Center for Advanced Studies in Engineering

About: Center for Advanced Studies in Engineering is a based out in . It is known for research contribution in the topics: Project management & Routing protocol. The organization has 319 authors who have published 333 publications receiving 2925 citations.

Prediction of Diabetes Using Machine Learning Algorithms in Healthcare

Abstract: There are several machine learning techniques that are used to perform predictive analytics over big data in various fields. Predictive analytics in healthcare is a challenging task but ultimately can help practitioners make big data-informed timely decisions about patient's health and treatment. This paper discusses the predictive analytics in healthcare, six different machine learning algorithms are used in this research work. For experiment purpose, a dataset of patient's medical record is obtained and six different machine learning algorithms are applied on the dataset. Performance and accuracy of the applied algorithms is discussed and compared. Comparison of the different machine learning techniques used in this study reveals which algorithm is best suited for prediction of diabetes. This paper aims to help doctors and practitioners in early prediction of diabetes using machine learning techniques.

Does corruption affect economic growth

Abstract: Using panel data from the International Country Risk Guide corruption index, institutional quality and political stability indices and several state variables for developed and developing countries, this paper explores the linear quadratic empirical relationship between corruption and economic growth. Empirical literature has shown a linear relationship between corruption and economic growth but hasn’t dif ferentiated between growthenhancing and growth-reducing levels of corruption. An analysis based on the generalized method of moments estimation shows that a decrease in corruption raises the economic growth rate in an inverted U-shaped way. This result is robust with respect to alternative specifications of the econometric relationship.

Agile software development: Impact on productivity and quality

Abstract: Agile means swift, active and responsive and this is what agile software development methodology refers to. Agile software development methodologies are widely accepted these days. It is an iterative approach to keep pace with dynamic development environments. Traditional software development methods are not efficient enough to convene with the rapid change in requirements and short iterations that are required for efficient product delivery. This study contains a quantitative analysis of the agile methodologies in practice, and the benefits associated with them. Analyses are done on a defined set of attributes that result in increased productivity and improved quality through the application of these methodologies. A development model has also been derived from empirical research conducted in this paper.

Estimation of Gasoline-Engine Parameters Using Higher Order Sliding Mode

Abstract: Automotive-engine control and fault diagnostics largely depend upon the accuracy of the nonlinear models used. The structure of these nonlinear models is generally agreed upon. However, the model parameters are mostly difficult to obtain. This paper presents the development of second-order sliding-mode technique with real twisting algorithm for estimation of more than one parameter from a single dynamical equation of the nonlinear model. The system under study is a mean-value engine model of a naturally breathing gasoline engine. The parameters estimated are throttle body's discharge coefficient, load torque, and indicated torque as a function of inlet manifold pressure. The estimated variables are used to compensate for the unmodeled dynamics, modeling inaccuracies, and approximations which arise from the assumptions made for the development of mathematical model of a real-world system. The resulting model is a better description of the actual engine dynamics and gives good agreement to real engine data. The data are acquired from a production model vehicle equipped with an electronic control unit compliant to OBD-II standard. The observer designed is simple enough for implementation, and estimated parameters can also be used for engine-controller design and fault-diagnosis work.