“It’s finding those sponsors, it’s finding those mentors, it’s finding the advisors, and the people who believe in what you can do. While it started as an intimidating task to learn it all, I developed strategies for asking effective questions for my teammates, and we were all able to learn more as a result,” says Sierra. “This summer, I interned on a team that required me to learn a lot of new technology very quickly, including Amazon Web Services. It was also the first class where I had to learn a completely new programming language very quickly, and it helped me get a better understanding of what specific things to look for when you are trying to learn a new language,” says Ashmita. Through this class I learned that there are multiple approaches to solving common problems. It was a very interesting course because it was my first functional programming language, and it helped me think about traditional programming problems in a different way. “This semester, I took a course in functional programming using OCaml. Learning new technologies and programming languages are challenges in which both Ashmita and Sierra have been able to grow: ![]() And, you have to continuously apply those learnings to make sure that you are optimizing whatever you are doing,” says Priya. “Change is the only constant, but change happens only when you learn. Below are takeaways from this group of innovators with various backgrounds and experiences who recently gathered for a roundtable chat at the Society of Women Engineers (SWE) annual conference.įront Row (L-R): Priya Balasubramaniam, Maria Sanchez Lopez, Ashmita Sarma, Gulnaz Sayed, and Shreya Chowdharyīack Row (L-R): Zoe Husted, Natalie Broide, Hope Giles, Jillian MacGregor, Sierra Schultz, and Charlotte Thomasson Learn in Order to Grow When they both received the opportunity to meet up with fellow AiC Community members, Apple VP of Engineering Program Management Hope Giles, and Apple VP of Core Technologies and iPhone Operations Priya Balasubramaniam, they were delighted to discover common ground with others on learning from technological experiences and peers, as well as mantras that move them forward. Below is the fourth edition of “Innovator to Innovator,” where AiC Community Members Ashmita Sarma and Sierra Schultz talk to Apple VP of Engineering Program Management Hope Giles and VP of Core Technologies and iPhone Operations Priya Balasubramaniam about finding allies and mentors, growing from learning, embracing strengths, and more.Īspirations in Computing (AiC) Community Members Ashmita Sarma and Sierra Schultz not only marvel at the power of technology and how it works, but also strive to innovate with others. Therefore, the intended model is an alternative model for survival data and lifetime data analysis.Apple and NCWIT present a series of personal essays and stories of innovation, as told by NCWIT Aspirations in Computing (AiC) Community members by way of conversations with Apple executives. The finding of an order of COVID-19 deaths in 153 days in Nepal obey the proposed distribution, it has a significantly positive relationship between the predictive test positive rate and the predictive number of deaths per day. Here, a simulation study and two real data sets, “the number of deaths per day due to COVID-19 of the first wave in Nepal" and ‘‘failure stresses (In Gpa) of single carbon fibers of lengths 50 mm", have been applied to validate the different theoretical findings. The value of the parameters is obtained from the maximum likelihood estimation, least-square estimation, and Cramér-Von-Mises methods. Some important properties of the new distribution are derived such as quintile function and median asymptotic properties and mode moments mean residual life, mean path time mean deviation order statistics and Bonferroni & Lorenz curve. ![]() ![]() The proposed model is unimodal and positively skewed whereas the hazard rate function is monotonically increasing and inverted bathtubs. This study suggested a new four-parameter Exponentiated Odd Lomax Exponential (EOLE) distribution by compounding an exponentiated odd function with Lomax distribution as a generator.
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