Penelitian

Penelitian - E-commerce continues to expand and achieved new levels during the recent holiday season. To rapidly fulfill the enormous volume and variety of orders, companies such as Amazon, Walmart, and Alibaba are investing heavily in new warehouses.

To address the shortage of workers, many companies are considering robots. However, reliably grasping a diverse range of products remains a Grand Challenge for robotics.


In a paper published Wednesday, Jan. 16, in Science Robotics, engineers at the University of California, Berkeley present a novel, "ambidextrous" approach to grasping a diverse range of object shapes without training.

"Any single gripper cannot handle all objects. For example, a suction cup cannot create a seal on porous objects such as clothing and parallel-jaw grippers may not be able to reach both sides of some tools and toys," said Jeff Mahler of the UC Berkeley.

Mahler works in the lab of Ken Goldberg, a UC Berkeley professor with joint appointme…

Penelitian - A team of researchers at Northwestern University has found that people serving as mock jurors tend to view police officer intent differently when viewing events captured using body cams versus dash cams.

In their paper published in Proceedings of the National Academy of Sciences, the group describes their study, in which they used volunteers as stand-ins for jurors watching either real or staged police action video events.


The use of body cams by police officers has become routine in the U.S.—their use is based on the idea that video footage of encounters between police and the public will make police officers more accountable for their actions.

Many jurisdictions have passed laws requiring their use after multiple instances in which questions were raised about the intent of the officers involved and their subsequent actions, particularly in cases when the victim was unarmed.

In this new effort, the researchers have sought to determine if the existence of body cam video d…

Penelitian - A team led by the University of California San Diego has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster.

Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices. The advance is described in a paper published recently in Nature Communications.


Training neural networks to perform tasks like recognize objects, navigate self-driving cars or play games eats up a lot of computing power and time. Large computers with hundreds to thousands of processors are typically required to learn these tasks, and training times can take anywhere from weeks to months.

That's because doing these computations involves transferring data back and forth between two separate units--the memory and the processor--and this consumes most of the energy and time during neural network training, said senior author Duygu Kuzum, a profe…

Penelitian - Wearable electronic devices are susceptible to degradation or fatigue fracture, but now the aged electrodes of the devices can be healed by simple water vapor treatment.

A group of international researchers led by Lifeng Cui from Dongguan University of Technology, China designs repairable microfiber-based network electrodes with high conductivity, high transparency and ultra-flexibility.


The electrodes consist of polycaprolactone microfibers as healing agents and a thin conducting layer coating such as gold. The electrodes can recover the conductivity and mechanical strength after tensile failure or even cutting, which can be attributed to the adhesion and capillary force at the interface of gold and polymer.

Upon embedding in PDMS elastomer, the electrodes show excellent durability of up to 1000 cycles and can be used in wearable pressure and strain sensing devices.



Journal : Yuting Wang et al. Reversible conductivity recovery of highly sensitive flexible devices by water…