Model Compression Methods for YOLOv5: A Review

Over the past few years, extensive research has been devoted to enhancing YOLO object detectors. Since its introduction, eight major versions of YOLO have been introduced with the purpose of improving its accuracy and efficiency. While the evident merits of YOLO have yielded to its extensive use in many areas, deploying it on resource-limited devices poses challenges. To address this issue, various neural network compression methods have been developed, which fall under three main categories, namely network pruning, quantization, and knowledge distillation. The fruitful outcomes of utilizing model compression methods, such as lowering memory usage and inference time, make them favorable, if not necessary, for deploying large neural networks on hardware-constrained edge devices. In this review paper, our focus is on pruning and quantization due to their comparative modularity. We categorize them and analyze the practical results of applying those methods to YOLOv5. By doing so, we identify gaps in adapting pruning and quantization for compressing YOLOv5, and provide future directions in this area for further exploration. Among several versions of YOLO, we specifically choose YOLOv5 for its excellent trade-off between recency and popularity in literature. This is the first specific review paper that surveys pruning and quantization methods from an implementation point of view on YOLOv5. Our study is also extendable to newer versions of YOLO as implementing them on resource-limited devices poses the same challenges that persist even today. This paper targets those interested in the practical deployment of model compression methods on YOLOv5, and in exploring different compression techniques that can be used for subsequent versions of YOLO.Comment: 18 pages, 7 Figure

Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfinding

Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications, often being the fundamental step in multi-agent systems. The increasing complexity of MAPF in complex and crowded environments, however, critically diminishes the effectiveness of existing solutions. In contrast to other studies that have either presented a general overview of the recent advancements in MAPF or extensively reviewed Deep Reinforcement Learning (DRL) within multi-agent system settings independently, our work presented in this review paper focuses on highlighting the integration of DRL-based approaches in MAPF. Moreover, we aim to bridge the current gap in evaluating MAPF solutions by addressing the lack of unified evaluation metrics and providing comprehensive clarification on these metrics. Finally, our paper discusses the potential of model-based DRL as a promising future direction and provides its required foundational understanding to address current challenges in MAPF. Our objective is to assist readers in gaining insight into the current research direction, providing unified metrics for comparing different MAPF algorithms and expanding their knowledge of model-based DRL to address the existing challenges in MAPF.Comment: 36 pages, 10 figures, published in Artif Intell Rev 57, 41 (2024

Carbon Nanostructure‐Based Scale Sensors Using Inkjet Printing and Casting Techniques

In this chapter, the fabrication and characterization of scale sensor using carbon nanotubes (CNTs) are discussed. Two different methods are used to prepare the carbon nanomaterials for the sensor fabrication: CNT casting and the CNT inkjet printing. In addition, the sensors are integrated into Kelvin architectures. The electrical resistance of the carbon nanomaterial films is measured with and without adding a drop of brine to the surface of the film. The films are characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), transmission electron microscopy (TEM), and energy dispersive X‐ray spectroscopy (EDS). Electrical resistance of the casted CNT films and five layers of CNT inkjet printing are found to be close to 40.0 kΩ and 1.00 kΩ, respectively. Adding one drop of brine solution on the surface of the casted CNT film and five layers of CNT inkjet printing changed the resistance by 50% and 75%, respectively. The resetting process is done for all sensors by soaking in deionized water (DI water) for some time, and the electrical resistance is measured and found to be close to the initial electrical resistance

The commitment of The Jordanian Industrial Companies in Applying Environmental Accounting

Accounting ideology is becoming highly concerned with the environmental responsibility. This study diagnoses the importance of environmental accounting principles of all enterprises .Environmental commitment calls for the need to evaluate any project in terms of its contribution to its environmental responsibilities. This study aims at assessing the environmental responsibility unit of Jordan’s Industrial Companies listed at ASE, and how the financial department in each company copes with the environmental aspects. Study results have indicated that all Jordan’s Industrial Companies are in general committed towards environmental accounting and they keep pace to the developments in this field. Results also revealed that environmental accounting function in industrial corporations keeps pace with the developments in environmental accounting. Key Words: Environmental Accounting, Hypothesis Testing, Validity, Reliability JEL Codes:  Q56, C12 ,C520,Q26

Flexural Ductility Behavior of Strengthened Reinforced Concrete Beams Using Steel and CFRP Plates

Reinforced concrete beams are commonly retrofitted using Carbon Fiber Reinforced Plastic (CFRP) plates as the technique is both inexpensive and unobtrusive. However, tests have shown that CFRP plates tend to debond at low strains, which can severely limit the ductility. Structural strengthening of beams subjected to flexure can be achieved using different retrofitting materials. The mostly used other retrofitting materials are; high strength galvanized steel plates (HSGS plates) and normal strength steel plates (NSS plates). This paper reports the behavior of retrofitted beams with each of these three materials. The experimental results of this study suggest that (HSGS plates) can be used to increase the strength of reinforced concrete structures with little, if any, loss of ductility

Dentists and Hepatitis B Vaccination – An In Vivo National Study

Hepatitis B continues to be a serious occupational concern for dental healthcare practitioners, with the possibility of transmission occurring during patient care practices. The incidence of hepatitis B amongst dentists, the factors raising their occupational risk, and the efficiency of vaccination programs in reducing this risk are all examined in this paper\u27s methodical evaluation of the body of prior research. This study addresses the important confluence of hepatitis B infection, occupational exposure, and vaccination status amongst dentists. In addition, it provides methods for improving the protection of dental professionals against hepatitis B infection by summarizing major findings and highlighting gaps in current knowledge, assuring the safety of both healthcare workers and their patients. The main objective of the study is to assess the relationship between Hepatitis B vaccination status and immunization level as measured by anti-HBs titer among a population of 192 dentists in Lebanon