Aims: To provide an alternative definition for subset Sarima modeling and demonstrate it by application to monthly internally generated revenue of Ikot Ekpene Local Government Area of Akwa Ibom State of Nigeria. Study Design: The study design is theoretical as well as empirical. Place and Duration of Study: Department of Mathematics and Computer Science, Rivers State University of Science and Technology, Port Harcourt, Nigeria. Methodology: Based on the duality relationship between autoregressive (AR) and moving average (MA) models an alternative definition to subset sarima models is proposed. The seasonality of the above-mentioned time series is established. A non-seasonal differencing of the seasonal difference of the series yields a stationary series which is analysed by Sarima methods. Results: Applying the duality relationship between AR and MA models, subset Sarima models may be defined in AR terms rather than exclusively in MA terms as earlier done. An analysis of a 120-point internally generated revenue series from 1998 to 2007 yields the additive model from the original SARIMA (1, 1, 0)x(1, 1, 0)12 model. The additive model is found to be adequate. Conclusion: Based on the new and equivalent definition the monthly internally generated revenue of Ikot Ekpene Local Government Area of Nigeria follows an additive Sarima Model.
Various genome evolutionary models have been proposed these last decades to predict the evolution of a DNA sequence over time, essentially described using a mutation matrix. By essence, all of these models relate the evolution of DNA sequences to the computation of the successive powers of the mutation matrix. To make this computation possible, hypotheses are assumed for the matrix, such as symmetry and time-reversibility, which are not compatible with mutation rates that have been recently obtained experimentally on genes ura3 and can1 of the Yeast Saccharomyces cerevisiae. In this work, authors investigate systematically the possibility to relax either the symmetry or the time-reversibility hypothesis of the mutation matrix, by investigating all the possible matrices of size 2Χ2 and 3Χ3. As an application example, the experimental study on the Yeast Saccharomyces cerevisiae has been used in order to deduce a simple mutation matrix, and to compute the future evolution of the rate purine/pyrimidine for ura3 on the one hand, and of the particular behavior of cytosines and thymines compared to purines on the other hand.
This paper presents dynamic reorganization of peer-to-peer networks to make query routing and content retrieval efficient. The reorganization is conducted which use content similarity information. Unlike other related studies using semantic proximity, the method proposed in this paper relies on folksonomy, which gained wide use in figuring out content similarity in various social networks. The proposed method is designed primarily for flooding-based unstructured P2P networks, however it also can be applied to structured P2P networks such as Tapestry. Simulation-based experiments confirm the effectiveness of the proposed method.
We study an initial value problem for a class of integro-differential equations of Volterra type in a real Banach space. Using method of upper and lower solutions and M¨onch and Von Harten theorem, we obtain an existence theorem of coupled quasi-solutions, which is an extension of those established by Y. Chen and W. Zhuang in .
In this paper, some new generalized retarded nonlinear integral inequalities of Gronwall-Bellman type are discussed. The upper bounds estimation of the embedded unknown functions are discussed by integral and differential techniques. Our results generalize some inequalities of H. El-Owaidy et al.  with both retard and nonlinear integral. Some applications are also presented in order to illustrate the usefulness of some of our results.
The existence of nonoscillatory solutions of a class of higher order forced neutral dynamic equations with time delay on time scales is discussed. The main tool is the Banach fixed point theorem. Based on the different values of p(t), we give several existence theorems of nonoscillatory solutions of our discussing equations. An example is also presented to illustrate the applications of the obtained results.
This paper presents a mathematical model (with computer simulation) for forecasting the profits of buying software for the automation of established processes in the Nigerian University System. The mathematical model uses certain assumptions to provide a basis for iterative estimation of future income and the obtained results are intended to assist the management and stakeholders in deciding if investing in a software project is worthwhile.
In this paper, an effective formulation of the variational iteration method is suggested for solving Bratu equation arising in electro-spinning. The suggested formulation depends on embedding a nonzero auxiliary parameter that controls the solution convergence region. An alternative formulation of the Bratu equation is suggested as well. The proposed formula eliminates the complexity that appears when solving using the standard variational iteration algorithms illustrated in [1,2] without approximating the exponential term. A suitable choice of the auxiliary parameter results in an accurate approximation compared with the approximation of the standard variational iteration method.
The state estimator is integral part of any Energy Management System. First and foremost the state estimation must be executed followed by system control, tie-line control, economic dispatch, security analysis etc. Most importantly the system voltage controls and the tie-line power controls must be handled within milliseconds to a few seconds. Obviously, in order to meet the requirements, state estimator should be able to process the results very fast. Due to the kind of complexity associated with the power system it’s very difficult to carry out the estimation in very short time. The author, H.N. Udupa & Dr. H.R. Kamath [1,2] had suggested a new innovative method to solve this complex problem in desired time without compromising on the results accuracy. In the said new approach, State Estimations are computed at each Node level. This paper presents a unique technique to carried-out the State Estimation at selected Node Areas instead of every Node Area. As the network is interconnected, by selecting suitable Node Area it is possible to estimate all the state variables of the system. The method of selecting the Node Area is detailed in this paper. A node/bus along with its connected nodes/buses is called “Node Area”. By computing the SE only at Selected Nodes reduces the complexity of the system and also results in huge cost saving. The Node Area level of state estimation technique is suitable for smart grid application. This paper presents the Node Area selection technique along with its computational time and comparison with the conventional Integrated State Estimation (ISE) and Node Level State estimation.`