Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.

This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices.

Korean Cattle 3D Reconstruction from Multi-View 3D-Camera System in Real Environment.

The rapid evolution of 3D technology in recent years has brought about significant change in the field of agriculture, including precision livestock management. From 3D geometry information, the weight and characteristics of body parts of Korean cattle can be analyzed to improve cow growth. In this paper, a system of cameras is built to synchronously capture 3D data and then reconstruct a 3D mesh representation. In general, to reconstruct non-rigid objects, a system of cameras is synchronized and calibrated, and then the data of each camera are transformed to global coordinates. However, when reconstructing cattle in a real environment, difficulties including fences and the vibration of cameras can lead to the failure of the process of reconstruction. A new scheme is proposed that automatically removes environmental fences and noise. An optimization method is proposed that interweaves camera pose updates, and the distances between the camera pose and the initial camera position are added as part of the objective function. The difference between the camera's point clouds to the mesh output is reduced from 7.5 mm to 5.5 mm. The experimental results showed that our scheme can automatically generate a high-quality mesh in a real environment. This scheme provides data that can be used for other research on Korean cattle.

Properties of Stone Matrix Asphalt Modified with Polyvinyl Chloride and Nano Silica.

In this study, the effects of polyvinyl chloride (PVC) and nano silica (NS) as modifiers on the properties of stone matrix asphalt (SMA) were studied. The experiment was performed with five modes: 1% NS was mixed into SMA; 5% PVC was mixed into SMA; and the ratio of NS was changed (1, 2, and 3%) with 5% PVC being mixed into SMA. The properties of modified and unmodified SMA materials were determined and compared by performing the penetration test, softening points test, viscosity measurements, dynamic shear rheometry, and multiple stress creep recovery under aging conditions. Moreover, the properties of the modified SMA were also determined in terms of Marshall stability, water stability, and rutting resistance. The obtained results indicate that the physical properties of SMA materials could be significantly improved by using a combination of PVC and NS as a modifier. Moreover, the SMA mixtures modified with PVC and NS exhibited high Marshall stability, good moisture damage resistance, and rutting resistance. Modified SMA mixtures with 5% PVC and 1% NS exhibited the best quality. This research has opened up a new avenue for the development of effective additives for SMA materials.

Effect of Ethanol Stress on Fermentation Performance of Saccharomyces cerevisiae Cells Immobilized on Nypa fruticans Leaf Sheath Pieces.

The yeast cells of Saccharomyces cerevisiae immobilized on Nypa fruticans leaf sheath pieces were tested for ethanol tolerance (0, 23.7, 47.4, 71.0 and 94.7 g/L). Increase in the initial ethanol concentration from 23.7 to 94.7 g/L decreased the average growth rate and concentration of ethanol produced by the immobilized yeast by 5.2 and 4.1 times, respectively. However, in the medium with initial ethanol concentration of 94.7 g/L, the average growth rate, glucose uptake rate and ethanol formation rate of the immobilized yeast were 3.7, 2.5 and 3.5 times, respectively, higher than those of the free yeast. The ethanol stress inhibited ethanol formation by Saccharomyces cerevisiae cells and the yeast responded to the stress by changing the fatty acid composition of cellular membrane. The adsorption of yeast cells on Nypa fruticans leaf sheath pieces of the growth medium increased the saturated fatty acid (C16:0 and C18:0) mass fraction in the cellular membrane and that improved alcoholic fermentation performance of the immobilized yeast.