Machine learning
A new patent application for a smart insect control device that utilizes artificial intelligence has been made available online. The system is designed to help farmers more efficiently manage insect pests and reduce costs associated with crop management. The method involves training a model on a source dataset in a
Iowa State University
Scientists at Iowa State University have developed a novel generative deep learning framework that can design printable, multifunctional microstructural materials. This breakthrough has significant implications for advancing material design technologies. The framework combines a custom-developed voxelized microstructure generator, HetMiGen, with a new machine learning model, TransVNet, to rapidly and accurately
Machine learning
A recent patent application filed by four inventors has described a system and method for providing alarm risk score analysis and intelligence in controlled environments. The system uses a combination of sensor information and video frames to determine the risk value of an event and generate an alarm if it
Big data
Researchers from the Polytechnic University of Valencia have proposed a novel hybrid dimensionality reduction framework that integrates Principal Component Analysis (PCA) with Restricted Boltzmann Machines (RBMs) to address the challenges of high-dimensional datasets generated by Internet of Things (IoT) applications. The framework combines PCA's global linear projection capabilities
Machine learning
Researchers Prafulla Nath Dawadi, David Everton Norman, and Harel Moshe Yedidsion have filed a patent application for a method utilizing reinforcement learning to optimize substrate processing in facilities. The invention aims to maximize processing on higher-yield tools while meeting production thresholds. Key components include identifying current state data, providing it
Machine learning
Microsoft Technology Licensing LLC has patented a technology that utilizes conversational artificial intelligence (AI) to generate gestural prompts for virtual assistants and bots. This system aims to bridge the gap between language-oriented conversations and multimodal gestures, enabling more expressive interactions with users. The patent, filed on July 26, 2022, and
Machine learning
Researchers Prafulla Nath Dawadi, David Everton Norman, and Harel Moshe Yedidsion have filed a patent application for a method utilizing reinforcement learning to optimize substrate processing in facilities. The invention aims to maximize processing on higher-yield tools while meeting production thresholds. Key components include identifying current state data, providing it
Machine learning
Researchers at China Tobacco Sichuan Industrial Co. have successfully employed machine learning techniques in conjunction with FT-NIR spectroscopy to predict tobacco blend proportions with high accuracy. This innovative approach enables the development of accurate and reliable quality control systems, paving the way for improved cigarette quality and market reputation. The
Eye diseases
Research from Nanyang Technological University has detailed the application of machine learning approaches to predict treatment failure in ocular tuberculosis. This study, published in Translational Vision Science & Technology, utilized the Collaborative Ocular Tuberculosis Study (COTS) dataset of 836 patients with tubercular uveitis across 27 international eye care centers. The
Electronic records
Research from the University of Massachusetts Chan Medical School has developed and tested a novel machine learning approach to monitor the impact of computerized clinical decision support (CDS) tools on clinicians' electronic health record (EHR) activities. The approach leverages topic modeling, a latent-variable statistical machine learning method, to infer
Machine learning
Researchers from the University of Texas Austin have proposed a new model-constrained Tikhonov autoencoder neural network framework, called TAEN, capable of learning both forward and inverse surrogate models using a single arbitrary observational sample. This framework, TAEN, is designed to address the challenge of addressing scarce data regimes and overfitting
Big data
Researchers from Jilin University of Finance and Economics conducted a study to investigate how AI-driven big data analytics enhances entrepreneurial decision-making in the digital economy. The study evaluated four machine learning models to predict AI service focus and found that Gradient Boosting outperformed others with a testing R² of 0.
