Category Archives: Computer Science
On the ‘edge’ of a break through: Clemson University researchers … – Clemson News
September 18, 2023September 14, 2023
Cameras positioned at a bustling intersection spot a pedestrian crossing the street as a self-driving car, out of sight around a curve, approaches in her direction.
To avoid a collision, data from the cameras has to be processed into actionable information that can be sent blazingly fast to the car, but how?
A group of Clemson University researchers led by Associate Professor Linke Guo said the answer could lie in edge computing, a new way of processing and moving data at lightning speed.
Edge computing gives the internet the ability to understand and interact with its immediate surroundings, without having to send large amounts of data to far-away computer centers.
The fates of several futuristic technologies hang in the balance as Clemson researchers work to break ground in the field. It could help make cities smarter, manufacturing more advanced and healthcare more connected, researchers said.
Edge computing will be a key enabler of many technologies, Guo said. Its a pivotal step toward creating a future that will result in applications that are faster, more efficient and more secure. I am excited about our work because we stand at the cusp of more seamlessly integrating data into our daily lives, which will come with a host of benefits.
Edge computing would complement and improve on cloud computing, the current standard for sharing and processing data.
In cloud computing, data is stored on a centralized server, often hundreds of miles from application users, and they access it through computers, such as smartphones and laptops. For example, when someone streams a video on YouTube or Netflix, thats the cloud at work.
But researchers said data is going to have to be processed faster to enable future technologies.
Every fraction of a second counts. For instance, if cameras take several seconds to send data about the pedestrian to the cloud, process it and relay the information to the car, the delay could spell disaster.
Edge computing aims to speed up the data processing by employing devices in the immediate vicinity of where the data is needed. Those devices could include everything from personal smartphones and connected cars to smart thermostats and local servers.
Its called edge computing because data is stored and processed at the edge of the cloud without having to make the leap to the cloud.
The Clemson group is working to use a form of machine-learning artificial intelligence called federated learning to boost edge computings potential. Those algorithms would help devices involved in edge computing get smarter without sending data to a centralized server, making computing faster and more secure.
As part of their work, researchers are tackling the problem of heterogeneous data. Some devices have lots of data but missing pieces, while others have different strengths and speeds, making coordination a challenge. The Clemson group aims to develop a new system called Harmonious Federated Intelligence to get the devices working together.
Guo is working with Assistant Professor Xiaolong Ma, Associate Professor Jon Calhoun, Professor Tao Wei and K.C. Wang, professor and the C. Tycho Howle Endowed Chair. All are on the faculty of the Holcombe Department of Electrical and Computer Engineering.
They are receiving funding for their work through the National Science Foundation. Among their partners is Xiaonan Zhang, who is Guos former Ph.D. student and is now an assistant professor of computer science at Florida State University.
Several students are also involved in the research, helping shape the future edge-computing workforce.
Im really interested in machine learning, said Ruiwen Shan, a Ph.D. student in Calhouns group. Its a hot topic these days, but I havent had a chance until now to look deep into it. This will be a great experience for me.
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On the 'edge' of a break through: Clemson University researchers ... - Clemson News
Howard’s New Science Program is Training the Next Data Activists – The Hilltop Online
Data science is an interdisciplinary field that allows for the use of the scientific method, algorithms and more to extract insight and make data-driven conclusions to solve some of the worlds most complex problems. (Photo courtesy of Adobe Stock images)
Integrating data science with social justice is what Howards new Masters in Applied Data Science graduate program hopes to accomplish. The fully online program intends to teach students how to use data to improve social and environmental conditions.
The program, which began this fall within the Center for Applied Data Science, aims to provide a new stance when it comes to considering the impact of data science on wider social issues such as health disparities, environmental injustice and economic disempowerment, according to the website.
The program comes about after Howard Universitys partnership with Mastercard, which included a $5 million grant that funded the centers establishment. The partnership aims to drive racial equity through data science, according to Mastercard.
Amy Yeboah, Ph.D. graduate director of the Masters in Applied Data Science program, emphasized the uniqueness of the programs standpoint within the data science field. Yeboah, who spent 10 years teaching African American studies at Howard, began to pivot her focus towards data science at the heart of the COVID-19 pandemic, being witness to the effects that it had brought to people like her.
Seeing the impact of COVID on Black communities allowed Yeboah to gain a new perspective on the nature and implications of Artificial Intelligence. I had seen that computer science, data science, AI specifically, was beginning to disproportionately impact Black and Brown lives, Hispanic lives and American lives, she said.
Nationwide, Black or African American data scientists make up 4.2 percent of the whole, according to Zippia, with White and Asian demographics making up a much larger proportion of the total at 64.2 percent and 18.8 percent.
The African American Studies professor went on to highlight a standout quality of the program which is that its faculty have diverse academic backgrounds. My traditional discipline is African American studies, I have a Ph.D. from Temple University, I also have a Masters in sociology, Yeboah said. Ive always been someone interested in statistics and technology.
The teaching faculty come from a variety of different educational backgrounds and disciplines, Yeboah described. We have a diverse faculty, diverse curriculum, and we are embedded in creating a community different from what exists right now in the tech world, she continued.
The anonymously donated Sean McCleese Endowed Chair will be seated in the Center for Applied Data Science, according to The Dig. They note that the chair will be used to work with the university on matters of social justice and to support the center.
Three weeks into the program, many students agree that the programs faculty provides an enriching sense of cultivation. Graduate student and chemical engineer Tamara Haye from Washington D.C. emphasized the switch from her specialized field to data science and analytics.
Im a chemical engineer, Im not a computer science engineer. Those are two different things. Its two different skill sets, the Howard undergraduate alumna said. For her, learning the Python programming language has been the most difficult thing so far.
The programs courses consist of computation social justice, data storytelling and visualization, engineering and managing data-driven change, machine learning, and bias and ethics among many other courses engaging in issues concerning tackling sensitive issues.
Ronald Jackson Carter Jr., a first-year graduate student in the new program agreed that the classes are challenging. Its very intense and fast-paced, but I think that the resources and the help are equally supportive, he said. The Mississippi native was the 45th Mister Howard University and is a Mastercard data science scholar. You have a professor, you have PAs that are very knowledgeable, the department chair, Dr. A is very supportive.
I think something that stands out the most is that its a diverse group of students, he continued. The program has new grads, it has people that have been in their careers for 12 years and are coming back trying to further their education, you have all these different people from different backgrounds, whether theyre starting out as computer scientists or sociologists.
The program is held completely online because Its a global conversation that we want you to join from wherever you are, Yeboah said. The program is 30 credits, including eight required courses, two electives involving data, an internship and a capstone.
Haye added how being a 1996 alumna allows her to see the change at the university over time. Theres been an expression and an allocation of resources that are unique to graduate students and the graduate programs, she said. I think now its just a matter of tapping into those resources.
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Howard's New Science Program is Training the Next Data Activists - The Hilltop Online
The CSUN club that’s encouraging women in STEM – Daily Sundial
CSUNs Girls Who Code club is just one of many across many campuses and countries, including 110 in California alone. According to the Girls Who Code official website, they have served over half a million girls, women and non-binary individuals through their various programs and clubs.
The purpose of Girls Who Code is to offer support to women and other underrepresented groups who are the minority in STEM fields, said club president Mariella Galvez-Perez, a senior at CSUN majoring in computer science.
Getting women and other underrepresented groups involved in computer science and STEM is important because it helps bring new ideas and outlooks on complex issues in the field, said Katya Mkrtchyan, the clubs faculty advisor and assistant professor in the Department of Computer Science.
If we focus on teaching women computer science skills, then I can say that it will bring different perspectives and approaches to problem solving new ideas, new ways of approaching problems, said Mkrtchyan.
Building a sense of community for newcomers is a major part of the club, said Girls Who Code Vice President Nitya Kumari.
Kumari, who is pursuing a masters in engineering management, said she and her board work hard to ensure everyone feels welcomed and supported at Girls Who Code.
I believe its mostly a community for girls who are into coding, even if they are beginners. It creates a sisterhood. We are all growing together in life and in our careers, and we help each other, said Kumari.
This semester is Galvez-Perezs first as the president of Girls Who Code, but she has been involved with the club as a member for about a year. The clubs message and sense of community for women in STEM are some of the factors that encouraged her to join.
In this major, theres a lot of guys. In my classes, Ive been one of just three girls, said Galvez-Perez. I liked that they empower women, and theyre all about helping them to succeed in the tech world. I became part of it because thats something Im passionate about.
In place since 2019, the club usually has 30-40 members each semester. Even though the club is targeted to STEM students, they make an effort to offer workshops that can be helpful for students from any background, according to Galvez-Perez.
We dont only have technical workshops. We also have workshops on how to build a resume, interviews, LinkedIn things that all majors need, said Galvez-Perez.
Each month, the club hosts a workshop, a social event and a study session. This semester, Galvez-Perez is looking forward to a workshop on technical interviews and the monthly study sessions.
Girls Who Code will be joined by the Society of Women Engineers group at CSUN at the study sessions, said Galvez-Perez.
Galvez-Perez reiterated how the study sessions could be used as an effort to combine the two groups and see how they work together.
The clubs can come together and study together. Like I said, theres a lot of men in the classrooms. So in our study sessions, girls can come together, help each other, get to know each other and feel less isolated, said Galvez-Perez.
Galvez-Perez said that preparing members for their future careers in STEM is one of the clubs biggest accomplishments. She has watched her peers go on to accomplish great things after graduating and being a part of the club.
Galvez-Perez gave an example of the previous club treasurer, who went on to pursue a masters degree in computer science at USC and work for the company Raytheon.
Helping people get interviews and internships and preparing them for a professional career, thats what Im really proud of, said Galvez-Perez.
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The CSUN club that's encouraging women in STEM - Daily Sundial
Mechanical engineering with a twist: Pursuing a passion for robotics … – MIT News
A photo of students in colorful hardhats running across Killian Court is what first drew Sharmi Shah 23 to the Department of Mechanical Engineering (MechE), but a desire to make the world a better place is what inspired her to pursue studies in the field and to focus on robotics.
Coming in, I thought I wanted to study mechanical engineering, but there wasnt much of a concrete basis behind that thinking, she says. She debated several majors, including pre-medicine and computer science, but landed on MechEs 2-A/6. Course 2-A/6 is a major in the mechanical engineering department, Shah explains. You take the core classes, but then you also get to pick and choose from computer science and electrical engineering.
Course 2-A is a twist on the traditional Course 2, mechanical engineering degree. By coupling the degrees core courses with a customized curriculum, students can home in on their personal interests such as robotics, entrepreneurship, or energy. Students can pick from a list of existing concentrations, like 2-A/6, also known as Control, Instrumentation and Robotics (CIR), or propose their own.
As a 2-A/6 major, Shah spent a year working on a robotic system named PEARL, a large sensing robot developed by theEngineering Systems Laboratory that harvests solar energy to recharge autonomous underwater vehicles (AUVs) and connect to low-Earth orbit satellite constellations for quick data transmission.
Inspired by the potential in the robotics field, she started taking more robotics classes and ended up taking most of the classes offered. In Professor Sangbae Kims class, 2.74 (Bio-Inspired Robotics), she and her team built a hula-hooping robot. We got to do everything from the controls to the mechanical design and the software, she says. In Professor Russ Tedrakes classes (Robotic Manipulation and Underactuated Robotics), she gained more experience with optimization techniques, perception, planning, and nonlinear controls.
Shah returned to MechE as a graduate student this fall and is now working in Kims Biomimetic Robotics Laboratory. Biomimetics is a discipline that employs an understanding of processes from nature, biology, and the natural world to create models, materials, machines or systems that help solve complex human problems.
During her graduate studies, she expects to focus on tactile sensing work she began during her Undergraduate Research Opportunity Program project as a senior. However, she knows her path may unfold in various ways that shes not fully aware of yet an uncertainty she embraces.
Not everything ends up going to plan, and that is A-OK, she says. You learn as you go that thinking can apply to your career planning, or classes, but also to engineering you try something, you try it again, you make a little progress. You keep trying.
Shes found a supportive community in MechE, and throughout campus, particularly as a member of Mirchi, MIT's nationally-ranked Bollywood fusion dance team. She also frequents the campus makerspaces and the MechE lounge, a gathering and collaboration space for the department. Community is important to Shah. Im grateful for all the friends Ive made here, and to my family theyre my biggest support system.
Shah says shes excited to be returning to MIT for her graduate studies. Theres always more I can learn and I want to keep learning.
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Mechanical engineering with a twist: Pursuing a passion for robotics ... - MIT News
Helping computer vision and language models understand what … – MIT News
Powerful machine-learning algorithms known as vision and language models, which learn to match text with images, have shown remarkable results when asked to generate captions or summarize videos.
While these models excel at identifying objects, they often struggle to understand concepts, like object attributes or the arrangement of items in a scene. For instance, a vision and language model might recognize the cup and table in an image, but fail to grasp that the cup is sitting on the table.
Researchers from MIT, the MIT-IBM Watson AI Lab, and elsewhere have demonstrated a new technique that utilizes computer-generated data to help vision and language models overcome this shortcoming.
The researchers created a synthetic dataset of images that depict a wide range of scenarios, object arrangements, and human actions, coupled with detailed text descriptions. They used this annotated dataset to fix vision and language models so they can learn concepts more effectively. Their technique ensures these models can still make accurate predictions when they see real images.
When they tested models on concept understanding, the researchers found that their technique boosted accuracy by up to 10 percent. This could improve systems that automatically caption videos or enhance models that provide natural language answers to questions about images, with applications in fields like e-commerce or health care.
With this work, we are going beyond nouns in the sense that we are going beyond just the names of objects to more of the semantic concept of an object and everything around it. Our idea was that, when a machine-learning model sees objects in many different arrangements, it will have a better idea of how arrangement matters in a scene, says Khaled Shehada, a graduate student in the Department of Electrical Engineering and Computer Science and co-author of a paper on this technique.
Shehada wrote the paper with lead author Paola Cascante-Bonilla, a computer science graduate student at Rice University; Aude Oliva, director of strategic industry engagement at the MIT Schwarzman College of Computing, MIT director of the MIT-IBM Watson AI Lab, and a senior research scientist in the Computer Science and Artificial Intelligence Laboratory (CSAIL); senior author Leonid Karlinsky, a research staff member in the MIT-IBM Watson AI Lab; and others at MIT, the MIT-IBM Watson AI Lab, Georgia Tech, Rice University, cole des Ponts, Weizmann Institute of Science, and IBM Research. The paper will be presented at the International Conference on Computer Vision.
Focusing on objects
Vision and language models typically learn to identify objects in a scene, and can end up ignoring object attributes, such as color and size, or positional relationships, such as which object is on top of another object.
This is due to the method with which these models are often trained, known as contrastive learning. This training method involves forcing a model to predict the correspondence between images and text. When comparing natural images, the objects in each scene tend to cause the most striking differences. (Perhaps one image shows a horse in a field while the second shows a sailboat on the water.)
Every image could be uniquely defined by the objects in the image. So, when you do contrastive learning, just focusing on the nouns and objects would solve the problem. Why would the model do anything differently? says Karlinsky.
The researchers sought to mitigate this problem by using synthetic data to fine-tune a vision and language model. The fine-tuning process involves tweaking a model that has already been trained to improve its performance on a specific task.
They used a computer to automatically create synthetic videos with diverse 3D environments and objects, such as furniture and luggage, and added human avatars that interacted with the objects.
Using individual frames of these videos, they generated nearly 800,000 photorealistic images, and then paired each with a detailed caption. The researchers developed a methodology for annotating every aspect of the image to capture object attributes, positional relationships, and human-object interactions clearly and consistently in dense captions.
Because the researchers created the images, they could control the appearance and position of objects, as well as the gender, clothing, poses, and actions of the human avatars.
Synthetic data allows a lot of diversity. With real images, you might not have a lot of elephants in a room, but with synthetic data, you could actually have a pink elephant in a room with a human, if you want, Cascante-Bonilla says.
Synthetic data have other advantages, too. They are cheaper to generate than real data, yet the images are highly photorealistic. They also preserve privacy because no real humans are shown in the images. And, because data are produced automatically by a computer, they can be generated quickly in massive quantities.
By using different camera viewpoints, or slightly changing the positions or attributes of objects, the researchers created a dataset with a far wider variety of scenarios than one would find in a natural dataset.
Fine-tune, but dont forget
However, when one fine-tunes a model with synthetic data, there is a risk that model might forget what it learned when it was originally trained with real data.
The researchers employed a few techniques to prevent this problem, such as adjusting the synthetic data so colors, lighting, and shadows more closely match those found in natural images. They also made adjustments to the models inner-workings after fine-tuning to further reduce any forgetfulness.
Their synthetic dataset and fine-tuning strategy improved the ability of popular vision and language models to accurately recognize concepts by up to 10 percent. At the same time, the models did not forget what they had already learned.
Now that they have shown how synthetic data can be used to solve this problem, the researchers want to identify ways to improve the visual quality and diversity of these data, as well as the underlying physics that makes synthetic scenes look realistic. In addition, they plan to test the limits of scalability, and investigate whether model improvement starts to plateau with larger and more diverse synthetic datasets.
This research is funded, in part, by the U.S. Defense Advanced Research Projects Agency, the National Science Foundation, and the MIT-IBM Watson AI Lab.
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Helping computer vision and language models understand what ... - MIT News
Top 10 Must-Read Books for Computer Science Students – Analytics Insight
Here is the list of best top 10 must-read books for computer science students
In this compilation, we present the Top 10 Must-Read Books tailored for Computer Science students. This list encompasses an eclectic range of titles, spanning from captivating biographies of industry trailblazers to profound tributes to the early days of computing, as well as practical how-to guides. Despite the vast differences in content and approach, every book featured here possesses a timeless quality, making them enduring staples in the ever-evolving realm of Computer Science.
Our top pick among computer science books is Charles Petzolds Code: The Hidden Language of Computer Hardware and Software. It offers readers, regardless of their backgrounds, a fascinating glimpse into the inner workings of computers. Petzold uses numerous illustrations and relatable analogies, like Braille and Morse Code.
Algorithms to Live By explores the practical application of computer algorithms to solve everyday decision-making problems and gain insights into how our minds operate. This interdisciplinary gem demonstrates how computer algorithms can be harnessed for various tasks, from finding a life partner to optimizing parking spot searches and email inbox organization.
Authored by MIT computer science professors, Structure and Interpretation of Computer Programs serves as a comprehensive programming text that delves into the mathematical and theoretical foundations of programming language. Though dense, its delivered with a light touch, making it particularly appealing to students with a mathematical background.
Algorithms stands as the most widely used college textbook on the subject, required reading in universities worldwide. It thoroughly covers essential algorithms and offers access to a rich online companion site packed with additional resources. The textbook and online content seamlessly integrate with a Massive Open Online Course (MOOC) for comprehensive learning.
Clean Code by Robert C. Martin is an instructive masterpiece that empowers readers to discern and craft code that functions impeccably exudes elegance, and mitigates future problems. This book imparts the essence of sound coding principles, transforming subpar code into excellence, and elucidates best practices in formatting and testing.
Code Complete, a pragmatic guide to software construction, amalgamates wisdom from academia, research, and industry. Laden with a plethora of code samples, it champions simplicity, fosters creativity, and serves as an encyclopedic compendium of coding excellence.
The Second Machine Age, a New York Times bestseller, offers insights into the transformative impact of technology on the world, foreshadowing a future where digital innovations and algorithms usurp human roles, including medical diagnosis. The authors outline a blueprint for a prosperous new era in the wake of these profound changes.
Everything You Need to Ace Computer Science and Coding in One Big Fat Notebook is a middle school-friendly reference guide brimming with comprehensible diagrams, charts, and explanations. It reads like the well-organized notes of the brightest student in class, earning praise from both young readers and adults for its accessibility and educational value.
Superintelligence by Swedish philosopher Nick Bostrom delves into the intriguing notion that if machines surpass humans in intelligence, they could potentially supplant us as the planets dominant species. The book explores various scenarios, prompting readers to reflect on our current interaction with technology and its implications for our future survival.
On the other hand, C Programming Language, authored by the creators of C, serves as a comprehensive guide to ANSI standard C programming. This textbook isnt tailored for novice computer science students, requiring a solid grasp of fundamental computer science principles before delving into the intricacies of C, known for its complexity among programming languages.
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Top 10 Must-Read Books for Computer Science Students - Analytics Insight
‘The Solutions Just Clicked’ | Exceptional Results | Stories | Brandeis … – Brandeis University
Part of Exceptional Results
Mathematician Bonnie Berger 83 says her lightbulb moment came during her sophomore year.
She was sitting at a computer terminal in Ford Hall, coding in FORTRAN, one of the earliest programming languages. It just came so easily to me, she says. I thought, Aha! Ive found what I love.
Berger, the Simons Professor of Mathematics at MIT, and a member of both the National Academy of Sciences and the American Academy of Arts and Sciences, is one of the worlds foremost experts in computational biology, the application of computer science and math to biology.
Shes used code-breaking strategies to reveal protein structures, applied machine learning and big data to drug discovery, and invented a computational tool called Dig that identifies genetic mutations in cancer cells before they turn tumorous. I view biology as providing me problems as a mathematician, she says.
Her father, a Miami businessman who dreamed of being a mathematician, used to slip notes under her bedroom door that read, Good morning, Bonnie! Would you like to do math problems today?
She started Brandeis as a Russian language major, then switched to psychology during her second year. She didnt have much interest in diagnosing mental illness or analyzing graffiti on a bathroom wall (an observational experiment assigned in one class), but she did love any assignment involving programming. In her junior year, she changed her major to computer science.
I could see how to lay out a program, she says. The solutions just clicked in my brain.
She got 11 A-pluses in her math and computer science classes. One summer, she designed the universitys first online course-registration system for the registrars office.
Although there werent many female faculty or students in the computer science department at the time, Berger says she never encountered sexism.
I was appreciated for my brain, she says. There were never any issues with gender. And faculty members encouraged her to pursue an advanced degree after graduation.
Brandeis helped me find myself, she says. It finds hidden jewels.
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'The Solutions Just Clicked' | Exceptional Results | Stories | Brandeis ... - Brandeis University
Symposium to Spotlight Digital Mental Health Technology – Dartmouth News
Experts in the field of digital mental health will gather at Dartmouth on Sept. 19 to discuss opportunities and challenges in developing innovative digital tools that can transform mental health care.
President Sian Leah Beilockwill deliver opening remarks to kick off theDigital Mental Health & AI Symposiumorganized by theCenter for Technology and Behavioral Healthat the Hanover Inn.
The Center for Technology and Behavioral Health is a leader in the science of digital health as applied to health behavior, saysCTBH Director Lisa Marsch.We are excited to host this event with the Dartmouth community to highlight the opportunities for using digital health tools to promote mental health anytime and anywhere.
Marsch noted that the center, part of the Geisel School of Medicine, has been designated as a Center of Excellence by the National Institutes of Health.
The one-day event includes keynote talks, a research poster session, and panel discussions on student mental health, how AI is shaping the field, and the ways to unlock the full potential of digital therapies.
The symposium will bring together some of the leading experts in the field under the same roof to discuss the successes and roadblocks so far and share their ideas on plotting the path forward, says event co-chairAndrew Campbell, Albert Bradley 1915 Third Century Professor in the Department of Computer Science.
Digital mental health technologies encompass a wide range of data-driven or AI-powered web-based and mobile tools that are designed to impact mental health outcomes of users.
The initial impetus behind trying to use technology in the mental health space was to fill the gap caused by the general lack of adequate health care resources, says Campbell. Soon after, the smartphone and social media became something akin to petri dishes to try to understand whats going on in peoples lives around the issue of mental health.
Since then, Campbell says, there have been a number of successes, for example,in using phones to predict behaviors, using those behaviors to predict symptoms, and then engaging in interventions and therapeutic approaches based on the predicted symptoms.
The upcoming symposium will focus on advances in behavioral sensing (the use of sensors in personal devices to measure and monitor behavior), intervention (activities accessed via technology platforms that improve users mental health), and the AI revolution.
Keynote speakers include:
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Symposium to Spotlight Digital Mental Health Technology - Dartmouth News
STEM students are privileged at Duke – The Chronicle – Duke Chronicle
What picture comes to mind when you think of the stereotypical STEM student? Are they stressed? Do they struggle to balance their workload? Do they procrastinate or do they work hard and play equally as hard? Regardless of what exactly you imagine, Im pretty sure that privilege was not a part of that image. Im not talking about the fact that STEM students are overwhelmingly white or Asian and male or the fact that their careers generate higher salaries. Im talking about the privilege that comes with studying STEM and how the Duke community treats students because of it.
I am not a STEM student. I never liked math. I always saw science as just another subject in school. And I never grew up with dreams of working in medicine, engineering, or a technology field. I preferred reading in English class and learning about culture in history class. I never considered this to be odd until I came to Duke. Here, it felt like everyone I met wanted to do one of three things (outside of law and consulting of course): go to medical school, become an engineer or major in computer science so that they could work at some tech company. And I wasnt wrong. A recent survey from the career center found that the top five industries Duke students enter are technology, finance, business or management consulting, healthcare and medicine and science or research. I felt like no one wanted to write books, or make movies or learn about people and culture. As a self-proclaimed anti-STEM student, I started to see the benefits of pursuing the STEM path at Duke and how my own path lacked these advantages.
Whenever I told someone I planned to major in African & African American Studies, I was always asked what I wanted to do or given a smile and a thats cool." Many Duke students dont even know what non-STEM students actually study. If you ask a Duke student to define cultural anthropology or describe what ethnic studies students are learning, they most likely cannot. But should the conversation switch to biology, chemistry or computer science, their faces light up.
How have we as a campus so easily coded STEM majors as normal while viewing the humanities and social sciences as foreign and in some cases useless? Why do we respect the rigor of labs and problem sets, but call other students lucky when they must read an assigned book in only a week or fully develop an original creative concept in just a few days? We are constantly told that there will be countless job opportunities available to us that have not been created yet, such as social media marketing. Then we as a society turn around and tell students in college to focus on building marketable skills (which is often just code for STEM skills like coding) and creating a stellar resume. How have these ideas translated into a greater push towards STEM?
STEM students are also privileged in terms of resources. Whenever the university allocates funds or comes across new resources, it seems like these departments always eat first. The history department sits in the Classroom Building on East Campus, across from Friedl which is home to the AAAS and cultural anthropology departments, while engineers quite literally have an entire quad to themselves. Even the quality of the classrooms varies. There are still chalkboards on campus used by you guessed it non-STEM professors. How are STEM buildings able to have such beautiful architecture and large glass windows, yet social science buildings are often in inconvenient locations that lead many students to avoid taking those courses? Lets be honest; traveling to Friedl, or the Classroom Building, or East Duke or Smith Warehouse when you dont live on East Campus is not the most convenient. Yet, its something that I and many other students do every week.
Even in terms of community, STEM students are privileged. Any room that they walk into they can be sure that at least one other student studies something under the STEM umbrella, and in many cases, its easy to find someone in their department. I have been in many rooms with pre-med, Pratt and computer science students where I was the odd one out. I was the one who said no to STEM. Even as a double major in AAAS and Visual & Media Studies, I struggle to find peers who are majoring in either department. Many social science departments at Duke have very few majors and finding a social science student who doesnt study public policy is also a real challenge. You have the occasional STEM and humanities double major or the STEM students with a social science minor but overall, being a non-STEM student is isolating and can be lonely. Who do you talk to about your classes when your friends are all pre-med? Who do you study with when youre surrounded by engineers? What upperclassmen can you turn to for advice when they all study computer science?
Learning to navigate this experience at Duke was an adjustment. While STEM students have no control over the resources they receive or the facilities they are given, we must acknowledge that there is some privilege there. By no means am I implying that STEM is easy. However, we must create space for non-STEM students to feel heard and let them know that whatever they choose to study is valid. STEM students are also responsible for educating themselves and using what few opportunities they have to take courses that teach them something different or challenge them in a new way. I believe that the humanities and social sciences provide useful skills that we all need to develop. Maybe then it will become clear that everything at Duke is valuable, not just STEM fields.
Sonia Green is a Trinity junior. Her column typically runs on alternate Tuesdays.
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STEM students are privileged at Duke - The Chronicle - Duke Chronicle
Elvis Moreno of Yonkers New York Explores the Fundamentals of … – Downbeach.com
Elvis Moreno of Yonkers, New York is an IT industry professional, and computer hobbyist. In the following article, Elvis Moreno discusses the architecture of the computer, that allows them to understand, retain, and retrieve information.
The term computer architecture is nothing more than the framework for understanding how computers work and perform tasks. A computers operation depends on hardware, software, and communication components, which include CPUs, memory, input/output devices, and storage units.
Elvis Moreno of Yonkers, New York explains that it encompasses everything from lines of text to spreadsheet digits to dots of colors to sound patterns to the systems appearance thanks to this fundamental aspect of computer science.
Without certain components, computer architecture would cease to exist. As a result, computers themselves would disappear. Each element plays a vital role in constructing a functional, workable architecture for basic and complex computing.
Todays digitally focused society has brought many unique input devices (i.e., those that connect external data sources to the computer) to the forefront VR headsets included. However, keyboards and mice remain the most common input devices, both of which have hardware drivers that sync with the architectures other components.
Elvis Moreno says that unsurprisingly, outputs are the inverse. They deliver the computers results to the user, with different output devices sending different media types. Headphones, for example, deliver sound, while printers spit out hardcopy text.
All computers have multiple memory/storage units, but they werent created equally. Instead, theyre categorized into primary and secondary storage.
Otherwise known as the main memory, its directly accessible by the CPU and used for storing instructions and information throughout program execution. Experts note the two major types are random access memory (RAM) and read-only memory (ROM).
The former, as a temporary memory, supplies relevant information directly to the CPU. The latter holds pre-installed instructions and firmware. Unlike RAM, its persistent and cant be changed due to its role in booting the machine upon startup.
Elvis Moreno of Yonkers, New York says that the CPU cant directly access secondary/external storage (i.e., solid-state drives (SSDs), hard disk drives (HDDs), and similar). Instead, information must be transferred to primary storage for CPU access.
Many industry professionals consider the central processing unit to be the brain of the machine. And just like human brains, its a complex part of computer architecture, comprising many sub-components like registers, arithmetic logic units (ALUs), and control circuits.
Elvis Moreno of Yonkers, New York notes that essentially, its job is to interpret and execute instructions, working with the other sections of the structure to make sense of the information and ensure it offers the appropriate output.
Diving deeper into the CPU unveils a world of integral sub-elements explained briefly by professionals as follows:
Located in the firmware, the bootloader is run by the processors that gets the operating system from the disc, loading it into the memory for execution. Its found on workstation and desktop computers, alongside embedded devices, making it one of the most vital components of computer architecture.
Elvis Moreno notes that the OS governs the functionality above firmware, managing memory usage and regulating input/ouput devices. As most slightly tech-savvy individuals will know, it also offers an interface that lets them launch apps and utilize stored data.
Buses, tangible bunches of signal lines, all have the same purpose (like USBs, for instance). They enable the flow of electrical impulses between components, letting information pass from one section to the next.
Elvis Moreno of Yonkers, New York says, referred to as traps or exceptions by some experts, interrupts redirect the processor from running the current task so it can deal with an occurrence, such as a peripheral malfunction or an input/output device has completed its previous job and is awaiting a new one.
Elvis Moreno of Yonkers, New York says that unbeknownst to many, computer architecture isnt entirely linear. Experts configure the above-mentioned components in various ways, depending on the system. In fact, there are five configurations often seen in the industry ISA, microarchitecture, client-server architecture, SIMD, and multicore architecture.
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