Journal of Physics: Conference Series 

About: Journal of Physics: Conference Series is an academic journal published by IOP Publishing. The journal publishes majorly in the area(s): Computer science & Engineering. It has an ISSN identifier of 1742-6588. Over the lifetime, 7910 publications have been published receiving 2511 citations.

Road Aerial Object Detection Based on Improved YOLOv5

Abstract: In this paper, the target detection technology based on deep learning is applied to the process of object detection in highway aerial photography. By detecting road objects such as vehicles or crosswalk, it lays the foundation for digitalization and informationization of roads. Firstly, the unmanned aerial vehicle is used to collect road images. Then based on YOLOv5 network, aiming at the problem of small detection target, attention mechanism is introduced to weigh different channels of feature graph, and SoftPool is introduced in SPP module to improve pooling operation and retain more detailed feature information. The experimental results show that the improved YOLOv5 network can identify and locate objects on aerial roads more accurately and effectively.

An Explicit Note on the Existence Theorem of Optimal Control Problem

Abstract: This short note presents an explicit step-by-step proof of the existence theorem of an optimal control problem applied to a deterministic model for a vector-borne disease.

Research on Safety Helmet Detection Algorithm of Power Workers Based on Improved YOLOv5

Abstract: The traditional helmet detection algorithm in power industry has low precision and poor robustness. In response to this problem, the helmet detection algorithm based on improved YOLOv5 (You only look once) is put forward in this paper. Firstly, the YOLOv5 network structure is improved. By increasing the size of the feature map, one scale is added to the original three scales, and the added 160*160 feature map can be used for the detection of small targets; Secondly, the K-means is used for re-clustering the helmet data set to get more suitable priori anchor boxes. The experimental results illustrate that the average accuracy of the improved YOLOv5 algorithm is increased by 2.9% and reaching 95% compared with the initial model, and the accuracy of helmet recognition is increased by 2.4% and reaching 94.6%. This algorithm reduces the rates of missing detection and misdetection of small target detection in original network, and has strong practicability and advanced nature. It can satisfy the requirements of real-time detection and has a certain role in promoting the safety of power industry.

Polyhydroxybutyrate/polylactic acid blends: An alternative feedstock for 3D printed bone scaffold model

Abstract: In this research, we developed 3D printing filaments from polyhydroxybutyrate (PHB)/poly(lactic acid) (PLA) blends to further its use in a fused filament fabrication (FFF) 3D printing technique as an alternative feedstock for manufacturing bone scaffold model. The filaments were fabricated with blending ratios of PHB/PLA at 100/0, 90/10, 70/30, 50/50, 30/70, 10/90, and 0/100 %wt. using an extrusion process. Furthermore, 10 phr of polypropylene glycol (PPG) was added as a processing aid to enhance the processability. The results of MFR showed that the suitable temperature for 3D printing of all blended filaments is 190 °C. The changes in thermal properties indicate the partial compatibility between PHB and PLA in the blends. PLA plays a vital role in improving the mechanical properties of PHB. 3D printing filament from PHB/PLA blends has been successfully developed.

Model-free control of the dynamic lift of a wind turbine blade section: experimental results

Abstract: This work addresses the problem of developing control algorithms for the control of the aerodynamic lift of wind turbine blades using air injection, taking into account disturbances caused by turbulent perturbations. For this, a test bench is used where the lift of a 2D blade section in a wind tunnel can be controlled by a set of micro-jets close to the trailing edge. Through a continuous, local identification of the lift variations a model-free control that does not need any prior knowledge of the system is proposed. It allows the control of the flow of the micro-jets and stabilizes the lift around a tracking reference. The ability of the proposed control algorithm to track the lift reference when subjected to external perturbations, i.e., gusts, is discussed. In particular, this work demonstrates that the lift can be set to particular values using the proposed control strategy, and can be re-stabilized to pre-gust lift conditions. Experimental results illustrate globally the feasibility of such a control.