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Heart disease is quickly becoming one of the most critical and widespread health concerns in the globe at the present time. At this time, a great deal of research is being conducted in an effort to treat a variety of cardiac conditions and a great number of lives. Because it enables medical practitioners to begin treating patients as soon as possible, early diagnosis of any heart illness is critical for this purpose. The purpose of this research is to develop a method that is capable of detecting coronary disease even before the onset of symptoms. After acquiring a data set consisting of highly processed ECG signal levels and other parameters that are required for the diagnosis of a variety of heart-related conditions, anomalies and outliers were eliminated from the data. One part of the dataset consisted of inputs classified as a category, whereas the other part consisted of inputs classified as binary. After that, we used the Keras framework to construct a deep learning model with three layers, and then we fed it the data set. The accuracy of the model with the binary data set was 93.89 percent, which is satisfactory given the modification made to this data set to include cancer cases in adults aged 18 to 77. In addition to the artificial neural network, a K-Fold Cross Validation model was developed and data was input into it. The accuracy of this model in diagnosing heart illness was 91.6 percent, which is quite good and helps in recognizing anomalies. This model also had a high success rate in identifying heart disease. As a result of advancements in technology, we are now in a position to diagnose illnesses and abnormalities of the heart in a greater population with greater precision [ABSTRACT FROM AUTHOR]

Over the past few decades, diesel engines are widely used in automobiles which is responsible for hazardous increase in pollution. Around the world, many countries are trying to reduce it by replacing diesel with CNG as a fuel which is more economical and leads to pollution free environment. Engineers came up with an idea to convert diesel engine to CNG engine. This conversion is possible by doing some alteration of engine components and it also include adding some extra components to the system which includes spark plug, valves etc. and by decreasing the compression ratio of the engine. It is used worldwide today and many countries have many programs to convert older, polluting diesel vehicles to CNG enable vehicles so that they can run on clean, economical natural gas. This is, an excellent way to reduce fuel cost, reduce pollution, reduce noise with minimum possible capital costs.first, second, and third level headings. [ABSTRACT FROM AUTHOR]

In this paper, we present the case of Estevan, an eighth-grader from Honduras whose interest in science lies primarily at the intersection of personal epistemology and identity. Drawing on video data from classroom interactions as well as interviews with Estevan and his teacher, Ms. K, we show how Estevan's passionate engagement in sensemaking about the seasons arose from an alignment between his epistemological stance that science involves figuring things out for yourself and his enacted identity as someone who faces challenges head-on. We use Estevan's case to highlight the importance of remaining open to the multiplicity of connections that might exist between interest in science and students' identities and to motivate looking deeper into such issues before prescribing how to engage students in science. [ABSTRACT FROM AUTHOR]