Open Access Original Research Article

Time Series Modeling and Forecasting of Consumer Price Index in Ghana

Aabeyir Boniface, Anokye Martin

Journal of Advances in Mathematics and Computer Science, Page 1-11
DOI: 10.9734/jamcs/2019/v32i130134

The knowledge of economic and financial indicators is the basis of making right decisions and sound judgment with respect to investment and allocation scare of resources. Such important indicators include the consumer price index, which measures the change in the prices paid by households for goods and services consumed. A trigger in the consumer price in Ghana causes inflation which affects the purchasing power of its citizens. Knowledge of the trend of the CPI is crucial in economic planning. The study therefore sought to construct the appropriate time series model for the CPI and then use the model to predict the next nine months CPI. The study further sought to determine the type of trend model that characterizes the CPI. The Box-Jenkins methodology was adopted. The results of analysis showed SARIMA(2, 1, 1)(1, 0, 0)12 as most fitted time series model and was used to predict the consumer price index for the next nine months. The S-model was also found to be the appropriate trend model for the CPI. The SARIMA (2, 1, 1)(1, 0, 0)12 is recommended for forecasting consumer price index in Ghana.

Open Access Original Research Article

An Investigation of the Use of Eigen Values in Human Face Modeling for Recognition Tasks

Emad F. Khalaf

Journal of Advances in Mathematics and Computer Science, Page 1-9
DOI: 10.9734/jamcs/2019/v32i130135

The face image modeling by eigenvalues is not a new track in the literature. However, a much complete study is required to achieve a comprehensive investigation of the topic. In this research paper, an experimental methodology is conducted for studying the different alternatives of utilizing the eigenvalues for human face recognition. For a better universal investigation, three popular databases are tested; Orl_faces, extended Yale face_A, and extended Yale face_B datasets. The main objective of the study is to find the best choice of using eigenvalues (EV) in face recognition. The technique of the moving average filter (MAF) is combined with that of eigenvalues to enhance the results. Probabilistic neural network (PNN) is used for classification. Three methods of this concept were developed as follows: EV, EV with MAF, and MAF alone. The elapsed time was tested, where for moving average filter was distinctly smaller than the other two methods. For the Yaleface_B database, the eigenvalues method was superior for each of the three training/testing systems. The results were enhanced after using different filters instead of a direct moving average filter to make the proposed method the superior again. The study proved the possibility of using eigenvalues in conjunction with a suitable filter to get acceptable results for all types of image limitations. The concluded ideas elicited from the study spot the light on the usefulness of utilization of eigenvalues in the face recognition tasks.

Open Access Original Research Article

Open Access Original Research Article

Design and Implementation of a Fuzzy Expert System for Diagnosing Breast Cancer

F. M. Okikiola, E. E. Aigbokhan, A. M. Mustapha, I. O. Onadokun, O. A. Akinade

Journal of Advances in Mathematics and Computer Science, Page 1-14
DOI: 10.9734/jamcs/2019/v32i130137

The death rate is caused by breast cancer in women is increasingly high and growing. A number of people are getting to lose this part of their body due to late diagnosis of this disease. This therefore requires the development of an efficient and accurate diagnosis approach that will aid providing the knowledge of the type of breast cancer type and severity in order to reduce the mortality rate through the disease. This need serves as the major motivation for this work. In this paper, we proposed a fuzzy expert system for diagnosis of and treatment recommendation of breast cancer problems which provide physicians and patients with information of the cancer type and treatment recommendation. The application was designed using JAVA programming language, MATLAB and SQLite database engine. This application permits update of new information as a means of knowledge. The evaluation showed that the inclusion of the fuzzy inference system improved the accuracy and precision of the system from 0.8 to 0.9. The system is user-friendly and has high level of acceptability from the validation conducted at the end of the research.

Open Access Original Research Article

The Algebraic-Function Congruences on Distributive Lattices

Wei Ji

Journal of Advances in Mathematics and Computer Science, Page 1-7
DOI: 10.9734/jamcs/2019/v32i130138

We propose the Chinese Remainder Theorem in distributive lattices and apply the results to investigate the congruences induced by algebraic functions on distributive lattices. It is shown that the congruence induced by an algebraic function preserves abutment relationships in distributive lattices.