Mechanical Engineering: Research Guide

Getting a quick and accurate reading of an X-ray or some other medical images can be vital to a patient's health and might even save a life. Obtaining such an assessment depends on the availability of a skilled radiologist and, consequently, a rapid response is not always possible. For that reason, says Ruizhi "Ray" Liao, a postdoc and a recent PhD graduate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), "we want to train machines that are capable of reproducing what radiologists do every day." Liao is first author of a new paper, written with other researchers at MIT and Boston-area hospitals, that is being presented this fall at MICCAI 2021, an international confe..

Flying cars, drones, and other urban aerial mobility vehicles have real potential to provide efficient transportation and delivery solutions, but what happens if a drone delivering cheeseburgers breaks down over a city park or in the middle of a crowded street? Researchers at the University of Illinois Urbana-Champaign developed a method to measure vehicles' ability to recover and complete its mission safely.

Researchers from the University of Melbourne (UoM) and the Singapore University of Technology and Design (SUTD) have developed an algorithm that can detect important events based on the time and geographical scale of topics being actively discussed on social media. Their algorithm, detailed in the Journal of Big Data, does not require knowing which events to detect upfront and can be tailored to use smaller or larger geographical and time resolutions to reflect the dynamic nature of real-life events.

One of the challenges in the era of Big Data is dealing with many independent variables, also known as the "curse of dimensionality." Therefore, there is an urgent need to develop algorithms that can select subsets of features that are relevant and have high predictive powers. To address this issue, computer scientists at the University of Groningen developed a novel feature selection algorithm. The description and validation of their method was published in the journal Expert Systems with Applications on 16 September 2021.

Say you're driving with a friend in a familiar neighborhood, and the friend asks you to turn at the next intersection. The friend doesn't say which way to turn, but since you both know it's a one-way street, it's understood.

Researchers at Skolkovo Institute of Science and Technology (Skoltech) in Russia have recently developed an innovative system for human-swarm interactions that allows users to directly control the movements of a team of drones in complex environments. This system, presented in a paper pre-published on arXiv is based on an interface that recognizes human gestures and adapts the drones' trajectories accordingly.

Advances in artificial-intelligence-based technologies have led to an astronomical increase in the amounts of data available for processing by computers. Existing computing methods often process data sequentially and therefore have large time and power requirements for processing massive quantities of information. Hence, a transition to a new computing paradigm is required to solve such challenging issues. Researchers are currently working towards developing energy-efficient neuromorphic computing technologies and hardware that are capable of processing massive amounts of information by mimicking the structure and mechanisms of the human brain.

Researchers at Skolkovo Institute of Science and Technology in Russia have recently developed MobileCharger, an autonomous robotic system designed to charge other robots as they complete their missions. This system, presented in a paper pre-published on arXiv, can transfer energy to mobile robots without forcing them to fly back to designated charging stations when their power is depleted.

CPQM's Laboratory for Quantum Information Processing has collaborated with the CDISE supercomputing team "Zhores" to emulate Google's quantum processor. Reproducing noiseless data following the same statistics as Google's recent experiments, the team was able to point to a subtle effect lurking in Google's data. This effect, called a reachability deficit, was discovered by the Skoltech team in its past work. The numerics confirmed that Google's data was on the edge of a so-called, density-dependent avalanche, which implies that future experiments will require significantly more quantum resources to perform quantum approximate optimization. The results are published in the field's leading jou..

Algorithms are sort of like a parent to a computer. They tell the computer how to make sense of information so they can, in turn, make something useful out of it.

To navigate their surroundings safely and most effectively, robots should be supported by a highly performing computer vision system. One of the greatest challenges when developing computer vision systems for robots is to limit occlusions so that the robot can sense most of its surroundings.

The TV show "Star Trek: The Next Generation" introduced millions of people to the idea of a holodeck: an immersive, realistic 3D holographic projection of a complete environment that you could interact with and even touch.

A new technique could unleash the potential for digital sensors like cameras to sense all light intensities, and microphones to sense all audio ranges

Spotify's whole business model relies on keeping you listening and being able to predict what songs you'll want to hear next. But Cornell researchers recently asked the question: Why do they still not let you vote down a song?

Music is an indispensable element in film: it establishes atmosphere and mood, drives the viewer's emotional reactions, and significantly influences the audience's interpretation of the story.

The two-second rule, taught in driver's ed classes across the country, is a rule of thumb that helps drivers maintain a safe distance from the car ahead at any speed. Adhering to the two-second rule can be difficult. A team of engineers led by Dan Work, associate professor of civil and environmental engineering, has developed an assistive technology to help drivers maintain this guidance to smooth out traffic jams and improve safety.

Over the past few decades, computer scientists have been exploring the potential of applying game theory and artificial intelligence (AI) tools to chess, the abstract strategy board game go, or other games. Another valuable use of game theory is in the economic sciences, particularly as a framework to explain strategic interactions in markets and the resulting outcomes.

When reporting on sports games live or remotely, commentators should be able to quickly recognize the numbers on the players' jersey shirts, as this allows them to keep up with what's happening and communicate it to their audience. However, quickly identifying players in sports videos is not always easy, as these videos are often taken at a distance to capture the overall progression of the game. A further difficulty is the fast motion of the broadcast camera that often results in motion blur.

The simulation of physical systems using computing tools can have numerous valuable applications, both in research and real-world settings. Most existing tools for simulating physical systems are based on physics theory and numerical calculations. In recent years, however, computer scientists have been trying to develop techniques that could complement these tools, which are based on the analysis of large amounts of data.

A small team of researchers from The State University of New York at Albany, the State University of New York at Buffalo and Keya Medical has found a common flaw in computer-generated faces by which they can be identified. The group has written a paper describing their findings and have uploaded them to the arXiv preprint server.

Computer scientists at the University of California San Diego have released OpenRooms, an new, open source dataset with tools that will help users manipulate objects, materials, lighting and other properties in indoor 3D scenes to advance augmented reality and robotics.

It's an old adage: there's no harm in getting a second opinion. But what if that second opinion could be generated by a computer, using artificial intelligence? Would it come up with better treatment recommendations than your professional proposes?

The Safety PoolTM Scenario Database, the largest public repository of scenarios for testing autonomous vehicles in the world—led by WMG at the University of Warwick and Deepen AI—will now be used in China, thanks to a new partnership with Automotive Data of China, a subsidiary of the China Automotive Technology and Research Center (CATARC-ADC).

The transportation of hazardous materials through densely populated areas, such as cities, is a necessary part of modern life, but comes with risks of spills and leaks, explosions, environmental issues, and public health concerns. New research in the International Journal of Simulation and Process Modelling, has used a transportation management simulation to look at problems that might arise in moving hazardous materials within a city when traffic congestion is common.

Human decision-making processes are inherently hierarchical. This means that they involve several levels of reasoning and different planning strategies that operate simultaneously to achieve both short-term and long-term goals.

Smart cities will not be truly smart until they have sustainable transport systems. New work published in the International Journal of Shipping and Transport Logistics has used fuzzy logic to look at the options.

Twenty years into the 21st century the demand for computational power is outpacing supply at an ever-increasing rate. From global pandemics that require rapid-response drug designs, to smart grids, self-driving vehicles, artificial intelligence and machine learning, scientists are scrambling to boost current computational capabilities until quantum computing becomes a practical reality.

Engineering systems, such as power grids and transportation systems, are becoming increasingly complex and encompass numerous sub-systems that are spatially interconnected. Modeling of these 'dynamic networks' is an important task for designing, analyzing, and controlling these systems. By exploiting graph theory, Shengling Shi developed novel modeling methods that consider the interconnection structure of dynamic networks and thus allow for more flexible locations of actuators and sensors in the network for data collection and data-driven modeling.

Scientists from the Division of Sustainable Energy and Environmental Engineering at Osaka University used generative adversarial networks trained on a custom dataset to virtually remove obstructions from building façade images. This work may assist in civic planning as well as computer vision applications.

Neural networks (NNs) are increasingly being used to predict new materials, the rate and yield of chemical reactions, and drug-target interactions, among others. For these applications, they are orders of magnitude faster ...