Machine learning
The federal government of Nigeria has embarked on a review of 26 trade syllabuses for technical colleges across the country. The review aims to ensure that technical and vocational education in Nigeria meets industry needs and adheres to international best practices. The move is part of the government's
Machine learning
Researchers at the University of Petra have developed a novel optimization framework called Quantum Epigenetic Algorithm (QEA), which combines quantum-inspired probabilistic representation with biologically motivated epigenetic gene regulation to perform efficient and adaptive feature selection. The QEA was evaluated across four benchmark datasets and consistently outperformed baseline methods, achieving the
Machine learning
Researchers at the Universidad de Cordoba have created an IoT-based system for real-time air quality monitoring and prediction, which can significantly reduce monitoring costs and enable large-scale data management. The system integrates pollutant sensors, detects liquefied petroleum gas, humidity, and temperature, and uses machine learning (ML) techniques to classify and
Machine learning
Researchers from the Korea Institute of Materials Science have proposed a novel approach to design biodegradable Mg-Zn-Mn-Sr-Ca (ZMJX) alloys for load-bearing orthopedic implants. By utilizing interpretable machine learning and a multi-objective genetic algorithm, the team aimed to optimize the composition of the alloys to achieve both mechanical strength and biologically
Machine learning
Artificial intelligence plays a critical role in meteorological forecasting, with researchers from Fudan University publishing a new study on the use of machine learning algorithms to simulate brightness temperatures. The study, published in Remote Sensing, found that deep neural networks (DNN) outperformed other machine learning approaches in retrieving brightness temperatures,
Machine learning
Eli Lilly and Company announced the launch of Lilly TuneLab, an artificial intelligence and machine learning (AI/ML) platform that provides biotech companies access to drug discovery models trained on years of Lilly's research data. The platform is part of Lilly Catalyze360's offerings for early-stage biotech
Machine learning
Researchers at Hong Kong Polytechnic University have proposed an innovative framework for estimating tree above-ground biomass, a crucial step towards achieving carbon neutrality. The existing global allometric models face challenges in accurately modeling local trees' biomass. The new framework involves collecting local tree felling data, implementing Light Detection and
Machine learning
Researchers from Istanbul Technical University have developed a new approach to bathymetric mapping using machine learning, which enables cost-effective and efficient mapping of underwater terrain. Traditionally, shipborne echosounders are used for bathymetry, but they are costly and inefficient in shallow waters. The new method leverages emerging technologies such as satellite
Machine learning
Insitro, a pioneer in machine learning for drug discovery and development, has announced a new collaboration with Eli Lilly and Company (Lilly) to develop advanced machine learning models that can predict key pharmacological properties of small molecules. This effort aims to address longstanding challenges in drug development where such properties
Machine learning
Eli Lilly has introduced Lilly TuneLab, a machine learning platform that allows selected early-stage biotechs to access drug discovery models trained on years of research data. The platform, hosted by a third party, employs federated learning to enable companies to take advantage of Lilly's AI models without sharing
Machine learning
A recent patent publication has showcased a service robot capable of advanced display interaction using artificial intelligence (AI) technology. The robot, invented by Xu, Zhetao, is designed to enhance marketing and user engagement through interactive displays that adjust to the user's position and orientation. The service robot comprises
Machine learning
Researchers at Marwadi University have developed a method to optimize the placement and sizing of distributed generations (DGs) and shunt capacitors in power distribution networks. By utilizing renewable energy resources, such as photovoltaic cells and wind turbines, the study aims to ensure a specific level of reliability in power distribution
