IEMS 2021

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    Theoretical study on instability of the base solutions of Lorenz system via Ordinary Differential Equations
    (Association for Industry, Engineering and Management Systems, 2021-03) Davani, Sina; Asmatulu, Ramazan
    The Lorenz system is well-known for producing chaotic solutions for a particular range of technical systems and process characteristics. To examine the instability, fluctuation parameters in the form of exponential functions are introduced to the base solutions of the ODEs, and numerical and computational methodologies are used to determine the range of values that cause instability under different conditions. This paper will focus on the Lorenz system's instability of Ordinary Differential Equations (ODE) that regulates the thermal-hydrodynamic behavior of a two-dimensional fluid layer which is equally warmed (distributed) from bottom to top. The boundary layer of instability is also examined and compared with numerical and computational methods, and the accuracy of the solutions is thoroughly investigated. The study will give considerable insight into the requirements for stability of numerous technical systems such as DNA analysis, chemical reactors, thermosyphons, Malkus waterwheel, electric circuits, DC motors, pipelines, and power generation using micro as well as nanoscale techniques.
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    Comparing the regional and international accreditation programs of NCAAA and ABET for undergraduate engineering education evaluations
    (Association for Industry, Engineering and Management Systems, 2021-03) Alarifi, Ibrahim M.; Rahman, Muhammad M.; Asmatulu, Ramazan
    This research study was focused on the accreditation of a local university and its programs during the 2017-2018 and 2018-2019 periods. Accreditation requires that the university be under the consideration by an autonomous agency for the quality assurance. Accreditation can be done for the entire institution or for individual programs within an institution. Accreditation is a voluntary process that many institutions go through with multiple steps. Usually, universities request accreditation agencies to assess their programs, faculty, and students' achievements to establish if they meet the quality requirements every six years. When requirements are met, the organization is regularly reassessed and accredited to make sure that the whole body persists in meeting the standards. Majmaah University (MU) of Saudi Arabia has been recently prepared for both regional (National Commission for Academic Accreditation and Assessment - NCAAA) and international (Accreditation Board for Engineering and Technology - ABET) accreditation programs. Most of the undergraduate engineering teaching programs were certified by both NCAAA and ABET. These accreditation programs have mainly similar outcomes although there were some small variations. This study provides the details on the similarity, differences, strengths, and weaknesses of the two accreditation systems and the required documentations to meet the accreditation criteria and demands.
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    LungStat: improving lung cancer diagnostic accuracy through computer vision
    (Association for Industry, Engineering and Management Systems, 2021-03) Sonawane, Kaustubh; Rai, Aditya
    Non-small cell lung cancer (NSCLC) results in over 1.8 million deaths worldwide every year; however, most of these deaths are preventable via early diagnosis, which reduces the mortality rate by more than 50%. Currently, physicians use a CT (Computed Tomography) scan as a preliminary method of identifying cancerous tumors. Unfortunately, this visual process of identifying NSCLC scans becomes time-consuming and inaccurate, leading to high misdiagnosis rates. The goal of this project is to create a cloud-based web application that can take an inputted CT scan and identify regions of potentially cancerous tumors at an accuracy >90%. This is accomplished by first standardizing all inputted scans to a standard size and range of pixel values. A 3D CNN is then trained to classify an inputted scan as either "positive" or "negative" for cancer. Class Activation Mapping (CAM) is then used on scans classified as "positive" in order to identify the location(s) of cancerous tumors. This algorithm core is accessed through a cloudbased user interface on AWS allowing physicians to upload and organize their patient's NSCLC scans as well as receive dynamic results based on patient biometric and cancer history background. Using the LungStat platform, an oncologist can simplify the procedure for lung cancer diagnosis by cutting down the average tumor identification time from about 1 hour to a few minutes. Overall, this project establishes a critical tool needed for the accurate diagnosis and treatment of NSCLC, leading to a severe reduction in the death rates caused by lung cancer.
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    A virtual STEM outreach program for elementary and middle school students during COVID-19
    (Association for Industry, Engineering and Management Systems, 2021-03) Shen, Anthony
    Gender inequality has been a persistent problem in higher education and industry in the STEM fields in the United States. While progress has been made in the last decade, there is a potential for increasing inequality in the time of COVID-19 with the inability to engage students in a face-to-face forum. In order to introduce elementary and middle school students to robotics and STEM, a monthly, virtual online outreach curriculum, mostly led by female students has been developed to stimulate student excitement and encourage girls to get involved in the fields of science and technology. Robotics is used as a conduit to teach and stimulate interest in STEM. A fun, hands on, and interactive curriculum for a series of educational online workshops has been developed, covering the engineering design process, competitive robotics, 3D CAD tutorial, programming, and robot mechanics. Our findings suggest that in elementary school, girls and boys are approximately equally interested in STEM. The outreach workshop appears to be a useful way to encourage and engage boys and girls in STEM virtually during COVID 19.
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    A brain computer interface system for the improvement of cognitive and communication abilities for patients with neuromuscular disorders
    (Association for Industry, Engineering and Management Systems, 2021-03) Ramakrishnan, Navya
    More than 16 million people in the United States are living with cognitive impairment. Reports suggest that 12,000-15,000 people have amyotrophic lateral sclerosis and approximately 17 million people have cerebral palsy, globally. The engineering goals are (i) to design an experimental study to analyze and improve cognitive performance and (ii) to develop a communication aid to support people with neuromuscular disorders using non-invasive brain-computer interface. A low-cost EEG device, Emotiv EPOC+ is used to record EEG data and a Python interface is used to stream the data for analysis. The features extracted are used to train the classifier, Linear Discriminant Analysis. The participants' cognitive performances were measured initially and after giving 20 days of feedback sessions with alpha-numeric speller. The performances were in the range of 76%- 81% initially and accuracy improved for all the participants and are in the range of 84%-89.3% after feedback sessions. The proposed feedback training design is an excellent way to improve cognitive abilities and can be used for healthy individuals as well as people with attention deficiency to improve their attention. A software application is developed to use the system as a communication aid for neuromuscular disorder patients who are unable to communicate. The accuracy in identifying the words of participants' choice are measured only using their brain activity. The communication aid was able to predict more than 91% of the words correctly. The system is low-cost and easy-to-use with a short setup time regardless of users' expertise.