is done with a classic NSGA-II based on two metrics. The results show that as it is in the first modified NSGA-II, including neighbors of more individuals of the population provides better results because it increases diversity and intensity of the search. The performance of the second modified NSGA-II is almost similar to the NSGA-II. So, it can be concluded that although integrating the neighborhood structures can improve the performance of search, it is better to define that the structures should be applied to how many and which solutions, in otherwise the quality of search may not increase. PubDate: May 2018

Abstract: Publication date: May 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 3 Şule Çürük and Serpil Halici In this study, we investigate Fibonacci quaternions and their some important properties. Then, we define a special sequence using the elements of the Fibonacci quaternion sequence. Furthermore, we calculate the autocorrelation, right and left periodic autocorrelation values by using the elements of the newly defined sequence. PubDate: May 2018

Abstract: Publication date: Mar 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 2 Mehmet Alegoz and Zehra Kamisli Ozturk In this study, we focus on designing the supply chain network of a company that sells households goods to its customers located in various cities of Turkey. Since the production plant of the company is fixed and cannot be changed, we divide the supply chain network design problem into two separate problems. In first problem, we focus on the network between the supplier and the production plant. This problem can be thought as a supplier selection problem and there are many qualitative and quantitative criteria, which affect this process. Therefore, we use Buckley's Fuzzy AHP algorithm, which enables us to evaluate the suppliers according to all types of criteria. In second phase of the study, we focus on the supply chain network between the production plant, warehouses and customers and develop a multi objective mathematical model. Although, the proposed mathematical model gives optimal solution for our company data within a reasonable time, large size instances cannot be solved by using this model due to the complexity of problem. For this reason, we propose various metaheuristic approaches based on tabu search and compare the results with optimal solution. Computational results show that one of our approaches gives high quality results within a reasonable time. We conclude the study by discussing the numerical results and giving some future work suggestions to interested readers. PubDate: Mar 2018

Abstract: Publication date: Mar 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 2 Abir Kessebi and Bahri Rezig Current researches on wireless sensor networks (WSN) are focusing on reducing the total amount of energy consumption and extending the network lifetime. WSN have many application fields like industry, health care, commercial and residential applications. The main goal of this paper is to evaluate, using MATLAB/Simulink simulations, the average amount of energy consumed in a WSN based on a clustering topology; to predict the optimal number of clusters in order to optimize the energy and also to study the cloud integration effects on lifetime and energy time dependency. The clustering topology is based on defining K clusters with N/k nodes, each node transmits data to the cluster head which will collect data from all of its own nodes, compute it and send it to the base station (BS). In our simulation, we have focused on many principal metrics in WSN such as optimal number of clusters, duty cycle, lifetime and distance to BS. Finally we have studied the effect of integrating cloud into classic WSN, the effect in terms of energy consumption and sensor node lifetime. PubDate: Mar 2018

Abstract: Publication date: Mar 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 2 David Blackman Hon. In aerodynamics, there are two types of surfaces: stiff and flexible. Stiff surfaces may gain energy from differential wind velocity on opposite sides of the particle. Flexible surfaces dissipate such energy through flutter i.e. like the tail of a kite. Kites have two components, the airfoil and the tail. Airfoils provide lift for the kite through the differential air currents. In such a dichotomous world the Ebola virus resembles the tail of the kite as opposed to the airfoil. One would expect the Ebola virus to flutter and fall. Through mathematical analysis of the electron micrograph it is concluded that the virus is not airborne, but it is probably waterborne. PubDate: Mar 2018

Abstract: Publication date: Jan 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 1 Hüseyin Oğuz and Elçin Yusufoğlu In this study, a numerical solution of elasticity problem is examined. This problem is a plane contact problem. The frictional contact problem for an elastic strip under a rigid punch system is considered. The frictional contact problem is related to infinite length elastic strip in contact with N punches under the influence of horizontal and vertical forces. The lower boundary of the strip is hinged. The solution of contact problems is often reduced to the solution of an integral equation. This integral equation system can be derived from contact problem by using the basic equations of elasticity theory and the given boundary conditions. The singular integral equation system is solved with the help of Gauss Jacobi Quadrature Collocation Method. The frictional contact problem for a homogenous and orthotropic elastic layer are investigated numerically the pressure distribution under the punch system due to the geometrical and mechanical properties of elastic layer are examined and the results are shown in the graphics and tabular form. PubDate: Jan 2018

Abstract: Publication date: Jan 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 1 G.P. Vinogradov The problem of constructing a choice model of an agent endogenously shaping purposes of his evolution is under debate. It is demonstrated that its solution requires the development of well-known methods of decision-making while taking into account the relation of action mode motivation to an agent's ambition to implement subjectively understood interests and the environment state. The latter is submitted for consideration as a purposeful state situation model that exists only in the mind of an agent. It is the situation that is a basis for getting an insight into the agent's ideas on the possible selected action mode results. The agent's ambition to build his confidence in the feasibility of the action mode and the possibility of achieving the desired state requires him to use the procedures of forming a model-representation based on the measured values of the environment state. This leads to the gaming approach for the choice problem and its solution can be obtained on a set of trade-off alternatives. PubDate: Jan 2018

Abstract: Publication date: Jan 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 1 Cansel Yormaz Serife Naz Elmas and Simge Simsek In this article, firstly we study about geometrical applications of split quaternions. Then, we obtain Hamitonian mechanical systems with Split quaternions. Quaternionic and Coquaternionic (split analoque of quaternions) extensions of Hamiltonian mechanics are introduced and are shown as offer a unifying framework for quantum mechanics. This study leads to the possibility of employing algebraic techniques of quaternions and coquaternions to absorbing in quantum mechanics. The founded equations are compared with the Hamiltonian energy equations generally are known and the Hamilton energy equations are obtained in Minkowski space. PubDate: Jan 2018

Abstract: Publication date: Jan 2018 Source:Universal Journal of Applied Mathematics Volume 6 Number 1 Aydin Teymourifar and Gurkan Ozturk In this paper, a hybrid method is proposed to generate feasible neighbors for the flexible job shop scheduling problem. Many of the optimization and artificial intelligence methods have been used to solve this important and NP-hard combinatorial problem which provides the basis for solving real-life problems. It is well-known that for such problems the hybrid methods obtain better results than the other approaches. For instance, the applied non-hybrid neural networks for the combinatorial problems, as the Hopfield neural network, usually converge early. Also, their results almost always contain large gaps. These shortcomings prevent them to find good results. Another necessity for a quality search is to find suitable neighbors of the obtained solutions; however, it is possible to create infeasible neighbors during the optimization process. The aim of this study is to overcome these deficiencies. In the suggested approach, at first, an initial solution is generated and then using the left shift heuristics, its gaps are removed. Based on the critical path and critical block concepts, 6 neighbors are constructed for the obtained solution. After the generation of each neighbor, a neural network runs and controls the constraints of the problem. If the achieved neighbor is feasible it is saved. Else if it is infeasible, the neural network tries to transform it into a feasible solution. This is done by applying penalties to the start time of the operations on the violated constraints, which shifts them to the right or the left. During this process, if there are not any violated constraints, the neural network reaches the stable condition so it stops and the obtained solution is saved as a feasible neighbor. Otherwise, after a certain number of the iterations, it stops without any feasible neighbors. Then these steps are repeated for the other created neighbors. This constraint-based process provides an effective and diverse search. Finally, the obtained neighbors, are improved using the left shift heuristics. Also to demonstrate the importance of the initial solutions, they are generated randomly and also using the Giffler and Thompson's heuristic. The comparison between the proposed approach and the methods from the literature shows that it constructs better neighbors. However, using the Giffler and Thompson heuristic to create the initial solution improves the results significantly. PubDate: Jan 2018