Work Force

A novel artificial intelligent model for predicting water treatment efficiency of various biochar systems based on artificial neural network and queuing search algorithm.

This study aims at providing a robust artificial intelligent model for predicting the efficiency of heavy metal removal from aqueous solutions of biochar systems with high accuracy and reliability. Not only is it environmentally significant, but it is also a powerful tool for improving biochar adsorption efficiency, reducing the risk of a global water shortage. Accordingly, 22 types of biomass fee...

Evaluation of green lean production in textile industry: a hybrid fuzzy decision-making framework.

Textile industry is an old and effective industry in Iran. However, due to its age and high energy consumption, this industry has low profitability and entrepreneurship. One of the most important problems of the weaving industry is the issue of waste regarding manpower, materials, machinery, and especially energy consumption. Another problem is environmental pollution. In this paper, using a multi...

Topology Automated Force-Field Interactions (TAFFI): A Framework for Developing Transferable Force Fields.

Force-field development has undergone a revolution in the past decade with the proliferation of quantum chemistry based parametrizations and the intro...

Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression.

BACKGROUND AND OBJECTIVES: Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-...

Substituting clinical features using synthetic medical phrases: Medical text data augmentation techniques.

Biomedical natural language processing (NLP) has an important role in extracting consequential information in medical discharge notes. Detecting meani...

Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.

Finding optimal parameters for force fields used in molecular simulation is a challenging and time-consuming task, partly due to the difficulty of tun...

Davis Computational Spectroscopy Workflow-From Structure to Spectra.

We describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice ...

Implementation of a standardized robotic assistant surgical training curriculum.

Since 2000, robotic-assisted surgery has rapidly expanded into almost every surgical sub-specialty. Despite the popularity of robotic surgery across t...

Semi-HIC: A novel semi-supervised deep learning method for histopathological image classification.

Histopathological images provide a gold standard for cancer recognition and diagnosis. Existing approaches for histopathological image classification ...

Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most establis...

CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum...

Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results.

This study aims to determine how randomly splitting a dataset into training and test sets affects the estimated performance of a machine learning mode...

A stochastic modeling approach for analyzing water resources systems.

Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the w...

Deep learning for colon cancer histopathological images analysis.

Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours. Unfortunately, existing methods remain limited when faced wi...

Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task spe...

The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings.

Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their...

Disease ontologies for knowledge graphs.

BACKGROUND: Data integration to build a biomedical knowledge graph is a challenging task. There are multiple disease ontologies used in data sources a...

Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases.

Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, ...

Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed ...

Transfer-RLS method and transfer-FORCE learning for simple and fast training of reservoir computing models.

Reservoir computing is a machine learning framework derived from a special type of recurrent neural network. Following recent advances in physical res...