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Topic Review
Encoding Techniques for Gait Analysis
Gait refers to the movement patterns of an individual’s walk. It encompasses the rhythm, speed, and style of movement which require a strong coordination of the upper and lower limbs. The dramatic increase in the use of numerous sensors, e.g., inertial measurement unit (IMU), in our daily wearable devices has gained the interest of the research community to collect kinematic and kinetic data to analyze the gait. The most crucial step for gait analysis is to find the set of appropriate features from continuous time series data to accurately represent human locomotion.
  • 591
  • 19 Jan 2024
Topic Review
Pedestrian Identification and Classification in Autonomous Vehicles
Pedestrian detection is at the core of autonomous road vehicle navigation systems as they allow a vehicle to understand where potential hazards lie in the surrounding area and enable it to act in such a way that avoids traffic-accidents, which may result in individuals being harmed. This paper demonstrates that the use of image augmentation on training data can yield varying results. 
  • 590
  • 10 Jan 2022
Topic Review
Public Transport COVID-19-Safe: New Barriers and Policies
The COVID-19 emergency forced cities worldwide to adopt measures to restrict travel and implement new urban public transport solutions. The discontinuity and reduction of services made users recognize public transport systems as contamination vectors, and the decrease in the number of passengers can already be seen in several places. Countermeasures that reduce the contact with other passengers—directly (limit the number of passengers in vehicles) or indirectly (operate with large vehicles)—and increase offers are possible solutions to make users feel safe while riding. 
  • 590
  • 28 Mar 2022
Topic Review
Surface Defect Detection of Strip-Steel
Surface-defect detection is crucial for assuring the quality of strip-steel manufacturing. Strip-steel surface-defect detection requires defect classification and precision localization, which is a challenge in real-world applications.
  • 589
  • 14 Sep 2022
Topic Review
Oximetry for Obstructive Sleep Apnea
Scoring polysomnography for obstructive sleep apnea diagnosis is a laborious, long, and costly process. Machine learning approaches, such as deep neural networks, can reduce scoring time and costs.
  • 589
  • 11 Oct 2023
Topic Review
Applications of Machine Learning in Fluid Mechanics
The significant growth of artificial intelligence (AI) methods in machine learning (ML) and deep learning (DL) has opened opportunities for fluid dynamics and its applications in science, engineering and medicine. Developing AI methods for fluid dynamics encompass different challenges than applications with massive data, such as the Internet of Things.
  • 586
  • 24 Aug 2023
Topic Review
KinectGaitNet
Gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports training. The main advantages of identifying a person by their gait include unobtrusiveness, acceptance, and low costs. Researchers proposes a convolutional neural network KinectGaitNet for Kinect-based gait recognition. The 3D coordinates of each of the body joints over the gait cycle are transformed to create a unique input representation. The proposed KinectGaitNet is trained directly using the 3D input representation without the necessity of the handcrafted features. The KinectGaitNet design allows avoiding gait cycle resampling, and the residual learning method ensures high accuracy without the degradation problem.
  • 585
  • 20 Apr 2022
Topic Review
NER&RE Techniques on Clinical Texts
Out of the various text mining tasks and techniques, our goal in this paper is to review the current state-of-the-art in Clinical Named Entity Recognition (NER) and Relationship Extraction (RE)-based techniques. Clinical NER is a natural language processing (NLP) method used for extracting important medical concepts and events i.e., clinical NEs from the data. Relationship Extraction (RE) is used for detecting and classifying the annotated semantic relationships between the recognized entities.
  • 584
  • 30 Sep 2021
Topic Review
Bayes Factor and Prior Elicitation
The Bayes factor is a ratio of the marginal likelihood of two competing models. The marginal likelihood for a model class is a weighted average of the likelihood over all the parameter values represented by the prior distribution. Therefore, carefully choosing priors and conducting a prior sensitivity analysis play an essential role when using Bayes factors as a model selection tool. This section briefly discusses the prior distributions, prior elicitation, and prior sensitivity analysis.
  • 584
  • 24 Feb 2022
Topic Review
Transporting Blood Using Unmanned Aerial Vehicles
Unmanned Aerial Vehicles (UAVs) play crucial roles in numerous applications, such as healthcare services. For example, UAVs can help in disaster relief and rescue missions, such as by delivering blood samples and medical supplies.
  • 582
  • 21 Nov 2022
Topic Review
Methods for Supervised Learning in Diagnosis of COVID-19
The methods for supervised learning in diagnosis of COVID-19 refer to the samples used for model training being labeled. The label information is fully utilized to guide network model training. The advantage is that the model accuracy can be effectively improved by learning a large amount of label information and the model is easy to evaluate. The current state of deep learning for COVID-19 classification and segmentation tasks from aspects of supervised learning is summarized, including summarizing the application of VGG, ResNet, DenseNet and lightweight networks to the classification task of COVID-19, and summarizing the application of the attention mechanism, multiscale mechanism, residual connectivity mechanism, and dense connectivity mechanism to the segmentation task of COVID-19.
  • 582
  • 22 Mar 2023
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.
  • 582
  • 02 Aug 2023
Topic Review
State-of-the-Art on Recommender Systems for E-Learning
Recommender systems (RSs) are increasingly recognized as intelligent software for predicting users’ opinions on specific items. Various RSs have been developed in different domains, such as e-commerce, e-government, e-resource services, e-business, e-library, e-tourism, and e-learning, to make excellent user recommendations. In e-learning technology, RSs are designed to support and improve the learning practices of a student or an organization.
  • 580
  • 06 Dec 2022
Topic Review
Automatic Detection of Cardiovascular Disorders
The main cause of death worldwide is cardiovascular disease (CVD), which claims more than 17 million lives each year. CVD disease creates other pathological issues with the heart, heart valves, or blood vessels.
  • 579
  • 03 Jan 2023
Topic Review
Artificial Intelligence Marketing for Customer-Relationships
Artificial intelligence marketing (AIM), which is an interdisciplinary research topic, is a disruptive technology that enables machines to automate the process of collecting and processing a massive amount of data and information to create knowledge related to marketing mix. This capability is essential to manifest personalization at scale, which has been impossible through human effort alone. This paper synthesizes the literature and develops an AIM framework to create a quantum leap in customer relationship enhancement, including customer trust, satisfaction, commitment, engagement, and loyalty.
  • 578
  • 29 Sep 2021
Topic Review
Novel Pooling Methods for Convolutional Neural Networks
Neural network computational methods have evolved over the past half-century. In 1943, McCulloch and Pitts designed the first model, recognized as the linear threshold gate. Hebbian developed the Hebbian learning rule approach for training the neural network. However, would the Hebbian rule remain productive when all the input patterns became orthogonal? The existence of orthogonality in input vectors is a crucial component for this rule to execute effectively. To meet this requirement, a much more productive learning rule, known as the Delta rule, was established. Whereas the delta rule poses issues with the learning principles outlined above, backpropagation has developed as a more complicated learning approach. Backpropagation could learn an infinite layered structure and estimate any commutative function. A feed-forward neural network is most often trained using backpropagation (FFNN).
  • 577
  • 08 Sep 2022
Topic Review
IoT for Smart Cities
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. 
  • 576
  • 15 Sep 2021
Topic Review
Deep Learning Models for Radiography in Chest Disease
Chest X-ray radiography (CXR) is among the most frequently used medical imaging modalities. It has a preeminent value in the detection of multiple life-threatening diseases. Radiologists can visually inspect CXR images for the presence of diseases. Most thoracic diseases have very similar patterns, which makes diagnosis prone to human error and leads to misdiagnosis. Machine learning (ML) and deep learning (DL) provided techniques to make this task more efficient and faster. Numerous experiments in the diagnosis of various diseases proved the potential of these techniques.
  • 573
  • 18 Jan 2023
Topic Review
Deep Learning in Optical Coherence Tomography Angiography
Optical coherence tomography angiography (OCT-A) provides depth-resolved visualization of the retinal microvasculature without intravenous dye injection. It facilitates investigations of various retinal vascular diseases and glaucoma by assessment of qualitative and quantitative microvascular changes in the different retinal layers and radial peripapillary layer non-invasively, individually, and efficiently. Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has been applied in OCT-A image analysis and achieved good performance for different tasks, such as image quality control, segmentation, and classification. DL technologies have further facilitated the potential implementation of OCT-A in eye clinics in an automated and efficient manner and enhanced its clinical values for detecting and evaluating various vascular retinopathies.
  • 573
  • 13 Feb 2023
Topic Review
Oriented Crossover in Genetic Algorithms
A genetic algorithm is a formula for resolving optimization issues that incorporate a constraint and natural selection similar to the biological process that propels evolution.
  • 573
  • 11 May 2023
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