Open Access Short Research Article

Examining Factors Responsible for Students Poor Performance in Mathematics, from the Perspective of Teachers and Students at Asesewa Senior High School in the Upper Manyakrobo District

Patrick Akwasi Anamuah Mensah, Mercy Opokua Denteh, Ibrahim Issaka, Evelyn Adjaah

Asian Research Journal of Mathematics, Page 1-14
DOI: 10.9734/arjom/2022/v18i730386

The purpose of this study was to determine the factors that contributed to pupils' poor mathematics performance at Asesewa Senior High School in Ghana. The researchers therefore seek to investigate the extent to which learning resources availability and learning activities inhibit the performance of students of that district in mathematics. Because the purpose of the study was to acquire information from respondents on their experiences, perceptions, and opinions about students' low performance in mathematics at Asesewa Senior High School, the researchers utilized a descriptive survey approach. The researchers used a descriptive survey approach because the goal of the study was to gather information from respondents on their experiences, views, and opinions about pupils' low math performance at Asesewa Senior High School. As the only school in the Manyakrobo District, it was prudent for the researchers to use it for study. The total number of participants in the study was 250, and the study sample was made up of one hundred and sixty-five (165) students and mathematics teachers of Asesewa Senior High School. Data was obtained through questionnaire distribution and was then analyzed with the help of SPSS. It was discovered that resources were accessible and that they could not be blamed for the drop in student mathematical performance. The survey also found that there was no significant variation in perceptions of resource availability and learning activities between males and females in terms of gender among teachers and students.

Open Access Original Research Article

Hidden Markov Model of Disease Progression and Control with Reference to COVID-19 Spread

Tirupathi Rao Padi, V. Kanimozhi, P. T. Sakkeel

Asian Research Journal of Mathematics, Page 15-31
DOI: 10.9734/arjom/2022/v18i730387

Disease progression studies through stochastic modeling are the most effective approaches as different processes involved in the disease acquisition, growth, spread, and control are random. This study develops a stochastic model for studying the disease spread using Markov Processes (MP) and Hidden Markov Models (HMM). This study considered two states of illness under the categories of hidden and visible. Further hidden states, as well as visible states, are classiffed into two groups each. This study attempted to relate the spread of disease in Tamil Nadu and Puducherry and its neighboring states. Increment/Decrement in daily positive cases of Tamil Nadu and Puducherry in uence the Increment/ Decrement in neighboring states' daily positive cases, assuming there are regular transitions of patients from one place to another. This study develops HMM for transitions among different states (Increment/Decrement) for understanding the dynamics of positivity for two consecutive days and three days. Probability distributions of the prevalence of positivity are derived from the developed transition probability matrices. The study further derived different statistical measures mathematical/ functional relations through the parameters under consideration. This study will help to measure the severity of the disease spread. The development of an interactive user interface for healthcare management will be the scope of this study.

Open Access Original Research Article

Effects of Social Media in Controlling Tungiasis: Mathematical Model

Calvet Night, David Ambogo, Daniel Achola

Asian Research Journal of Mathematics, Page 32-46
DOI: 10.9734/arjom/2022/v18i730388

In this paper, a deterministic model incorporating social media in controlling tungiasis disease is considered. The model is shown to be positively invariant as well as bounded. We showed that the model has two equilibria points: disease free and endemic equilibria points. In both cases, the steady states are locally asymptotically stable provided the basic reproduction number is less than unity.

Open Access Original Research Article

Eliminate the Nonlinear Oscillations of the Modified duffing Equation by using the Nonlinear Integrated Positive Position Feedback

Hanan Ahmed Abed Rahman

Asian Research Journal of Mathematics, Page 47-62
DOI: 10.9734/arjom/2022/v18i730389

In this article, the nonlinear integrated positive position feedback (NIPPF) control adds to a nonlinear dynamical system modeled as the well known Duffng oscillators. This control is proposed to mitigate system nonlinear vibrations. The whole system mathematical model is analyzed by applying the multiple time scales perturbation method. The slow- ow modulation equations that govern the oscillation amplitudes of both the main system and controller are derived. The stability of the steady-state solution is presented and studied applying frequency response equations near the simultaneous primary and internal resonance cases. Before and after (NIPPF) control the nonlinear systems' steady-state amplitude are examined, the comparison is made to validate the closeness between the numerical solution and the analytical perturbative one at time-history and frequency response curves.

Open Access Original Research Article

On a Question of Constructing Mӧbius Transformations via Spheres and Rigid Motions

P. G. R. S. Ranasinghe, R. A. S. T. Abeysekara

Asian Research Journal of Mathematics, Page 63-68
DOI: 10.9734/arjom/2022/v18i730390

A Mӧbius Transformation or a Fractional Linear Transformation is a complex-valued function that maps points in the extended complex plane into itself either by translations, dilations, inversions, or rotations or even as a combination of the four mappings. Such a mapping can be constructed by a stereographic projection of the complex plane on to a sphere, followed by a rigid motion of the sphere, and a projection back onto the plane. Both Mӧbius transformations and Stereographic projections are abundantly used in diverse fields such as map making, brain mapping, image processing etc. In 2008, Arnold and Rogness created a short video named as Mӧbius Transformation Revealed and made it available on YouTube which became an instant hit. In answering a question posted in the accompanied paper by the same name, Siliciano in 2012 showed that for any given Mӧbius transformation and an admissible sphere, there is exactly one rigid motion of the sphere with which the transformation can be constructed. The present work is prepared on a suggestion posted by Silciano in characterizing rigid motions in constructing a specific Mӧbius transformation. We show that different admissible spheres under a unique Mӧbius transformation would require different rigid motions.

Open Access Original Research Article

Application of Stacking-Based Ensemble Learning Model for Water Quality Prediction

Longfeng Zhang, Yiqi Yang, Yanqiao Deng, Hao Kang, Tingting Hua-ng

Asian Research Journal of Mathematics, Page 69-79
DOI: 10.9734/arjom/2022/v18i730391

Water is the source of life, and the growth of animals and plants cannot leave the water source. The quality of water will directly affect the life and health of humans, animals and plants. In order to predict the concentration and changing trend of various pollutants in water bodies and promote the comprehensive management of water resources, this paper proposes a new integrated model based on the idea of Stacking integrated learning. The model is based on XGBoost, support vector regression, and multi-layer perceptron. The model is constructed with ridge regression as the meta-model. The model was applied to the pH and total nitrogen content of water quality, and the mean absolute percentage error was used to quantitatively evaluate the prediction results, and the results of the ensemble learning model were compared with the prediction results of a single base model. The results show that the stacking ensemble learning idea can effectively improve the prediction ability and generalization performance of the base model. The proposed ensemble learning model has very good prediction ability and generalization ability, and has great potential in other prediction fields such as water quality.