Generic color correction for tone mapping operators in high dynamic range imaging.

One of the significant challenges in tone mapping is to preserve the perceptual quality of the tone-mapped images. Traditional tone mapping operators (TMOs) compress the luminance of high dynamic range (HDR) images with little to no consideration of image color information resulting into suboptimal colors. Existing color management algorithms require either manual parameter tuning or introducing lightness and hue shifts.

Not all soil carbon is created equal: Labile and stable pools under nitrogen input.

Anthropogenic activities have raised nitrogen (N) input worldwide with profound implications for soil carbon (C) cycling in ecosystems. The specific impacts of N input on soil organic matter (SOM) pools differing in microbial availability remain debatable. For the first time, we used a much-improved approach by effectively combining the C natural abundance in SOM with 21 years of C-C vegetation conversion and long-term incubation.

Non-invasive detection of mental fatigue in construction equipment operators through geometric measurements of facial features.

Introduction: Prolonged operation of construction equipment could lead to mental fatigue, which can increase the chances of human error-related accidents as well as operators' ill-health. The objective detection of operators' mental fatigue is crucial for reducing accident risk and ensuring operator health. Electroencephalography, photoplethysmography, electrodermal activity, and eye-tracking technology have been used to mitigate this issue.

Method for developing and using high quality reference images to evaluate tone mapping operators.

With the advancement of imaging technology, high dynamic range (HDR) images can now be captured and displayed to produce realistic effects. Tone mapping operators (TMOs) are used to map HDR radiance to the displayable range. A reliable TMO would play a significant role in the accurate reproduction of HDR scenes.

Plastic Waste Management Strategies and Their Environmental Aspects: A Scientometric Analysis and Comprehensive Review.

Plastic consumption increases with the growing population worldwide and results in increased quantities of plastic waste. There are various plastic waste management strategies; however, the present management progress is not sustainable, and plastic waste dumping in landfills is still the most commonly employed strategy. Being nonbiodegradable, plastic waste dumping in landfills creates several environmental and human health problems.

Exploring the potential effect of Achnatherum splendens L.-derived biochar treated with phosphoric acid on bioavailability of cadmium and wheat growth in contaminated soil.

Biochar remediation efficiency could be enhanced through numerous treatments such as acids treatment. Still, there has little work done on HPO-treated biochar particularly biochar derived from Achnatherum splendens L. feedstock.

Comparative Study of Supervised Machine Learning Algorithms for Predicting the Compressive Strength of Concrete at High Temperature.

High temperature severely affects the nature of the ingredients used to produce concrete, which in turn reduces the strength properties of the concrete. It is a difficult and time-consuming task to achieve the desired compressive strength of concrete. However, the application of supervised machine learning (ML) approaches makes it possible to initially predict the targeted result with high accuracy.

Development of sediment load estimation models by using artificial neural networking techniques.

This study aims at the development of an artificial neural network-based model for the estimation of weekly sediment load at a catchment located in northern part of Pakistan. The adopted methodology has been based upon antecedent sediment conditions, discharge, and temperature information. Model input and data length selection was carried out using a novel mathematical tool, Gamma test.