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Topic Review
Steganography and Steganalysis in VoIP
The rapid advance and popularization of VoIP (Voice over IP) has also brought security issues. VoIP-based secure voice communication has two sides: first, for legitimate users, the secret voice can be embedded in the carrier and transmitted safely in the channel to prevent privacy leakage and ensure data security; second, for illegal users, the use of VoIP Voice communication hides and transmits illegal information, leading to security incidents. Therefore, in recent years, steganography and steganography analysis based on VoIP have gradually become research hotspots in the field of information security. Steganography and steganalysis based on VoIP can be divided into two categories, depending on where the secret information is embedded: steganography and steganalysis based on voice payload or protocol. The former mainly regards voice payload as the carrier, and steganography or steganalysis is performed with respect to the payload. It can be subdivided into steganography and steganalysis based on FBC (fixed codebook), LPC (linear prediction coefficient), and ACB (adaptive codebook). The latter uses various protocols as the carrier and performs steganography or steganalysis with respect to some fields of the protocol header and the timing of the voice packet. It can be divided into steganography and steganalysis based on the network layer, the transport layer, and the application layer. Recent research results of steganography and steganalysis based on protocol and voice payload are classified in this paper, and the paper also summarizes their characteristics, advantages, and disadvantages. The development direction of future research is analyzed. Therefore, this research can provide good help and guidance for researchers in related fields. 
  • 1.0K
  • 17 Sep 2024
Topic Review
Digital Product Passport in Modern Manufacturing
Digital Product Passport (DPP)’s impact on supply chain transparency, providing crucial product lifecycle information that bolsters decision-making and facilitates optimal resource management. DPP model, when applied to sectors such as electronics manufacturing, promises transformative results. 
  • 369
  • 23 Apr 2024
Topic Review
Smart Grid
Traditional power grid models are based on a central system for generating and distributing energy and have undergone significant changes in recent years. The integration of the latest generation of technologies, rare in critical infrastructure such as the Internet of Things (IoT), has facilitated the evolution to a more dynamic and connected power grid model now known as the Smart Grid (SG). SG’s contributions result from introducing a mutual flow of information between manufacturers and customers, from which both can benefit. This flow enables fine-grained consumption measurements reported to each energy service provider in near real-time to provide consumers with up-to-date price data or control a utility that contains the grid’s energy load in real-time according to actual demand, allowing utilities to perform accurate demand response procedures by anticipating high demand peaks, avoiding and mitigating power outages, and distributing the load on available generators. On the other hand, consumers can take part in programs that reduce electricity consumption in the event of rising energy prices while using home-generated (renewable) electricity (such as the so-called microgrid).
  • 727
  • 17 Apr 2024
Topic Review
Line Feature, Vanishing Points and Manhattan World Analysis
In conventional point-line visual inertial odometry systems under indoor environment, consideration of spatial position recovery and line feature classification can improve localization accuracy. A monocular visual inertial odometry based on structured and unstructured line features of vanishing points is proposed. First, degeneracy phenomenon caused by special geometric relationship between epipoles and line features is analyzed in process of triangulation, and a degeneracy detection strategy is designed to determine the location of the epipoles. Then, considering the property that vanishing point and epipole coincide at infinity, vanishing point feature is introduced to solve the degeneracy and direction vector optimization problem of line features. Finally, threshold constraints are used to categorize straight lines into structural and non-structural features under the Manhattan world assumption, and the vanishing point measurement model is added to the sliding window for joint optimization. Comparative tests on the EuRoC and TUM-VI public datasets validated the effectiveness of the proposed method.
  • 251
  • 18 Mar 2024
Topic Review
Anomaly Detection in Autonomous Robotic Missions
An anomaly in autonomous robotic missions (ARM) is a deviation from the expected behaviour, performance, or state of the robotic system and its environment, which may impact the mission’s objectives, safety, or efficiency; and this anomaly can be caused either by system faults or the change in the environmental dynamics of interaction. The nuanced understanding of anomaly categories facilitates a more strategic approach, ensuring that detection methods are more effective in addressing the specific nature of the anomaly.
  • 603
  • 11 Mar 2024
Topic Review
Control Technology of Offshore Wind Power Systems
As global energy crises and climate change intensify, offshore wind energy, as a renewable energy source, is given more attention globally. The wind power generation system is fundamental in harnessing offshore wind energy, where the control and design significantly influence the power production performance and the production cost.
  • 374
  • 06 Mar 2024
Topic Review
Definition of Autonomous Cycles for the Agroindustrial Sector
One of the great current challenges of Micro, Small and Medium Enterprises (MSMEs) is to dynamically innovate to improve their supply of goods, products, and services in order to respond to the changing needs of the market. In particular, several studies have concluded that investment in innovation has a high impact on the competitiveness of organizations, which can lead to the introduction of new products and processes. Thus, innovation is a means for companies to adapt to remain in the market, considering available resources.
  • 209
  • 20 Feb 2024
Topic Review
Supervised Learning Approaches for Mobile Robot Control
Machine learning (ML) is a branch of artificial intelligence that has been developing at a dynamic pace in recent years. ML is also linked with Big Data, which are huge datasets that need special tools and approaches to process them. ML algorithms make use of data to learn how to perform specific tasks or make appropriate decisions. ML approaches that have been applied to the task of mobile robot control are divided into the following: supervised learning, unsupervised learning, and reinforcement learning. The supervised learning methods are grouped into two main categories of regression and classification.
  • 207
  • 18 Feb 2024
Topic Review
Machine Learning for Building Energy Management
Machine learning (ML) algorithms are now part of everyday life, as many technological devices use these algorithms. Machine learning (ML) is now used in many industrial and scientific fields, from aerospace to marketing and advertising. In the architecture, engineering and construction (AEC) sector, ML models and algorithms can be applied to building automation systems (BASs) and building digital twins (BDT) to improve building energy efficiency and flexibility by making use of widely available building operational data. Such systems can automate building management, reducing global consumption of primary resources (i.e., energy and water), increasing indoor comfort, increasing structural safety, and reducing the need for building maintenance. 
  • 286
  • 18 Feb 2024
Topic Review
Building Management Systems and Operation
Artificial neural networks (ANNs) have become a cornerstone in efficiently managing building energy management systems (BEMSs) as they offer advanced capabilities for prediction, control, and optimization. 
  • 184
  • 02 Feb 2024
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