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Topic Review
IoT
This entry presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.
  • 855
  • 25 May 2021
Topic Review
Advancements and Challenges in Handwritten Text Recognition
Handwritten Text Recognition (HTR) involves automatically transforming a source’s handwritten text within a digital image into its machine text representation.
  • 855
  • 07 Mar 2024
Topic Review
Deep Reinforcement Learning Approaches for Smart Manufacturing
AI and, in particular, the Deep Reinforcement Learning (DRL) algorithms, which are a perfect response to the unpredictability and volatility of modern demand, are studied in detail. Through the introduction of RL concepts and the development of those with ANNs towards DRL, the potential and variety of these kinds of algorithms are highlighted. Moreover, because these algorithms are data based, their modification to meet the requirements of industry operations is also included. Digital twins are a technology that is increasingly important in I.40 and I.5.0, which seems to be crucial to the development of smart manufacturing. 
  • 853
  • 13 Jan 2023
Topic Review
Extended Reality Technology for Teaching New Languages
Much attention has been given to the use of extended reality (XR) technology in educationalinstitutions due to its flexibility, effectiveness, and attractiveness. However, there is a limited study of the application of XR technology for teaching and learning languages in schools. Thus, this paper presents a systematic review to identify the potential benefits and challenges of using XR technology for teaching new languages. This review provides a basis for adopting XR technology for teaching languages in schools. This research also provides recommendations to successfully implement the XR technology and ways to improve motivation, engagement, and enhanced accessibility of learning and teaching resources for both students and teachers. To fulfil the aims of this research, previous studies from 2011 to 2021 are collected from various academic databases. This study finds that there is still aneed to develop appropriate strategies for the development and implementation of XR technology for teaching new languages to school students.
  • 850
  • 16 Dec 2021
Topic Review
Big Data Analytics Applications and Opportunities
Big data applications and analytics are vital in proposing ultimate strategic decisions. The existing literature emphasizes that big data applications and analytics can empower those who apply Big Data Analytics during the COVID-19 pandemic.
  • 850
  • 27 Dec 2022
Topic Review
Convolutional Neural Network in the Medical Imaging
Convolutional Neural Networks (CNN), commonly known as ConvNet, is one of the common types of Artificial Neural Network (ANN) that comes under the supervised method category. This method is known for its ability to discover and interpret patterns. This pattern detection brings up the usefulness of CNN for image analysis. 
  • 848
  • 10 Apr 2023
Topic Review
Knee Injury Detection Using Deep Learning
Knee injuries account for the largest percentage of sport-related, severe injuries (i.e., injuries that cause more than 21 days of missed sport participation). The improved treatment of knee injuries critically relies on having an accurate and cost-effective detection. Deep-learning-based approaches have monopolized knee injury detection in MRI studies.
  • 846
  • 20 May 2022
Topic Review
Robotic-Systems for Improving Upper-Limb Spasticity
Spasticity is a motor disorder that causes stiffness or tightness of the muscles and can interfere with normal movement, speech, and gait. Traditionally, the spasticity assessment is carried out by clinicians using standardized procedures for objective evaluation. However, these procedures are manually performed and, thereby, they could be influenced by the clinician’s subjectivity or expertise. The automation of such traditional methods for spasticity evaluation is an interesting and emerging field in neurorehabilitation. One of the most promising approaches is the use of robot-aided systems.
  • 845
  • 26 Oct 2020
Topic Review
Universal Intelligence for Sustainability
Artificial intelligence (AI), as a product of biological intelligence, is a technological tool based on data and the information-processing power of discrete machines that carry out a series of interdependent operations to generate and store discrete data and information, using discrete, finite, and closed algorithms. In turn, the concept of sustainability is increasingly considered an almost essential component of discourses designed to support and justify decision-making at all levels of human activities.  The strong and functional couplings among ecological, economic, social, and technological processes explain the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, and the power of information, and the COVID-19 syndemic. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy, and information, and a given time horizon. Given the high stakes; the need for effective, efficient, diverse solutions; their local and global, and present and future effects; and their unforeseen short-, medium-, and long-term impacts; achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents (SUIAs). The proposed philosophical and technological SUIAs will be heuristic devices for harnessing the strong functional coupling between human, artificial, and nonhuman biological intelligence in a non-zero-sum game to achieve sustainability.
  • 845
  • 21 Jun 2022
Topic Review
Biologically inspired metaheuristics
A metaheuristic is a high level, problem-independent framework that provides a series of steps and guidelines used to develop heuristic optimizers. Nowadays, the tendency is to use the term for both the general framework and for the algorithms built based on its rules. In the latest years, the literature has shown an increase in the number of proposals of new optimization metaheuristics and their improvements through step alterations, local search procedures or hybridizations.
  • 842
  • 09 Oct 2021
Topic Review
AUV Adaptive Sampling Methods
Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced.
  • 841
  • 12 Nov 2020
Topic Review
Intelligent Energy Management Systems for Electric Vehicle Transportation
Electric Vehicles (EVs) have been gaining interest as a result of their ability to reduce vehicle emissions. Developing an intelligent system to manage EVs charging demands is one of the fundamental aspects of this technology to better adapt for all-purpose transportation utilization. It is necessary for EVs to be connected to the Smart Grid (SG) to communicate with charging stations and other energy resources in order to control charging schedules, while Artificial Intelligent (AI) techniques can be beneficial for improving the system, they can also raise security and privacy threats. Privacy preservation methodologies have been introduced to ensure data security. Federated Learning (FL) and blockchain technology are two emerging strategies to address information protection concerns. 
  • 835
  • 22 Nov 2022
Topic Review
Unsupervised Domain Adaptation for Image Classification
Unsupervised domain adaptation (UDA) is a transfer learning technique utilized in deep learning. UDA aims to reduce the distribution gap between labeled source and unlabeled target domains by adapting a model through fine-tuning. To reduce the domain divergence between the source and target domain, there are mainly two main types of UDA methods that have gained significant attention: discrepancy-based UDA methods and adversarial-based UDA methods.
  • 835
  • 31 May 2023
Topic Review
Relationship of Artificial Intelligence, Advertising, and Generative Models
Although artificial intelligence technologies have provided valuable insights into the advertising industry, more comprehensive studies that properly examine the applications of AI in advertising using scientometric network analysis are needed.
  • 834
  • 11 Mar 2024
Topic Review
Computer Vision and Artificial Intelligence for Fish Recognition
Computer vision has been applied to fish recognition. With the inception of deep learning techniques in the early 2010s, the use of digital images grew strongly, and this trend is likely to continue. As the number of articles published grows, it becomes harder to keep track of the state of the art and to determine the best course of action for new studies.
  • 833
  • 24 Nov 2022
Topic Review
Learning for Unmanned Ground Vehicles
The problem of autonomous navigation of a ground vehicle in unstructured environments is both challenging and crucial for the deployment of this type of vehicle in real-world applications. We present a review on the recent contributions in the roboticsliterature adopting learning-based methods to solve the problem of environment perception andinterpretation with the final aim of the autonomous context-aware navigation of ground vehicles inunstructured environments.
  • 832
  • 29 Apr 2021
Topic Review
Quantum Generative Adversarial Networks
Quantum mechanics studies nature and its behavior at the scale of atoms and subatomic particles. By applying quantum mechanics, a lot of problems can be solved in a more convenient way thanks to its special quantum properties, such as superposition and entanglement. In the current noisy intermediate-scale quantum era, quantum mechanics finds its use in various fields of life. Following this trend, researchers seek to augment machine learning in a quantum way. The generative adversarial network (GAN), an important machine learning invention that excellently solves generative tasks, has also been extended with quantum versions. Since the first publication of a quantum GAN (QuGAN) in 2018, many QuGAN proposals have been suggested. A QuGAN may have a fully quantum or a hybrid quantum–classical architecture, which may need additional data processing in the quantum–classical interface. Similarly to classical GANs, QuGANs are trained using a loss function in the form of max likelihood, Wasserstein distance, or total variation. The gradients of the loss function can be calculated by applying the parameter-shift method or a linear combination of unitaries in order to update the parameters of the networks. 
  • 830
  • 15 Mar 2023
Topic Review
Augmented Reality in Professional Training
Professional training is defined as a set of behaviors and acts with the purpose of increasing the employees’ professional skills to carry out a particular job in a better manner. Such a definition highlights three important features of professional training. First, its purpose is educational, which focuses on employee development (e.g., skill acquisition and knowledge growth) rather than performance improvement. Augmented reality (AR) is defined as a technology-enhanced environment where virtual objects (augmented components) can be overlaid into the real world. Azuma (1997) identified three technical features of AR: a combination of the real and virtual world, real-time interaction, and accurate 3D registration of virtual and real objects.
  • 827
  • 27 Jan 2022
Topic Review
Computer Vision in Self-Steering Tractors
Agricultural machinery, such as tractors, is meant to operate for many hours in large areas and perform repetitive tasks. The automatic navigation of agricultural vehicles can ensure the high intensity of automation of cultivation tasks, the enhanced precision of navigation between crop structures, an increase in operation safety and a decrease in human labor and operation costs.
  • 826
  • 24 Feb 2022
Topic Review
Intelligent Fault Diagnosis
For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch.
  • 825
  • 14 Jan 2021
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