Comparison of estimating vegetation index for outdoor free-range pig production using convolutional neural networks.

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction.

Estimating vegetation index for outdoor free-range pig production using YOLO.

The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m. The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition.

Evaluation of Reducing NO and SO Concentration in Nano SiO-TiO Photocatalytic Concrete Blocks.

The use of titanium dioxide in concrete block pavements is a promising approach to reduce air pollution in the roadside. When TiO is used as an additive of cement concrete or mortar, it is not dispersed uniformly due to agglomeration between particles causing the degradation of photocatalytic reaction. To improve the photocatalytic performance of TiO, the Nano SiO-TiO (NST) has been developed by coating TiO with SiO as a support using the sol-gel method.

Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic.

This study utilizes modeling and simulation to analyze coronavirus (COVID-19) infection trends depending on government policies. Two modeling requirements are considered for infection simulation: (1) the implementation of social distancing policies and (2) the representation of population movements. To this end, we propose an extended infection model to combine analytical models with discrete event-based simulation models in a hybrid form.

A study on engineering characteristics of asphalt concrete using filler with recycled waste lime.

This study focuses on determining the engineering characteristics of asphalt concrete using mineral fillers with recycled waste lime, which is a by-product of the production of soda ash (Na(2)CO(3)). The materials tested in this study were made using a 25%, 50%, 75%, and 100% mixing ratio based on the conventional mineral filler ratio to analyze the possibility of using recycled waste lime. The asphalt concretes, made of recycled waste lime, hydrated lime, and conventional asphalt concrete, were evaluated through their fundamental engineering properties such as Marshall stability, indirect tensile strength, resilient modulus, permanent deformation characteristics, moisture susceptibility, and fatigue resistance.