We present a machine learning approach, based on the genetic algorithms (GA), that can be used to reconstruct inflationary potential directly from cosmological data. create pipeline consisting of GA, primordial code and Boltzmann calculate theoretical predictions, cosmic microwave background (CMB) As proof concept, we apply our methodology Planck CMB data explore functional space single-field p...

In this paper, a novel approach proposed for structural damage detection from limited number of sensors using extreme learning machine (ELM). As the number of sensors used to measure modal data is normally limited and usually are less than the number of DOFs in the finite element model, the model reduction approach should be used to match with incomplete measured mode shapes. The second-order a...

Colorectal cancer (CRC) is one of the leading cancers in the world and early-screening is still the best method of cancer patient survival. However, colonoscopy as the current gold standard is not without flaws and an emerging technique called surface-enhanced Raman spectroscopy (SERS) coupled with machine learning is a possible candidate that could be applied in parallel with colonoscopy. This...

Colorectal cancer (CRC) is one of the leading cancers in the world and early-screening is still the best method of cancer patient survival. However, colonoscopy as the current gold standard is not without flaws and an emerging technique called surface-enhanced Raman spectroscopy (SERS) coupled with machine learning is a possible candidate that could be applied in parallel with colonoscopy. This...

Supervised learning aims to build a function or model that seeks as many mappings possible between the training data and outputs, where each will predict label match its corresponding ground-truth value. Although supervised has achieved great success in tasks, sufficient supervision for labels is not accessible domains because accurate labelling costly laborious, particularly medical image anal...