Moving object detection is an important step in any video surveillance system, tracking or video activity. This paper examines the result of the adaptive Gaussian Mixture Model using the Maximum A posterior (MAP) updates on video clips (dataset) obtained from Adeyemi College of Education Ondo, Nigeria. The results showed a reliable moving object detection algorithm, shadows constitute a problem, in that moving shadows can be mistaken as moving objects. The shadow was suppressed using the HSV and Phong illumination Model. The overall performance of this system was evaluated using the confusion matrix and the receiver operating characteristic (ROC), shadow detection and shadow discrimination values which showed a better result compared to existing benchmarks.
In recent years, Peer-to-Peer (P2P) streaming networks have been becoming popular because of not only fault tolerance, but also load balancing. However, in P2P streaming networks, there are some problems such as topology imbalance, interruption of streaming, latency in segment delivery, and degradation of received content caused by connecting low-performance nodes. Therefore, in this paper, we propose a new approach which reconfigures streaming networks dynamically using network motifs which can be used as an approach to characterize the complex networks, and evaluate our approach by simulation. The results indicate that our approach greatly decreases height and latency in generated trees, and provides an ability to reconfigure dynamically the network in case of predecessor's disconnection or defection. Moreover, our approach improves the quality of contents in a streaming network regardless of its network size.
The concept of generalized base space is given as a generalization of closure spaces, kernel spaces, topological spaces. The purpose of this paper is to study and investigate some separations axioms in the so-called generalized base spaces. Some characterizations of GBTi-spaces for i = 0, 1, 2, 3, 4 are obtained and some relations among these spaces are established. We study some results concerning separation axioms which are true in general topology, but it is not true in the generalized base spaces.
Transportation Problem (TP) is based on supply and demand of commodities transported from several sources to the different destinations. Usual methods for calculating initial basic feasible solution are North-West corner method, least cost method, row minima method/ column minima method, Russell’s method, Vogel’s approximation method etc. The transportation costs are considered as imprecise numbers described by fuzzy numbers which are more realistic and general in nature. Since the objective is to minimize the total cost or to maximize the total profit, subject to some fuzzy constraints, the objective function is also considered as a fuzzy number. The method is to rank the fuzzy objective values of the objective function by some ranking method to find the best alternative. On the basis of this idea method of magnitude ranking technique has been adopted to transform the fuzzy transportation problem and the initial basic feasible solution is found by Monalisha's Approximation Method (MAM'S).
This paper discussed a genetic algorithm based hybrid approach to solve different scenario (optimistic scenario, most-likely scenario and pessimistic scenario) of fuzzy multi-objective assignment problem (FMOAP) using an exponential membership function in which coefficient of the objective function is described by triangular possibilities distribution (TDP). Moreover, we used the α-level sets to classify the fuzzy judgment for Decision maker (DM) to optimize different scenario of fuzzy objective functions. We used a fuzzy technique to solve multi-objective optimization problem in which DM is required to specify the indistinct aspiration level as per the his/her preference and genetic algorithm is used to solve the 0-1 optimization problem for different choices of shape parameter in the exponential membership function. A numerical example is provided to demonstrate the effectiveness of the proposed approach with data set form realistic situation.
In this paper, we are interested in studying the stability of the equilibrium points of harvesting of a prey-predator system with time delay in the growth rate of the predator population. Firstly, we state the formulation of the model. Secondly, we drive different conditions stability of the equilibrium of the system, respectively. Constant effort harvesting of the prey has been incorporated in the model to cater for the effects of human poaching. Finally, we illustrate our results by some examples. The objective of this paper is to study the effects of harvesting and time delay on the dynamics of predator-prey system.
In this paper, we consider a new class of convex functions which is called λ-preinvex functions. We prove several Hermite-Hadamard type inequalities for differentiable λ-preinvex functions via Fractional Integrals. Some special cases are also discussed.