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Topic Review
Design of Experiments in the Advancement of Biomaterial
Optimisation of tissue engineering (TE) processes requires models that can identify relationships between the parameters to be optimised and predict structural and performance outcomes from both physical and chemical processes. Design of Experiments (DoE) methods are commonly used for optimisation purposes in addition to playing an important role in statistical quality control and systematic randomisation for experiment planning. DoE is only used for the analysis and optimisation of quantitative data (i.e., number-based, countable or measurable), while it lacks the suitability for imaging and high dimensional data analysis.
  • 1.3K
  • 18 Jan 2023
Topic Review
Takagi–Sugeno Fuzzy-PI Controller Hardware
The intelligent system Field Programmable Gate Array (FPGA) is represented as Takagi--Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and floating-point). Two hardware designs are proposed; the first one uses a single clock cycle processing architecture, and the other uses a pipeline scheme. The bit accuracy was tested by simulation with a nonlinear control system of a robotic manipulator. The area, throughput, and dynamic power consumption of the implemented hardware are used to validate and compare the results of this proposal. The results achieved allow the use of the proposed hardware in applications with high-throughput, low-power, and ultra-low-latency requirements such as teleoperation of robot manipulators, tactile internet, or industry 4.0 automation, among others.
  • 1.3K
  • 29 Oct 2020
Topic Review
Semantic Trajectory and Recommender Systems in Cultural Spaces
Semantic trajectories can efficiently model human movement for further analysis and pattern recognition, while personalised recommender systems can adapt to constantly changing user needs and provide meaningful and optimised suggestions. 
  • 1.3K
  • 22 Dec 2021
Topic Review
AI Revolution in Digital Finance in Saudi Arabia
In recent years, Artificial Intelligence (AI) has become widespread, driven by abundant daily data production and increased computing power. It finds applications across various sectors, including transportation, education, healthcare, banking, and finance. The financial industry, in particular, is rapidly adopting AI to achieve significant cost savings. AI has the potential to revolutionize financial services by offering tailored, faster, and more cost-effective solutions. Saudi Arabia is emerging as a growing market in this field, emphasizing technology-driven institutions. Despite gaining prominence and government support, AI has yet to play a crucial role in improving the efficiency of financial transactions.
  • 1.3K
  • 27 Nov 2023
Topic Review
Radar-Based Non-Contact Continuous Identity Authentication
Non-contact vital signs monitoring using microwave Doppler radar has shown great promise in healthcare applications. Recently, this unobtrusive form of physiological sensing has also been gaining attention for its potential for continuous identity authentication, which can reduce the vulnerability of traditional one-pass validation authentication systems. Physiological Doppler radar is an attractive approach for continuous identity authentication as it requires neither contact nor line-of-sight and does not give rise to privacy concerns associated with video imaging.
  • 1.3K
  • 01 Jun 2021
Topic Review
Palmprint Recognition
Palmprint recognition constitutes a pivotal biometric technology deployed in the identification and verification of individuals, relying on the distinctive patterns inherent in their palmprints. This method, known for its reliability and security, finds extensive applications in diverse fields, including access control, security systems, and forensic investigations. Palmprint image acquisition involves capturing high-quality palmprint images using various devices like cameras, scanners, or smartphones. These images are then subjected to preprocessing techniques, encompassing noise reduction, normalization, and enhancement, to ensure consistent submission despite any restrictions on the availability of materials and/or refined input data. Following preprocessing, relevant features are extracted, like minutiae points specific to an individual’s palm, ridges, and lines. These features are crucial for accurate identification and are obtained through advanced image processing methods.
  • 1.3K
  • 10 Jan 2024
Topic Review
Resource Allocation Schemes for 5G Network
Resource allocation is an important aspect of any cellular network environment. It plays a significant part in maintaining friendly access for end-users, business partners, and customers of cellular-based applications. Resource allocation has great benefits for the cellular network environment.
  • 1.3K
  • 21 Oct 2021
Topic Review Video Peer Reviewed
Geometry-Based Deep Learning in the Natural Sciences
Nature is composed of elements at various spatial scales, ranging from the atomic to the astronomical level. In general, human sensory experience is limited to the mid-range of these spatial scales, in that the scales which represent the world of the very small or very large are generally apart from our sensory experiences. Furthermore, the complexities of Nature and its underlying elements are not tractable nor easily recognized by the traditional forms of human reasoning. Instead, the natural and mathematical sciences have emerged to model the complexities of Nature, leading to knowledge of the physical world. This level of predictiveness far exceeds any mere visual representations as naively formed in the Mind. In particular, geometry has served an outsized role in the mathematical representations of Nature, such as in the explanation of the movement of planets across the night sky. Geometry not only provides a framework for knowledge of the myriad of natural processes, but also as a mechanism for the theoretical understanding of those natural processes not yet observed, leading to visualization, abstraction, and models with insight and explanatory power. Without these tools, human experience would be limited to sensory feedback, which reflects a very small fraction of the properties of objects that exist in the natural world. As a consequence, as taught during the times of antiquity, geometry is essential for forming knowledge and differentiating opinion from true belief. It not only provides a framework for understanding astronomy, classical mechanics, and relativistic physics, but also the morphological evolution of living organisms, along with the complexities of the cognitive systems. Geometry also has a role in the information sciences, where it has explanatory power in visualizing the flow, structure, and organization of information in a system. This role further impacts the explanations of the internals of deep learning systems as developed in the fields of computer science and engineering.
  • 1.3K
  • 21 Jun 2023
Topic Review
Sarcasm and Irony Detection in Social Media
Sarcasm and irony represent intricate linguistic forms in social media communication, demanding nuanced comprehension of context and tone. 
  • 1.3K
  • 30 Nov 2023
Topic Review
Tiny-YOLO-Based CNN Architecture for Applications in Human Detection
Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. Human detection technologies have advanced significantly due to the rapid development of deep learning techniques. Convolutional neural networks (CNNs) have become quite popular for tackling various problems, among which includes object detection.
  • 1.3K
  • 14 Oct 2022
Topic Review
Applications of Internet of Things
IoT-dependent systems (IoTSs) cause heavy usage of energy. This is one of the biggest issues associated with IoTSs. Another issue is that the security of digital content is a big challenge and difficulty. Image processing has recently played an essential role in resolving these difficulties.
  • 1.3K
  • 02 Mar 2023
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.
  • 1.3K
  • 28 Oct 2020
Topic Review
Artificial Intelligence in Translational Medicine
Between preclinical and clinical research, translational research is benefitting from computer-based approaches like Artificial Intelligence, resulting in breakthroughs for advancing human health. 
  • 1.3K
  • 17 Dec 2021
Topic Review
Impact of Artificial Intelligence on the Job Market
This research explores the impact of artificial intelligence (AI) on the job market, including both its potential benefits and drawbacks. The research discusses how AI can automate repetitive tasks, improve accuracy, and assist workers in performing their jobs more effectively. However, the article also highlights concerns about job displacement, biases and discrimination, and the deskilling of workers. The research examines the impact of AI on different industries and types of jobs and discusses the need for workers to develop complementary skills and for employers to invest in AI technologies that work collaboratively with human workers. The research concludes by highlighting the importance of investing in education and training programs, ensuring ethical and transparent development and deployment of AI, and implementing appropriate policies to support workers who are displaced by AI.
  • 1.3K
  • 22 May 2023
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.
  • 1.3K
  • 01 Nov 2020
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.
  • 1.3K
  • 27 Oct 2020
Topic Review
Simulators in Educational Robotics
Simulators are part of educational robotics, which easily and quickly enable the user to engage virtually with the development and programming of robots through GUIs. Using a simulator means that it is not necessary to deal exclusively with real robots that might have a significant cost. Hence, simulators are a useful tool that might save resources and assist the educational process.
  • 1.3K
  • 18 Mar 2021
Topic Review
Intelligent Power Management System
This is a cloud-based intelligent power management system that uses analytics as a control signal and processes balance achievement pointer, and describes operator acknowledgments that must be shared quickly, accurately, and safely. Current studies of it aims to introduce a conceptual and systematic structure with three main components: demand power (direct current (DC)-device), power mix between renewable energy (RE) and other power sources, and a cloud-based power optimization intelligent system.
  • 1.3K
  • 01 Nov 2021
Topic Review
Risk Analysis of Engineering Procurement and Construction
The lump sum turn key (LSTK) contract for engineering, procurement, and construction (EPC) projects is a typical contract type used in large-scale and complex plant projects. 
  • 1.3K
  • 21 Jun 2022
Topic Review
Machine Learning Algorithms in Manufacturing
The quality-control process in manufacturing must ensure the product is free of defects and performs according to the customer’s expectations. Maintaining the quality of a firm’s products at the highest level is very important for keeping an edge over the competition. To maintain and enhance the quality of their products, manufacturers invest a lot of resources in quality control and quality assurance. During the assembly line, parts will arrive at a constant interval for assembly. The quality criteria must first be met before the parts are sent to the assembly line where the parts and subparts are assembled to get the final product. Once the product has been assembled, it is again inspected and tested before it is delivered to the customer. Because manufacturers are mostly focused on visual quality inspection, there can be bottlenecks before and after assembly. The manufacturer may suffer a loss if the assembly line is slowed down by this bottleneck. To improve quality, state-of-the-art sensors are being used to replace visual inspections and machine learning is used to help determine which part will fail.
  • 1.3K
  • 19 Oct 2022
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