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Topic Review
Machine Learning for Precision Agriculture with UAV
Unmanned aerial vehicles (UAVs) are increasingly being integrated into the domain of precision agriculture, revolutionizing the agricultural landscape. Specifically, UAVs are being used in conjunction with machine learning techniques to solve a variety of complex agricultural problems. 
  • 1.5K
  • 19 Jun 2023
Topic Review
Efficient Structural Design with ANNs
Artificial Neural Networks (ANNs) are showing their potential as structural design tools. ANNs are applied to design a dry precast concrete connection. They can be easily and effectively adapted to different connection parameters, being possible to use them in both precast or cast in situ concrete connection design.
  • 1.5K
  • 27 Oct 2020
Topic Review
Network Traffic Analysis
Network data traffic is increasing with expanded networks for various applications, with text, image, audio, and video for inevitable needs. Network traffic pattern identification and analysis of traffic of data content are essential for different needs and different scenarios. Many approaches have been followed, both before and after the introduction of machine and deep learning algorithms as intelligence computation. The network traffic analysis is the process of incarcerating traffic of a network and observing it deeply to predict what the manifestation in traffic of the network is. To enhance the quality of service (QoS) of a network, it is important to estimate the network traffic and analyze its accuracy and precision, as well as the false positive and negative rates, with suitable algorithms. 
  • 1.5K
  • 14 Jul 2022
Topic Review
Control-Based 4D Printing
Building on the recent progress of four-dimensional (4D) printing to produce dynamic structures, this study aimed to bring this technology to the next level by introducing control-based 4D printing to develop adaptive 4D-printed systems with highly versatile multi-disciplinary applications, including medicine, in the form of assisted soft robots, smart textiles as wearable electronics and other industries such as agriculture and microfluidics. This study introduced and analyzed adaptive 4D-printed systems with an advanced manufacturing approach for developing stimuli-responsive constructs that organically adapted to environmental dynamic situations and uncertainties as nature does. The adaptive 4D-printed systems incorporated synergic integration of three-dimensional (3D)-printed sensors into 4D-printing and control units, which could be assembled and programmed to transform their shapes based on the assigned tasks and environmental stimuli. This paper demonstrates the adaptivity of these systems via a combination of proprioceptive sensory feedback, modeling and controllers, as well as the challenges and future opportunities they present.
  • 1.5K
  • 28 Oct 2020
Topic Review
The Application of Digital Twins in Healthcare
Digital twins (DTs) play a crucial role in the ongoing Industry 4.0 revolution, leveraging advanced data analytics and the connectivity of Internet of Things (IoT) to drive transformative changes across industries. The metaverse presents the potential for transformative changes in healthcare by offering virtual health services, supporting mental health, managing reality, and enabling virtual management. These innovations have the capacity to enhance accessibility, convenience, and the overall patient experience, bringing healthcare closer to individuals and ensuring that they receive the necessary care, regardless of physical distance or limitations.
  • 1.5K
  • 02 Aug 2023
Topic Review
The Convergence of AI, 6G, and Wireless Communication
In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. By integrating AI and ML, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems.
  • 1.5K
  • 27 Mar 2024
Topic Review Peer Reviewed
Optimisation of Small-Scale Aquaponics Systems Using Artificial Intelligence and the IoT: Current Status, Challenges, and Opportunities
Environment changes, water scarcity, soil depletion, and urbanisation are making it harder to produce food using traditional methods in various regions and countries. Aquaponics is emerging as a sustainable food production system that produces fish and plants in a closed-loop system. Aquaponics is not dependent on soil or external environmental factors. It uses fish waste to fertilise plants and can save up to 90–95% water. Aquaponics is an innovative system for growing food and is expected to be very promising, but it has its challenges. It is a complex ecosystem that requires multidisciplinary knowledge, proper monitoring of all crucial parameters, and high maintenance and initial investment costs to build the system. Artificial intelligence (AI) and the Internet of Things (IoT) are key technologies that can overcome these challenges. Numerous recent studies focus on the use of AI and the IoT to automate the process, improve efficiency and reliability, provide better management, and reduce operating costs. However, these studies often focus on limited aspects of the system, each considering different domains and parameters of the aquaponics system. This paper aims to consolidate the existing work, identify the state-of-the-art use of the IoT and AI, explore the key parameters affecting growth, analyse the sensing and communication technologies employed, highlight the research gaps in this field, and suggest future research directions. Based on the reviewed research, energy efficiency and economic viability were found to be a major bottleneck of current systems. Moreover, inconsistencies in sensor selection, lack of publicly available data, and the reproducibility of existing work were common issues among the studies.
  • 1.5K
  • 19 Feb 2024
Topic Review
Walking Recognition in Mobile Devices
Presently, smartphones are used more and more for purposes that have nothing to do with phone calls or simple data transfers. One example is the recognition of human activity, which is relevant information for many applications in the domains of medical diagnosis, elderly assistance, indoor localization, and navigation. The information captured by the inertial sensors of the phone (accelerometer, gyroscope, and magnetometer) can be analyzed to determine the activity performed by the person who is carrying the device, in particular in the activity of walking. Nevertheless, the development of a standalone application able to detect the walking activity starting only from the data provided by these inertial sensors is a complex task. This complexity lies in the hardware disparity, noise on data, and mostly the many movements that the smartphone can experience and which have nothing to do with the physical displacement of the owner. In this work, we explore and compare several approaches for identifying the walking activity. We categorize them into two main groups: the first one uses features extracted from the inertial data, whereas the second one analyzes the characteristic shape of the time series made up of the sensors readings. Due to the lack of public datasets of inertial data from smartphones for the recognition of human activity under no constraints, we collected data from 77 different people who were not connected to this research. Using this dataset, which we published online, we performed an extensive experimental validation and comparison of our proposals.
  • 1.5K
  • 01 Nov 2020
Topic Review
Artificial Intelligence in CORONA Virus
AI is the most demanding field of the world. It is playing a vital role in many aspects like prediction of any pandemic or making any vaccine faster.
  • 1.5K
  • 11 Feb 2021
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.
  • 1.5K
  • 09 Oct 2021
Topic Review
Applications of Brain–Computer Interfaces to Control and Automation
Brain–computer interfacing (BCI) is a real-time communication system that connects the brain and external devices. A BCI system can directly convert the information sent by the brain into commands that can drive external devices and can replace human limbs or phonation organs to achieve communication with the outside world and to control the external environment. In other words, a BCI system can replace the normal peripheral nerve and muscle tissue to achieve communication between a human and a computer or between a human and the external environment. BCIs have been validated in various noisy structured environments such as homes, hospitals, and expositions, resulting in the direct application of BCIs gaining popularity with regular consumers.
  • 1.5K
  • 12 Jun 2023
Topic Review
Mars Rover Mastcam Images
The Curiosity rover has landed on Mars since 2012. One of the instruments onboard the rover is a pair of multispectral cameras known as Mastcams, which act as eyes of the rover.
  • 1.5K
  • 28 Oct 2021
Topic Review
Lamport Timestamps
The algorithm of Lamport timestamps is a simple algorithm used to determine the order of events in a distributed computer system. As different nodes or processes will typically not be perfectly synchronized, this algorithm is used to provide a partial ordering of events with minimal overhead, and conceptually provide a starting point for the more advanced vector clock method. They are named after their creator, Leslie Lamport. Distributed algorithms such as resource synchronization often depend on some method of ordering events to function. For example, consider a system with two processes and a disk. The processes send messages to each other, and also send messages to the disk requesting access. The disk grants access in the order the messages were sent. For example process [math]\displaystyle{ A }[/math] sends a message to the disk requesting write access, and then sends a read instruction message to process [math]\displaystyle{ B }[/math]. Process [math]\displaystyle{ B }[/math] receives the message, and as a result sends its own read request message to the disk. If there is a timing delay causing the disk to receive both messages at the same time, it can determine which message happened-before the other: [math]\displaystyle{ A }[/math] happens-before [math]\displaystyle{ B }[/math] if one can get from [math]\displaystyle{ A }[/math] to [math]\displaystyle{ B }[/math] by a sequence of moves of two types: moving forward while remaining in the same process, and following a message from its sending to its reception. A logical clock algorithm provides a mechanism to determine facts about the order of such events. Lamport invented a simple mechanism by which the happened-before ordering can be captured numerically. A Lamport logical clock is a numerical software counter value maintained in each process. Conceptually, this logical clock can be thought of as a clock that only has meaning in relation to messages moving between processes. When a process receives a message, it re-synchronizes its logical clock with that sender. The above-mentioned vector clock is a generalization of the idea into the context of an arbitrary number of parallel, independent processes.
  • 1.5K
  • 24 Oct 2022
Topic Review
An Optimal House Price Prediction Algorithm: XGBoost
An accurate prediction of house prices is a fundamental requirement for various sectors, including real estate and mortgage lending. It is widely recognized that a property’s value is not solely determined by its physical attributes but is significantly influenced by its surrounding neighborhood. Meeting the diverse housing needs of individuals while balancing budget constraints is a primary concern for real estate developers. 
  • 1.5K
  • 18 Jan 2024
Topic Review
Hashtag Recommendation
Hashtag recommendation suggests hashtags to users while they write microblogs in social media platforms. Although researchers have investigated various methods and factors that affect the performance of hashtag recommendations in Twitter and Sina Weibo, a systematic review of these methods is lacking.
  • 1.5K
  • 25 May 2021
Topic Review
Music Generation of Traditional Chinese Pentatonic Scale
Recent studies demonstrate that algorithmic music attracted global attention not only because of its amusement but also its considerable potential in the industry. Thus, the yield increased academic numbers spinning around on topics of algorithm music generation. The balance between mathematical logic and aesthetic value is important in music generation.
  • 1.5K
  • 19 Oct 2022
Topic Review
Transformers for Computer Vision
Vision transformers (ViTs) are designed for tasks related to vision, including image recognition. Originally, transformers were used to process natural language (NLP). As a special type of transformer, vision transformers (ViTs) can be used for various computer vision (CV) applications.
  • 1.5K
  • 09 May 2023
Topic Review
Machine Failure Prediction Using Survival Analysis
With the rapid growth of cloud computing and the creation of large-scale systems such as IoT environments, the failure of machines/devices and, by extension, the systems that rely on them is a major risk to their performance, usability, and the security systems that support them. The need to predict such anomalies in combination with the creation of fault-tolerant systems to manage them is a key factor for the development of safer and more stable systems. 
  • 1.5K
  • 19 Oct 2023
Topic Review
Transformer-Based Model for Predicting Customers’ NPD in e-Commerce
Transformers offer advantages in capturing long-term dependencies within time series data through self-attention mechanisms. This adaptability to various time series patterns, including trends, seasonality, and irregularities, makes them a promising choice for next purchase day (NPD) prediction. The transformer model demonstrates improvements in prediction accuracy compared to the baselines. 
  • 1.5K
  • 02 Nov 2023
Topic Review
Use of Deep Learning for Video Classification
Deep learning models, specifically convolutional neural networks (CNNs), are well known for understanding images. An artificial neural network (ANN) is an algorithm based on interconnected nodes to recognize the relationships in a set of data. Algorithms based on ANNs have shown a great success in modeling both the lineßar and the non-linear relationships in the underlying data. Due to the huge success rate of these algorithms, they are extensively being used for different real-time applications.
  • 1.5K
  • 15 May 2023
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