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Topic Review
Large-Scale Service Function Chaining in Smart City
Smart cities leverage the Internet of Things (IoT) to collect data from various sources and employ data-driven approaches to improve the management, evaluation, and decision-making processes. From a core network perspective, service function chaining (SFC) is an enabling paradigm for elastically controlling the massive network services (NS) from IoT-empowered smart cities. SFC can effectively enforce policies and regulations set by city authorities, including data retention policies, content filtering, compliance checks, etc. Moreover, SFC optimizes service delivery, resource efficiency, quality of experience (QoE)/quality of service (QoS), and service-specific routing. To activate all the beneficial factors, mobile network operators need solutions to reflect SFC orchestration policies while ensuring efficient resource utilization and preserving QoS in large-scale networking congestion states.
  • 137
  • 16 Oct 2023
Topic Review
Smart Sensors
Sensors play a crucial role in Industry 4.0 by enabling machines to collect and analyze data in real time, which can be used to improve production processes and increase efficiency. Smart sensors can monitor a variety of parameters in an electric motor, such as temperature, vibration, and electric tension, providing valuable insight into its performance and condition. These data can be used to identify potential issues before they escalate, reducing downtime and increasing productivity.
  • 259
  • 16 Oct 2023
Topic Review
Multiple Object Tracking and High-Speed Vision
Multiple object tracking detects and tracks multiple targets in videos, such as pedestrians, vehicles, and animals. It is an important research direction in the field of computer vision, and has been widely applied in intelligent surveillance and behavior recognition. High-speed vision is a computer vision technology that aims to realize real-time image recognition and analysis through the use of fast and efficient image processing algorithms at high frame rates of 1000 fps or more. It is an important direction in the field of computer vision and is used in a variety of applications, such as intelligent transportation, security monitoring, and industrial automation.
  • 157
  • 16 Oct 2023
Topic Review Peer Reviewed
Techno-Economic Analysis of State-of-the-Art Carbon Capture Technologies and Their Applications: Scient Metric Review
Carbon dioxide (CO2) emissions are a serious hazard to human life and the ecosystem. This is the reason that many measures have been put in place by the International Energy Agency (IEA) to reduce the anthropogenic-derived CO2 concentration in the atmosphere. Today, the potential of renewable energy sources has led to an increased interest in investment in carbon capture and storage technologies worldwide. The aim of this paper is to investigate state-of-the-art carbon capture and storage (CCS) technologies and their derivations for the identification of effective methods during the implementation of evidence-based energy policies. To this extent, this study reviews the current methods in three concepts: post-combustion; pre-combustion; and oxy-fuel combustion processes. The objective of this study is to explore the knowledge gap in recent carbon capture methods and provide a comparison between the most influential methods with high potential to aid in carbon capture. The study presents the importance of using all available technologies during the post-combustion process. To accomplish this, an ontological approach was adopted to analyze the feasibility of the CCS technologies available on the market. The study findings demonstrate that priority should be given to the applicability of certain methods for both industrial and domestic applications. On the contrary, the study also suggests that using the post-combustion method has the greatest potential, whereas other studies recommend the efficiency of the oxy-fuel process. Furthermore, the study findings also highlight the importance of using life cycle assessment (LCA) methods for the implementation of carbon capture technologies in buildings. This study contributes to the energy policy design related to carbon capture technologies in buildings.
  • 3.0K
  • 16 Oct 2023
Topic Review
Intelligent Fault Diagnosis Based on Machine Learning
Intelligent fault diagnosis (IFD) plays a vital role in preventative maintenance (PM) for Industry 4.0, which can reduce downtime, improve overall system efficiency, decrease maintenance costs, enhance reliability, and extend the lifespan of machinery, as well as help to optimise operations and make informed decisions. Data-driven approaches based on deep learning (DL) have been widely accepted for IFD in smart manufacturing. Meanwhile, various deep neural network (DNN) architectures have been utilised and developed in the field of IFD. 
  • 214
  • 16 Oct 2023
Topic Review
Circular Economy and Product Durability
Due to the large and unsustainable use of valuable natural resources and electronic waste generation worldwide, which poses risks to human health and the environment, different organizations have initiated efforts to shift from a linear economy to a circular economy. A crucial aspect of promoting a circular economy is improving product durability, which can reduce resource extraction and waste because products remain in use for a longer period. Methods for measuring and indexing durability should encourage consumers to buy more durable products and incentivize manufacturers to compete in improving durability.
  • 231
  • 16 Oct 2023
Topic Review
Categories of Point Cloud Segmentation Methods
Laser point clouds have been widely used in many fields, such as autonomous driving, augmented reality and so on. Point cloud classification and segmentation are key to scene understanding. Therefore, many scholars have systematically studied point cloud classification and segmentation. Machine learning approaches are the most commonly used data analysis methods. In the field of point cloud data analysis, deep learning is used for point cloud classification and segmentation. To improve the accuracy of point cloud classification and segmentation, some researchers have drawn on image methods to handle point clouds. 
  • 461
  • 16 Oct 2023
Topic Review
Enhancing Fatigue Strength of Adhesively Bonded Composite Joints
Adhesive bonding is widely seen as the most optimal method for joining composite materials, bringing significant benefits over mechanical joining, such as lower weight and reduced stress concentrations. Adhesively bonded composite joints find extensive applications where cyclic fatigue loading takes place, but this might ultimately lead to crack damage and safety issues. Consequently, it has become essential to study how these structures behave under fatigue loads and identify the remaining gaps in knowledge to give insight into new possibilities. The fatigue life of adhesively bonded composite joints is influenced by various parameters, including joint configuration and material properties of adherends and adhesive. Numerous studies with varying outcomes have been documented in the literature. However, due to the multitude of influential factors, deriving conclusive insights from these studies for practical design purposes has proven to be challenging. Hence, this research aims to address this challenge by discussing different methods to enhance the fatigue performance of adhesively bonded composite joints. Additionally, it provides a comprehensive overview of the existing literature on adhesively bonded composite joints under cyclic fatigue loading, focusing on three main aspects: adherends modification, adhesive modification, and joints configurations. Since the effect of modifying the adhesive, adherends, and joint configurations on fatigue performance has not been comprehensively studied in the literature. 
  • 408
  • 16 Oct 2023
Topic Review
FMECA Applied to Cyber-Power Grids
Failure modes, effects, and criticality analysis (FMECA) is a qualitative risk analysis method widely used in various industrial and service applications. Despite its popularity, the method suffers from several shortcomings analyzed in the literature over the years. The classical approach to obtain the failure modes’ risk level does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language.
  • 171
  • 16 Oct 2023
Topic Review
Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles
On-road transportation of freight is central to modern economic activity. However, current on-road freight vehicles emit significant amounts of greenhouse gas emissions (GHGs), on the order of 7% of global anthropogenic emissions, along with significant amounts of local and regional air pollutants. Mitigating CO2 emissions from long-haul commercial trucking is a major challenge that must be addressed to achieve substantial reductions in greenhouse gas (GHG) emissions from the transportation sector. Extensive recent research and development programs have shown how significant near-term reductions in GHGs from commercial vehicles can be achieved by combining technological advances. 
  • 230
  • 16 Oct 2023
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