BackgroundMalarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM).MethodologyEpidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis.Results/FindingsPerennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission.Conclusions/SignificanceChanges in climatic factors influence malaria directly by modifying the behaviour and geographical distribution of vectors and by changing the length of the life cycle of the parasite.
This paper proposes an adaptive and interactive agent based intelligent tutoring system for cognitive ability realization and improvement (ITSCARE - Intelligent Tutoring System for Cognitive Ability Realization and Improvement). ITSCARE allows the learners to realize their cognitive ability and to improve their cognition while studying the course. It provides different types of course materials which are dynamically adapted. It also increases the confidence level of the learners and provides an effective learning experience. This system also provides game based learning which influences the learners to get motivated and focus on the course. After the completion of each chapter, a test is conducted to predict the cognitive ability where students are assessed using their help seeking skills during the test and cognitive skill factors such as memory, concentration, attention in detail etc,. It uses politeness style to provide the test results and feed back to the students which keep the learner interest in the subject. Collaborative learning among the learner is improved by conducting quiz competition where a group of students participate and a winner is chosen. It uses different type of software agent to predict and improve the cognitive skill.
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