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Topic Review
Network Intrusion Detection Systems Using Artificial Intelligence/Machine Learning
The rapid growth of the Internet and communications has resulted in a huge increase in transmitted data. These data are coveted by attackers and they continuously create novel attacks to steal or corrupt these data. The growth of these attacks is an issue for the security of systems and represents one of the biggest challenges for intrusion detection. An intrusion detection system (IDS) is a tool that helps to detect intrusions by inspecting the network traffic. Although many researchers have studied and created new IDS solutions, IDS still needs improving in order to have good detection accuracy while reducing false alarm rates. 
  • 4.1K
  • 23 Dec 2022
Topic Review
On Predictive Maintenance in Industry 4.0
In the era of the fourth industrial revolution, several concepts have arisen in parallel with this new revolution, such as predictive maintenance, which today plays a key role in sustainable manufacturing and production systems by introducing a digital version of machine maintenance. The data extracted from production processes have increased exponentially due to the proliferation of sensing technologies. Even if Maintenance 4.0 faces organizational, financial, or even data source and machine repair challenges, it remains a strong point for the companies that use it. Indeed, it allows for minimizing machine downtime and associated costs, maximizing the life cycle of the machine, and improving the quality and cadence of production.
  • 4.1K
  • 24 Aug 2022
Topic Review
Sign Language Recognition Models
A hybrid system for sign language is a combination of both vision-sensor-based and combination of different sensors based models. 
  • 4.0K
  • 01 Jun 2022
Topic Review
Social Robots in Special Education
In recent years, social robots have become part of a variety of human activities, especially in applications involving children, e.g., entertainment, education, companionship. The interest of this work lies in the interaction of social robots with children in the field of special education. 
  • 4.0K
  • 23 Jun 2021
Topic Review
Cybersecurity Practices for Social Media Users
Cybersecurity is a collection of technologies established to protect the cyber environment of an individual user or organization. There are many cyber threats existing within the social media platform, such as loss of productivity, cyber bullying, cyber stalking, identity theft, social information overload, inconsistent personal branding, personal reputation damage, data breach, malicious software, service interruptions, hacks, and unauthorized access to social media accounts. It is also revealed that demographic factors, for example age, gender, and education level, may not necessarily be influential factors affecting the cyber awareness of the internet users.
  • 3.9K
  • 10 Feb 2022
Topic Review
Urban Land Use Planning
Urbanization is persistent globally and has increasingly significant spatial and environmental consequences. It is especially challenging in developing countries due to the increasing pressure on the limited resources, and damage to the bio-physical environment.
  • 3.8K
  • 13 Oct 2021
Topic Review
Videos Data Augmentation for Deep Learning Models
In most Computer Vision applications, Deep Learning models achieve state-of-the-art performances. One drawback of Deep Learning is the large amount of data needed to train the models. Unfortunately, in many applications, data are difficult or expensive to collect. Data augmentation can alleviate the problem, generating new data from a smaller initial dataset. Geometric and color space image augmentation methods can increase accuracy of Deep Learning models but are often not enough. More advanced solutions are Domain Randomization methods or the use of simulation to artificially generate the missing data. Data augmentation algorithms are usually specifically designed for single images. Most recently, Deep Learning models have been applied to the analysis of video sequences.
  • 3.8K
  • 25 Mar 2022
Topic Review
The Modulation Recognition Method Based on Deep Learning
Deep learning is a powerful artificial intelligence technology that can learn features from a large amount of data and fit nonlinear networks, so it is widely used in the fields of computer vision, natural language processing, and speech recognition, and has achieved tremendous success. Since mobile communication networks are able to generate large amounts of different types of data at a very fast pace, relevant researchers have applied deep learning to the field of communication, bringing opportunities for the development of communication technologies. For example, signal modulation identification in wireless communication can be done using deep learning techniques, and deep learning-based modulation identification methods have better robustness than traditional AMR methods and higher accuracy rates. There are many excellent neural networks in deep learning, such as convolutional neural network (CNN), recurrent neural network (RNN), etc. Among them, CNN is good at processing image data and RNN is good at processing sequence signals. CNN and RNN are widely used in AMR. The application of these neural networks to deep learning is discussed.
  • 3.7K
  • 08 Oct 2022
Topic Review
Autonomous Vehicles
An Autonomous Vehicle (AV), or a driverless car, or a self-driving vehicle is a car, bus, truck, or any other vehicle that is able to drive from point A to point B and perform all necessary driving functions, without any human intervention. An Autonomous Vehicle is normally equipped with different types of sensors to perceive the surrounding environment, including Normal Vision Cameras, Infrared Cameras, RADAR, LiDAR, and Ultrasonic Sensors.  An autonomous vehicle should be able to detect and recognise all type of road users including surrounding vehicles, pedestrians, cyclists, traffic signs, road markings, and can segment the free spaces, intersections, buildings, and trees to perform a safe driving task.  Currently, no realistic prediction expects we see fully autonomous vehicles earlier than 2030. 
  • 3.7K
  • 22 Jun 2025
Topic Review
Noise Removal Filter for LiDAR Point Clouds
Light Detection and Ranging (LiDAR) is a critical sensor for autonomous vehicle systems, providing high-resolution distance measurements in real-time. However, adverse weather conditions such as snow, rain, fog, and sun glare can affect LiDAR performance, requiring data preprocessing.
  • 3.7K
  • 24 May 2023
Topic Review
Land Surface Model
Land Surface Models (LSMs) are important components of the climate models, which help to capture the water, energy, and momentum exchange between the land surface and the atmosphere, providing lower boundary conditions to the atmospheric models.
  • 3.7K
  • 02 Apr 2021
Topic Review
Avalanche (Consensus Protocol)
Avalanche is a protocol for solving consensus in a network of unreliable machines, where failures may be crash-fault or Byzantine. The protocol was anonymously introduced on IPFS on May 2018 and was formalized in more detail by Cornell University researchers in 2019. The protocol has four basic interrelated mechanisms that compose structural support of the consensus tool. These four mechanisms are Slush, Snowflake, Snowball, and Avalanche. By using uses randomized sampling and metastability to ascertain and persist transactions, It represents a new protocol family. Although the original paper focused on a single protocol, namely Avalanche, it implicitly introduced a broad spectrum of voting-based, or quorum-based consensus protocols, called the Snow family. While Avalanche is a single instantiation, the Snow family seems to be able to generalize all quorum-based voting protocols for replica control. Unlike prior quorum-based work, the Snow family enables arbitrarily parametrizable failure probability at the quorum intersection level. Standard quorum-based protocols define this failure probability to be precisely zero, but by introducing errors in the quorum intersection, a larger set of consensus protocol design is available.
  • 3.7K
  • 03 Nov 2022
Topic Review
Attention Mechanism for Remote Sensing
Machine learning, particularly deep learning (DL), has become a central and state-of-the-art method for several computer vision applications and remote sensing (RS) image processing. Researchers are continually trying to improve the performance of the DL methods by developing new architectural designs of the networks and/or developing new techniques, such as attention mechanisms. Since the attention mechanism has been proposed, regardless of its type, it has been increasingly used for diverse RS applications to improve the performances of the existing DL methods.
  • 3.5K
  • 24 Nov 2021
Topic Review
HVAC Systems of Smart Building
Early fault detection and diagnosis in heating, ventilation and air conditioning (HVAC) systems may reduce the damage of equipment, improving the reliability and safety of smart buildings, generating social and economic benefits. Data models for fault detection and diagnosis are increasingly used for extracting knowledge in the supervisory tasks. This article proposes an autonomic cycle of data analysis tasks (ACODAT) for the supervision of the building’s HVAC systems. Data analysis tasks incorporate data mining models for extracting knowledge from the system monitoring, analyzing abnormal situations and automatically identifying and taking corrective actions. This article shows a case study of a real building’s HVAC system, for the supervision with our ACODAT, where the HVAC subsystems have been installed over the years, providing a good example of a heterogeneous facility. The proposed supervisory functionality of the HVAC system is capable of detecting deviations, such as faults or gradual increment of energy consumption in similar working conditions. The case study shows this capability of the supervisory autonomic cycle, usually a key objective for smart buildings.
  • 3.5K
  • 01 Jun 2021
Topic Review
Agent-Based Programming
Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In an agent-based programming language, agents are the building blocks, and programs are obtained by programming their behaviours (how an agent reasons), their goals (what an agent aims to achieve) and their interoperation (how agents collaborate to solve a task).
  • 3.4K
  • 08 Mar 2021
Topic Review
Navigation Systems for the Visually Impaired
The visually impaired suffer greatly while moving from one place to another. They face challenges in going outdoors and in protecting themselves from moving and stationary objects, and they also lack confidence due to restricted mobility. Due to the recent rapid rise in the number of visually impaired persons, the development of assistive devices has emerged as a significant research field.
  • 3.4K
  • 07 Nov 2022
Topic Review
Prediction of Customer Churn in Retail E-Commerce Business
Customer Relationship Management (CRM) is defined as a process in which the business manages its interactions with customers using data integration from various sources and data analysis.
  • 3.3K
  • 18 Jan 2022
Topic Review
AI Public Datasets for Railway Applications
The aim of this entry is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public availability and freedom of use. These data are of great value for open research and publications related to the application of AI in the railway sector.
  • 3.3K
  • 09 Oct 2021
Topic Review
Environmental Intelligence
We propose that coupled human and environmental information processing can be applied to concomitantly increase the scope and penetration of surveillance, leading to new opportunities to detect, track, quantify, predict and influence events and interactions across a wide range of operations. Academia and non-governmental organizations, state actors, and commercial interests are expected to utilize and benefit from environmental intelligence in differentiated manners.
  • 3.3K
  • 14 Jan 2022
Topic Review
Radar Object Detection
With the improvement of automotive radar resolution, radar target classification has become a hot research topic. Deep radar detection can be classified into point-cloud-based and pre-CFAR-based. Radar point cloud and pre-CFAR data are similar to the LiDAR point cloud and visual image, respectively. Accordingly, the architectures for LiDAR and vision tasks can be adapted for radar detection. 
  • 3.3K
  • 07 Jun 2022
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