Intensive sleep re-training is a promising new therapy for chronic insomnia. Therapy is completed over a 24-h period during a state of sleep deprivation. Improvements of sleep and daytime impairments are comparable to the use of stimulus control ther...
Endoscopic high-speed video (HSV) systems for visualization and assessment of vocal fold dynamics in the larynx are diverse and technically advancing. To consider resulting “concepts shifts” for neural network (NN)-based image processing,...
This paper presents a novel framework to enable automatic re-training of the supervisory powertrain control strategy for hybrid electric vehicles using supervised machine learning. The aim of re-training is to customize the control strategy to a user...
Accurate segmentation of interstitial lung disease (ILD) patterns from computed tomography (CT) images is an essential prerequisite to treatment and follow-up. However, it is highly time-consuming for radiologists to pixel-by-pixel segment ILD patter...
As a crucial task in surveillance and security, person re-identification (re-ID) aims to identify the targeted pedestrians across multiple images captured by non-overlapping cameras. However, existing person re-ID solutions have two main challenges:...
Vehicle Re-Identification (Re-ID) based on Unsupervised Domain Adaptation (UDA) has shown promising performance. However, two main issues still exist: (1) existing methods that use Generative Adversarial Networks (GANs) for domain gap alleviation com...
Arousing and emotional situations can improve cognitive performance and the memorability of events. Recently, the enhancement of training performance in Labrador Retriever dogs through 30 min of dog–human play immediately after acquiring a nove...
Despite its positive influence on physical and mental wellbeing, running is associated with a high incidence of musculoskeletal injury. Potential modifiable risk factors for running-related injury have been identified, including running biomechanics....
This paper presents a comprehensive model for detecting and addressing concept drift in network security data using the Isolation Forest algorithm. The approach leverages Isolation Forest’s inherent ability to efficiently isolate anomalies in h...
28 January 2020
Purpose: The intervention of 12 week gait retraining with minimalist shoes was established to examine its effect on impact forces, joint mechanics, and vertical stiffness during running. Methods: Thirty male recreational runners were randomly assigne...
Robotic gait retraining systems typically function by employing mechanisms that move a patient’s lower limbs in a controlled manner. In this paper, an end-effector gait retraining system was designed, utilizing a 2-PRR mechanism (PRR refers to...
Traffic emissions serve as one of the most significant sources of atmospheric PM2.5 pollution in developing countries, driven by the prevalence of aging vehicle fleets and the inadequacy of regulatory frameworks to mitigate emissions effectively. Thi...
The present study compared the effect between walking exercise and a newly developed sensor-based gait retraining on the peaks of knee adduction moment (KAM), knee adduction angular impulse (KAAI), knee flexion moment (KFM) and symptoms and functions...
A new methodology is proposed for designing professional retraining programs for aviation, rocket, and space industry employees, focused on the formation of the necessary competencies. The novelty of the proposed method is in the formalization of the...
Personalized healthcare recommender systems are increasingly being deployed in edge AI environments through wearable devices. In such environments, cloud servers leverage high-performance GPUs to train base models, which are then optimized for data r...
This article addresses the design of a robust inner and outer loop controller for active gait retraining in individuals with leg motor weakness, using a lower limb exoskeleton with elastic joints. The proposed control algorithm for the inner loop is...
While many anterior cruciate ligament (ACL) prevention programs have been published, few have achieved significant reductions in injury rates and improvements in athletic performance indices; both of which may increase compliance and motivation of at...
In recent years, graph neural networks (GNNs) have played an important role in graph representation learning and have successfully achieved excellent results in semi-supervised classification. However, these GNNs often neglect the global smoothing of...
Athletes with femoroacetabular impingement syndrome (FAIS) managed arthroscopically do not always return to sport. Inability to control back/pelvis, hip and lower limb movements may contribute to the onset and recurrence of symptoms. Our hypothesis i...
Objectives: This study examined the effects of re-warm-up versus no re-warm-up before squats or bench presses on mechanical, physiological, and psychophysiological responses in recreationally trained men. Methods: Twenty-two participants (22.8 &plusm...
The unsupervised domain-adaptive vehicle re-identification approach aims to transfer knowledge from a labeled source domain to an unlabeled target domain; however, there are knowledge differences between the target domain and the source domain. To mi...
Background/Objectives: Gait retraining is widely used in orthopedic rehabilitation to address abnormal movement patterns. However, retaining walking modifications can be challenging without guidance from physical therapists. Real-time auditory biofee...
This study presents CORE-ReID V2, an enhanced framework built upon CORE-ReID V1. The new framework extends its predecessor by addressing unsupervised domain adaptation (UDA) challenges in person ReID and vehicle ReID, with further applicability to ob...
Convolutional Neural Networks are usually fitted with manually labelled data. The labelling process is very time-consuming since large datasets are required. The use of external hardware may help in some cases, but it also introduces noise to the lab...
Extreme winter temperatures during the 2018–2019 dormant season contributed to trunk collapse and complete trunk death of numerous genotypes throughout a diverse grapevine planting in eastern North Dakota, USA. Through the early portion of the...
8 December 2021
Background: As the effectiveness on stress urinary incontinence (SUI) prevention of pelvic floor muscle training (PFMT) for pregnant women has been inconclusive, we are planning to conduct a trial to evaluate a video program designed for prevention o...
Background/Objectives: Tinnitus affects approximately 15% of the population and lacks a universally effective treatment. Tinnitus Retraining Therapy (TRT) is widely used but requires 6–8 h of daily sound exposure for 1–2 years, limiting a...
Background/Objectives: Attention bias (AB) toward food is associated with obesity, but it is unclear if programs designed to reduce AB can impact adolescents’ eating behavior. We investigated whether a two-week, smartphone-delivered attention r...
Background: Resuming a physical exercise program after a period of cessation is common in older women. Monitoring the responses during this detraining (DT) and retraining (RT) may allow us to analyze how the body reacts to an increase and a reduction...
The lack of highly effective treatments for fibromyalgia (FM) represents a great challenge for public health. The objective of this parallel, pilot randomized controlled trial (RCT) was two-fold: (1) to analyze the clinical effects of mindfulness plu...
Purpose: Although the Achilles tendon (AT) is the largest and strongest tendon, it remains one of the most vulnerable tendons among elite and recreational runners. The present study aims to explore the effects of 12-week gait retraining (GR) on the p...
Among various activation functions, the Rectified Linear Unit (ReLU) has become the most widely adopted due to its computational simplicity and effectiveness in mitigating the vanishing-gradient problem. In this work, we investigate the advantages of...
The increasing use of artificial intelligence (AI) and deep learning (DL) techniques has driven advances in vehicle classification and detection applications for embedded devices with deployment constraints due to computational cost and response time...
Using Spatial Domain Correlation Pattern Recognition (CPR) in Internet-of-Things (IoT)-based applications often faces constraints, like inadequate computational resources and limited memory. To reduce the computation workload of inference due to larg...
22 July 2024
Background: Intracranial neoplasm, often referred to as a brain tumor, is an abnormal growth or mass of tissues in the brain. The complexity of the brain and the associated diagnostic delays cause significant stress for patients. This study aims to e...
Deep neural networks (DNNs) have been widely applied in different application domains. The DNN was first studied intensively in vision applications before adapting it to other fields. To migrate DNN solutions from the vision domain to another applica...
The data-driven intelligent fault diagnosis method has shown great potential in improving the safety and reliability of train operation. However, the noise interference and multi-scale signal characteristics generated by the train transmission system...
Machine Reading Comprehension (MRC) research concerns how to endow machines with the ability to understand given passages and answer questions, which is a challenging problem in the field of natural language processing. To solve the Chinese MRC task...
The idea of the person re-identification (Re-ID) task is to find the person depicted in the query image among other images obtained from different cameras. Algorithms solving this task have important practical applications, such as illegal action pre...
3 September 2022
Elite masters endurance athletes are considered models of optimal healthy aging due to the maintenance of high cardiorespiratory fitness (CRF) until old age. Whereas a drop in VO2max in masters athletes has been broadly investigated, the modifying im...
Driven by growing public security demands and the advancement of intelligent surveillance systems, person re-identification (ReID) has emerged as a prominent research focus in the field of computer vision. However, this task presents challenges due t...
The definition of vehicle viewpoint annotations is ambiguous due to human subjective judgment, which makes the cross-domain vehicle re-identification methods unable to learn the viewpoint invariance features during source domain pre-training. This wi...
The automated identification system of vessel movements receives a huge amount of multivariate, heterogeneous sensor data, which should be analyzed to make a proper and timely decision on vessel movements. The large number of vessels makes it difficu...
The main objective of this study is to automatically detect real-time snow-related road surface conditions using imagery captured from existing roadside webcams along interstate freeways. Blowing snow is considered one of the most hazardous roadway w...
This paper proposes a framework for unmixing of hyperspectral data that is based on utilizing the scattering transform to extract deep features that are then used within a neural network. Previous research has shown that using the scattering transfor...
Intelligent mobile image sensing powered by deep learning analyzes images captured by cameras from mobile devices, such as smartphones or smartwatches. It supports numerous mobile applications, such as image classification, face recognition, and came...
Background/Objectives: The timely and accurate detection of atrial fibrillation (AF) is critical from a clinical perspective. Detecting short or transient AF events is challenging in 24–72 h Holter ECG recordings, especially when symptoms are i...
Deep learning has achieved good classification results in the field of traffic classification in recent years due to its good feature representation ability. However, the existing traffic classification technology cannot meet the requirements for the...
Recently, convolutional neural networks (CNNs) have shown significant advantages in the tasks of image classification; however, these usually require a large number of labeled samples for training. In practice, it is difficult and costly to obtain su...
Tree species classification is an important and challenging task in image recognition and the management of forest resources. Moreover, the task of tree species classification based on remote sensing images can significantly improve the efficiency of...
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