Results 51 to 60 of about 38,696 (266)
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
The paper suggests a method for determining the optimal location of service points (warehouses) based on the method for optimal planning of radiation therapy of malignant tumors.
Viktor Danchuk +2 more
doaj +1 more source
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Automatic Determination of Quasicrystalline Patterns from Microscopy Images
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
IntroductionA two-warehouse deterministic inventory system for purchases of short-expiry items with low purchasing costs is modelled. The total cost of the replenishment cycle is arrived at by implementing multiple just-in-time (JIT) purchases for the ...
R. Thilagavathi +5 more
doaj +1 more source
Development of an ANFIS Model for the Optimization of a Queuing System in Warehouses
Queuing systems (QS) represent everyday life in all business and economic systems. On the one hand, and there is a tendency for their time and cost optimization, but on the other hand, they have not been sufficiently explored.
Mirko Stojčić +3 more
doaj +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Perbandingan Algoritma Simulated Annealing dan Harmony Search dalam Penerapan Picking Order Sequence
Implementation of mobile rack warehouse is commonly used in manufacturing industry because it can minimize the warehouse area used. Applying picking orders in taking of Stock Keeping Unit (SKU) on mobile rack warehouses could give fast loading order ...
Tanti Octavia, Septiananda Angelica
doaj

