Education writer Rachel Higgins is on the blog today to discuss some of the profound advancements high tech majors have made to the scientific field, both in terms of discoveries and innovations. The future of computational education is of obvious importance to the Massachusetts Academy of Sciences, and Rachel’s article exposes and details many of the background reasons why. Rachel, who primarily writes about advancements in e-learning, frequently writes posts and articles that provide information for accredited online degrees.
Computation Revolutionizes the Field of Engineering and the Way it is Taught in College.
As technology advances, the Society for Industrial and Applied Mathematics (SIAM) asserts that alongside theory and physical experimentation, computation has emerged as the third primary mode of discovery. Numerical simulation has enabled the study of complex systems and natural phenomena that would be too expensive or dangerous through practical experimentation or testing. Yet, despite utilizing their their benefits every day, most people are still wholly unaware of how important these complex computer algorithms are in developing products for industry and consumers.
Today, computer science engineering is a broad multidisciplinary area encompassing applications in science, engineering, applied mathematics, and numerical analysis as well as computer science. Among researchers, computer models and computer simulations have become an essential element of the process, supplementing or even replacing experimentation in many cases. The shift from application of data garnered through experimentation to computational results requires expertise in mathematical modeling, computer language comprehension, numerical analysis, algorithm development, software implementation, program execution, validation and visualization of results, all of which are essential elements of computer science engineering.
In design of aircraft and vehicle simulation, the importance of computer modeling has become increasingly vital in recent years. Aerospace designers for Lockheed Martin, for instance, use simulation to replicate the performance of aircraft lift fans and try other their designs before building them. “For a long time, simulation and CAD (computer-aided design software) have been separate and unequal disciplines,”says Todd Evans, spokesman for design software maker MSC Software. “But over the last few years, that’s been changing. Those disciplines have been moving towards each other.” Simulations are expected to soon replace physical testing altogether, cutting parts of the design process from 350 days to 36, reducing the cost of prototyping and manufacturing.
Computer modeling of weather and climate conditions are also proving increasingly reliable. Climate scientists at times use the same computer modeling programs to predict weather patterns for the upcoming week and climate expectations for the next few decades. “The models are constantly being improved,” Michael D. Lemonick, senior writer for Climate Central, says. Climate scientists today often modify their programs to predict the actual timing of El Ninos and La Ninas over the next few years.
Development of information and communication technology in the medical sphere is one of the most promising venues for computer engineering looking forward. This includes technologies adapted to the hospital environment and remote healthcare. The Wireless Networks Group and the Department of Telematics Engineering at Spain’s Universitat Politècnica de Catalunya are currently involved in a project that reduces the probability of drug administration errors through a sucre patient identification system utilizing radio-frequency technology. The Biomedical Engineering Research Centre has been carrying out a number of tests of robots that create anatomic models, enabling repetitive, systematic methodology, applied to quantify independent measurements of external factors. With these tests, surgeons can learn how to improve the “most suitable stitching method,” says Alicia Casals, leader of the university’s robotics research group.
Another machine learning technique is the development of artificial neural networks (ANNs). ANNs are used for classifying non-linear electron-cardiogram signals and recognizing abnormal patterns suggesting the risks of cardiovascular diseases. Reusable neuron architecture, enabled using performance-efficient and cost-effective silicon implementation allows automatic training updates through computer chips, helping to improve the execution speed and energy efficiency of classifying data that provides important clues regarding cardiovascular diseases.
Many technical improvements have also recently lead to significant advancements in diagnostic ultrasound imaging. Developments in array designs have resulted in greater bandwidths and improvements in spatial and contrast resolution, while advancements in digital signal processing have produced innovations in image display and archiving. The enhancement of doppler students and novel non-linear modes have allowed vessels to be imaged even down to the level of microcirculation.
In 2008, French professor Alain Carpentier unveiled the world’s first fully implantable artificial heart. A mixture of animal tissue and titanium, the technology is covered in specially treated tissue to avoid rejection by the body’s immune system, particularly as related to the formation of blood clots. Carpentier’s heart utilizes electronic sensor technology to allow his artificial heart to respond instantly to changes in blood pressure and flow, while adapting to the heartbeat rate accordingly. While the heart has not yet been found to be completely reliable — most laboratory tests have shown side effects due to infections or blood clots — it is an important step forward in computer-aided aided bioengineered organs.
In 2010, a multi-institutional team, lead by University of California-San Francisco professor Shuvo Roy, developed an implantable artificial kidney that can be powered by the human body’s circulatory system. While the design is currently still in development, the goal is to one day allow thousands of people to be removed from dialysis machines or kidney-donor waiting lists. The system relies on advances in nanotechnology and tissue generation and “could dramatically reduce the burden of renal failure for millions of people worldwide” while also reducing one of the largest costs in US health care, according to Roy.
Due to the vast field of disciplines that utilize computation, as well as their growing interconnectedness, members of the Society for Industrial and Applied Mathematics assert that CSE graduates should have a working knowledge in application areas such as computational physics, weather forecasting, astronomy, computational chemistry, computational fluid dynamics, bioengineering, acoustics, molecular biology, electronic design automation, circuit simulation and semiconductor simulation, among others. SIAM maintains that it is “absolutely essential that interdisciplinary collaboration be an integral part of the curriculum and thesis research of CSE students.
SIAM maintains that courses should include multidisciplinary projects and presentations whenever possible, as well as participation from research teams, and internships at a National Library or within industry.” The group also asserts that a curriculum’s chosen model and its chances for success are highly dependent on local academic strengths as well as political considerations. The current economic climate around the globe is very favorable toward multidisciplinary work in science and engineering. As technology becomes more pervasive in every facet of live in highly developed cultures for both industry and consumer products, the opportunities for computer science engineers will likely continue to grow for the foreseeable future.