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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]

Sociologists and historians of science/engineering have documented the salience of meritocracy and technocracy in engineering and engineering education (Cech, 2014; Slaton, 2015; Riley, 2008). Some engineering education scholars have begun to document how technocracy and meritocracy have been mechanisms of marginalization within engineering education (Slaton, 2015; Foor, Walden, & Trytten, 2007; Secules, Gupta, Elby, & Turpen, 2018). Our team has been engaged in the iterative redesign of a pedagogy seminar for engineering peer educators working within a college-level introduction to engineering design course. Using tools of discourse analysis, we analyze how technocratic stances are reproduced or challenged in engineering peer educators' talk during pedagogy seminar discussions. We study peer educators, in particular, because they are in a unique position to do harm if the ideologies of meritocracy and technocracy aren't challenged. Likewise, they are in a unique position to do good if they actively disrupt these ideologies in the introductory engineering design course. We present empirical examples of engineering peer educators both reproducing and contesting technocratic (and, at times, meritocratic) stances in reasoning about engineering education. We believe that such empirical examples can help engineering educators hone their attention to student thinking in the classroom and help us understand what it might look like to see evidence of growth in students' reasoning. [ABSTRACT FROM AUTHOR]

Engineering ethics curriculum and the research around it often emphasizes micro-ethical issues such as whistle-blowing and responsible conduct of research with lesser but growing attention to macro-ethical issues such as how engineering practice is entangled with broader social, political, economic, and environmental concerns. Engaging in macro-ethical reasoning often requires conceptualizing a wide range of stakeholders and their concerns, challenging one's beliefs about engineering as naturally leading to social good, and conceptualizing negative impacts of engineering work. There is still a paucity of research on the moment-to-moment dynamics and evolution of students' macro-ethical reasoning in sociotechnical contexts. In this paper, we present analysis of audio-video data from a series of focus group sessions in which engineering students discuss the ethics and ethical implications of a 2012 incident in which statisticians and engineers at Target developed predictive analytical software capable of identifying shoppers who were pregnant. We show how students' conceptualization of different stakeholders was relational, in that the ways in which pregnant women were conceptualized was entangled with how Target was conceptualized. We also argue that the way students construct various stakeholders over three focus group sessions constrained how they were able to understand any of the stakeholders as causing harm or being harmed. [ABSTRACT FROM AUTHOR]

Engineering ethics curriculum and the research around it often emphasizes micro-ethical issues such as whistle-blowing and responsible conduct of research with lesser but growing attention to macro-ethical issues such as how engineering practice is entangled with broader social, political, economic, and environmental concerns. Engaging in macro-ethical reasoning often requires conceptualizing a wide range of stakeholders and their concerns, challenging one's beliefs about engineering as naturally leading to social good, and conceptualizing negative impacts of engineering work. There is still a paucity of research on the moment-to-moment dynamics and evolution of students' macro-ethical reasoning in sociotechnical contexts. In this paper, we present analysis of audio-video data from a series of focus group sessions in which engineering students discuss the ethics and ethical implications of a 2012 incident in which statisticians and engineers at Target developed predictive analytical software capable of identifying shoppers who were pregnant. We show how students' conceptualization of different stakeholders was relational, in that the ways in which pregnant women were conceptualized was entangled with how Target was conceptualized. We also argue that the way students construct various stakeholders over three focus group sessions constrained how they were able to understand any of the stakeholders as causing harm or being harmed. [ABSTRACT FROM AUTHOR]

Learning Assistants (LAs) are undergraduate peer educators who participate in weekly pedagogy seminars and work alongside faculty instructors in active-learning based undergraduate courses. While LA programs were initially developed for science and math courses, many LA programs support LAs in a wide range of disciplines. This paper describes a pilot adaptation of the LA program for engineering design courses that we have developed at the University of Maryland, College Park Campus. All LAs assist in 14 separate sections of University of Maryland's engineering design course for first-year undergraduate students. Our seminar integrates topics from the discipline-general LA pedagogy seminar (cognitive science of learning, facilitation of classroom discourse, collaboration, metacognition) with topics especially relevant to engineering design (design reviews, design thinking, expert-novice practices in engineering design, engineering epistemology, teamwork and equity). While seminar goals aligned with the goals of LA programs nationally, our seminar design team also articulated several values which guided the design of our seminar: a) helping LAs reframe their role as supporting growth rather than evaluation, b) valuing a broad set of metrics of success from day one, c) celebrating that different students bring in different expertise, and disrupting overly simplistic expertise/novice dichotomies, d) acknowledging that we all have different starting points and valuing a plurality of goals, e) helping our students track their own progress through reflecting on concrete representations of their thinking, and f) supporting LAs in developing deep disciplinary knowledge of design thinking. This paper describes the embodiment of these goals by highlighting several key features of the seminar. We conduct quantitative and qualitative analysis of several data sources (surveys, instructor reflections, field notes, and coursework) to assess the extent to which the embodiment of our values helped us meet our goals. Finally, we describe challenges and identify areas where we were not meeting our goals and describe some of the aspects of the seminar that we plan to revise in the next iteration. [ABSTRACT FROM AUTHOR]

Engineering education research has started to attend to the idea that the education of a socially responsible professional engineer will, in part, require the weaving of social responsibility and engineering macro-ethics into the fabric of the engineering curriculum. In this paper, writing as an engineering design instructor, I present my own successes and challenges with incorporating notions of social responsibility and macro-ethics in an engineering design lesson. The lesson plan evolved over a period of 10 semesters. I document the process of that evolution and discuss how students' responses to activity prompts influenced that evolution. [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]