Stay updated with breaking news from Raining poetry. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.
WETER LLC was established in 2020 to carry out research and development in the field of natural and technical sciences, devices (systems) for the production and transmission (distribution) of electricity, urban infrastructure systems in collaboration with scientists, specialists and specialized institutions to obtain design results that allow the creation of new power generating devices and infrastructure communications of cities. The company has a production and research office in Dubai, UAE: TIAGLIN HUB, WETER LLC; UAE, DUBAI, DIP 1, W10. The company has highly qualified specialists: research engineers; feasibility studies experts marketing and market analysis specialists; engineering-specialists; design engineers; architects; technical staff. To date, WETER LLC has been implementing projects W.E.T.E.R, GOROD L.E.S and V.O.D.A aimed at developing urban infrastructure, creating energy-efficient facilities and overcoming electricity shortages. Moreover, the properties of the objects of the projects determine the creation of optimal, comfortable and safe living conditions for humans, reducing the man-made impact on nature and the climate of the planet.
Although robots have been used by the wind energy industry to paint and polish blades, automation has not been widely adopted. Research at the laboratory demonstrates the ability of a robot to trim, grind, and sand blades.
Recent studies have demonstrated that backdoor attacks can cause a significant security threat to federated learning. Existing defense methods mainly focus on detecting or eliminating the backdoor patterns after the model is backdoored. However, these methods either cause model performance degradation or heavily rely on impractical assumptions, such as labeled clean data, which exhibit limited effectiveness in federated learning. To this end, we propose FLPurifier, a novel backdoor defense method in federated learning that can effectively purify the possible backdoor attributes before federated aggregation. Specifically, FLPurifier splits a complete model into a feature extractor and classifier, in which the extractor is trained in a decoupled contrastive manner to break the strong correlation between trigger features and the target label. Compared with existing backdoor mitigation methods, FLPurifier doesn’t rely on impractical assumptions since it can effectively purify the backdoor effects in the training process rather than an already trained model. Moreover, to decrease the negative impact of backdoored classifiers and improve global model accuracy, we further design an adaptive classifier aggregation strategy to dynamically adjust the weight coefficients. Extensive experimental evaluations on six benchmark datasets demonstrate that FLPurifier is effective against known backdoor attacks in federated learning with negligible performance degradation and outperforms the state-of-the-art defense methods.
Intrinsic, a software and AI robotics company at Alphabet, has integrated NVIDIA AI and Isaac platform technologies to advance the complex field of autonomous robotic manipulation.
This award acknowledges GrayMatter's industry-leading SCAN&GRIND™ robotic system powered by a proprietary physics-based advanced technology to improve manufacturing systems and surface finishing applications.
SKC NoiseCHEK is the easiest-to-use dosimeter available! Designed specifically for OEHS professionals, SKC NoiseCHEK offers the easiest operation and accurate noise measurements. Everything you need is right in your palm. Pair Bluetooth models to your mobile devices and monitor workers remotely with the SmartWave dB app without interrupting workflow. Careful design features like a locking windscreen, sturdy clip, large front-lit display, bright status LEDs, and more make NoiseCHEK the top choice in noise dosimeters. Demo NoiseCHEK at AIHA Connect Booth 1003.
Every year, millions of workers get injured on the job, and a significant number of reported occupational injuries are hand related. The good news is that hand injuries are the number one preventable industrial accident across all industries.