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Topic Review
3D Biometrics
Biometrics have been used to identify humans since the 19th century. Over time, these biometrics became 3D. The main reason for this was the growing need for more features in the images to create more reliable identification models. Three main categories of 3D biometrics were identified. These were face, hand and gait. The corresponding percentages for these categories were 74.07%, 20.37% and 5.56%, respectively. The face is further categorized into facial, ear, iris and skull, while the hand is divided into fingerprint, finger vein and palm. In each category, facial and fingerprint were predominant, and their respective percentages were 80% and 54.55%. The use of the 3D reconstruction algorithms was also determined. These were stereo vision, structure-from-silhouette (SfS), structure-from-motion (SfM), structured light, time-of-flight (ToF), photometric stereo and tomography. Stereo vision and SfS were the most commonly used algorithms with a combined percentage of 51%. The state of the art for each category and the available datasets are also presented. Finally, multimodal biometrics, generalization of 3D reconstruction algorithms and anti-spoofing metrics are the three areas that should attract scientific interest for further research. 
  • 1.2K
  • 02 Sep 2022
Topic Review
AI&ML for Medical Sector
This work represents a comprehensive analysis of the potential AI, ML, and IoT technologies for defending against the COVID-19 pandemic. The existing and potential applications of AI, ML, and IoT, along with a detailed analysis of the enabling tools and techniques are outlined. A critical discussion on the risks and limitations of the aforementioned technologies are also included.
  • 1.2K
  • 21 Jan 2021
Topic Review
Bayesian Nonlinear Mixed Effects Models
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a nonlinear tendency. While frequentist analysis of nonlinear mixed effects models has a long history, Bayesian analysis of the models has received comparatively little attention until the late 1980s, primarily due to the time-consuming nature of Bayesian computation. Since the early 1990s, Bayesian approaches for the models began to emerge to leverage rapid developments in computing power, and have recently received significant attention due to (1) superiority to quantify the uncertainty of parameter estimation; (2) utility to incorporate prior knowledge into the models; and (3) flexibility to match exactly the increasing complexity of scientific research arising from diverse industrial and academic fields. 
  • 1.1K
  • 23 Mar 2022
Topic Review
Smart Parking Systems
The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.
  • 1.1K
  • 27 Oct 2020
Topic Review
AI-Assisted Design-on-Simulation for Life Prediction
Many researchers have adopted the finite-element-based design-on-simulation (DoS) technology for the reliability assessment of electronic packaging. DoS technology can effectively shorten the design cycle, reduce costs, and effectively optimize the packaging structure. However, the simulation analysis results are highly dependent on the individual researcher and are usually inconsistent between them. Artificial intelligence (AI) can help researchers avoid the shortcomings of the human factor. 
  • 1.1K
  • 28 Sep 2021
Topic Review
Associative Classification Method
Machine learning techniques are ever prevalent as datasets continue to grow daily. Associative classification (AC), which combines classification and association rule mining algorithms, plays an important role in understanding big datasets that generate a large number of rules. Clustering, on the other hand, can contribute by reducing the rule space to produce compact models. 
  • 1.1K
  • 20 Sep 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.
  • 1.1K
  • 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.
  • 1.1K
  • 28 Oct 2020
Topic Review
Radar Depth and Velocity Estimation
Radar can measure range and Doppler velocity, but both of them cannot be directly used for downstream tasks. The range measurements are sparse and therefore difficult to associate with their visual correspondences. The Doppler velocity is measured in the radial axis and, therefore, cannot be directly used for tracking.
  • 1.1K
  • 08 Jun 2022
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.
  • 1.1K
  • 01 Nov 2020
Topic Review
Machine Learning-Based Forecasting of Renewable Energy
With the increasing penetration of renewable energy sources (RES) into the electricity grid, accurate forecasting of their generation becomes crucial for efficient grid operation and energy management. Traditional forecasting methods have limitations, and thus machine learning (ML) and deep learning (DL) algorithms have gained popularity due to their ability to learn complex relationships from data and provide accurate predictions.
  • 1.1K
  • 27 Apr 2023
Topic Review
Artificial Intelligence in Edge-Based IoT Applications
Given its advantages in low latency, fast response, context-aware services, mobility, and privacy preservation, edge computing has emerged as the key support for intelligent applications and 5G/6G Internet of things (IoT) networks. This technology extends the cloud by providing intermediate services at the edge of the network and improving the quality of service for latency-sensitive applications. Many AI-based solutions with machine learning, deep learning, and swarm intelligence have exhibited the high potential to perform intelligent cognitive sensing, intelligent network management, big data analytics, and security enhancement for edge-based smart applications. 
  • 1.1K
  • 15 Feb 2023
Topic Review
Autonomous Vehicle
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 operations and 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. 
  • 1.1K
  • 17 Feb 2021
Biography
Yoshiyasu Takefuji
Graduated from Elec. Eng., Keio Univ. BS (1978), MS (1980), Ph.D. (1983). Asst Prof: Univ. of South Florida (1983-1985), Assoc Prof: Univ. of South Carolina (1985-1988), Assoc Prof: Case Western Reserve Univ. (1988-1996: tenured in 1992), tenured Prof: Keio Univ. (1992-2021), Emeritus Prof: Keio Univ. (2021-present), Prof: Musashino Univ. (2021-present), Docent Prof. Jyvaskyla Univ. He authors 4
  • 1.1K
  • 04 Apr 2023
Topic Review
Evolution of Intelligent Vehicle Technology
The time evolution of intelligent vehicle technology is explained, which highlights the development of an intelligentvehicle and its safety applications, focusing on the various usages of perception sensors in production.
  • 1.1K
  • 25 Nov 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. 
  • 1.1K
  • 17 Dec 2021
Topic Review
Opportunities and Challenges in Quantum Computing for Business
Quantum computing is emerging as a groundbreaking force, promising to redefine the boundaries of technology and business. 
  • 1.1K
  • 14 Nov 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.
  • 1.1K
  • 27 Oct 2020
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.
  • 1.1K
  • 01 Jun 2021
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.
  • 1.1K
  • 11 Feb 2021
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