Current Issue : July-September Volume : 2024 Issue Number : 3 Articles : 5 Articles
Plastic pollution has a negative influence on biodiversity especially in aquatic ecosystems, and it has been labelled as one of the greatest dangers to biota. This paper proposes a Convolutional Neural Networks (CNN) based plastic detection model for the embedded platform to identify different shapes of underwater plastics such as bags, bottles, containers, cups, nets, pipes, ropes, snack wrappers and tarps. The model is optimized for Raspberry Pi using OpenVINO framework, with the intention to produce a cost-effective edge system for a Remote Operating Vehicle (ROV) system. The development of the model utilizes a pre-trained object detection model from YOLOv5 and the TrashCan 1.0 dataset, for training and testing. The final model exhibits a good performance, achieving more than 85% accuracy in the overall prediction, which highlights the model's accuracy and reliability in detecting and classifying underwater plastic shapes. Results from this work highlight the potential of the deep learning (DL) real-time embedded processing at the edge rather by a separate computer on land, using a cost-effective embedded platform....
Three-dimensional (3D) bioprinting embedded within a microgel bath has emerged as a promising strategy for creating intricate biomimetic scaffolds. However, it remains a great challenge to construct tissue-scale structures with high resolution by using embedded 3D bioprinting due to the large particle size and polydispersity of the microgel medium, as well as its limited cytocompatibility. To address these issues, novel uniform sub-microgels of cell-friendly cationic-crosslinked kappa-carrageenan (κ-Car) are developed through an easy-to-operate mechanical grinding strategy. These κ-Car sub-microgels maintain a uniform submicron size of around 642 nm and display a rapid jamming-unjamming transition within 5 s, along with excellent shear-thinning and self-healing properties, which are critical for the high resolution and fidelity in the construction of tissue architecture via embedded 3D bioprinting. Utilizing this new sub-microgel medium, various intricate 3D tissue and organ structures, including the heart, lungs, trachea, branched vasculature, kidney, auricle, nose, and liver, are successfully fabricated with delicate fine structures and high shape fidelity. Moreover, the bone marrow mesenchymal stem cells encapsulated within the printed constructs exhibit remarkable viability exceeding 92.1% and robust growth. This κ-Car sub-microgel medium offers an innovative avenue for achieving high-quality embedded bioprinting, facilitating the fabrication of functional biological constructs with biomimetic structural organizations....
Willmore defined embedded surfaces on f : S → E3, which is the embedding of S into Euclidean 3-space. He investigated the Euclidean metric of E3, inducing a Riemannian structure on f (S). The expression analogous to the left-hand member of the curvature K is replaced by the mean curvature H2 on f (S). Our aim is to observe the Gaussian and mean curvatures of curve–surface pairs using embedded surfaces in different curve–surface pairs and to define some developable operations on their curve–surface pairs. We also investigate the embedded surfaces using the Willmore method. We first recall the Darboux curve–surface and derive the new characterizations. This curve–surface pair is called the osculating Darboux curve–surface if its position vector always lies in the osculating Darboux plane spanned by a Darboux frame. Thus, we observed an osculating Darboux curve–surface pair. We also obtained the ∼D -scroll of the curve–surface pair and involute ∼D-scroll of the curve–surface pair with some differential geometric elements and found ∼D (α,M)(s) and ∼ D∗ (α,M)(s)-scrolls of the curve–surface pair (α,M)....
The moisture content within the concrete pore network significantly influences the mechanical, thermal, and durability characteristics of concrete structures. This paper introduces a novel fully embedded wireless temperature and relative humidity sensor connected to an automatic acquisition system designed for continuous concrete monitoring. Relative humidity measurements from this new sensor are compared with those obtained by a commercial system based on the borehole method at different depths (2.5 and 4.0 cm) and exposure conditions (oven drying and humid chamber). The results allow for proving that both systems provide consistent internal relative humidity measurements aligned with the exposure conditions and highlight the capability of fully embedded wireless sensors as a practical and reliable alternative to the conventional borehole method. Additionally, the continuous monitoring of the wireless cast-in sensor exhibits reliability during unintended temperature fluctuations, emphasizing the effectiveness of permanently installed sensors in promptly detecting unintended curing variations in real time. The continuous real-time information provided combined with the practicality of these sensors might assist construction managers to improve the quality control of the concrete curing process and shrinkage behavior, and ensure the integrity of concrete surface finishing....
In recent years, the growing demand for efficient and sustainable energy management has led to the development of innovative solutions for embedded systems. One such solution is the integration of hybrid nanogrid energy management systems into various applications. There are currently many energy management systems in different domains, such as buildings, electric vehicles, or even naval transport. However, an embedded nanogrid management system is subject to several constraints that are not sufficiently studied in the literature. Indeed, such a system often has a limited energy reserve and is isolated from any energy supply for a long time. This paper aims to provide a comprehensive overview of the current state of research, advancements, and challenges in the field of hybrid nanogrid energy management systems. Furthermore, it offers a comparative analysis between hybrid nanogrids and microgrids and the implications of their integration in embedded systems. This paper also discusses the key components, operation principles, optimization strategies, real-world implementations, challenges, and future prospects of hybrid nanogrid energy management systems. Moreover, it highlights the significance of such systems in enhancing energy efficiency, reducing carbon footprints, and ensuring reliable power supply....
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