We propose a simple and robust HSV color-space-based algorithm that can automatically extract object position information without human intervention or prior knowledge. In manufacturing sites with high variability, it is difficult to recognize produc...
Effective diagnosis of electric bearing faults, especially weak early-stage faults, remains challenging due to complex rotational-speed conditions and external noise. Although the velocity-guided chirplet transform (VGCT) can effectively characterize...
We study the foot plantar sensor placement by a deep reinforcement learning algorithm without using any prior knowledge of the foot anatomical area. To apply a reinforcement learning algorithm, we propose a sensor placement environment and reward sys...
This paper develops the model of the joint phantom track deception and the joint techniques of time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) localization to deceive air defense radar networks under the condition that an...
The aim of this paper is to formulate and analyze a cyclic iterative algorithm in real Hilbert spaces which converges strongly to a common solution of fixed point problem and multiple-sets split common fixed point problem involving demicontractive op...
Virtual reality offers unprecedented experiences and serves as a new learning tool. However, limited research has examined how this novel visual experience influences cognitive processes. This study described a conceptual theoretical framework of vis...
Currently, using semantic segmentation networks to distinguish dynamic and static key points has become a mainstream designing method for semantic SLAM systems. However, the semantic SLAM systems must have prior semantic knowledge of relevant dynamic...
The objective of this paper is to introduce an iterative method with the addition of an inertial term to solve equilibrium problems in a real Hilbert space. The proposed iterative scheme is based on the Mann-type iterative scheme and the extragradien...
Camouflaged object detection (COD) is an arduous challenge due to the striking resemblance of camouflaged objects to their surroundings. The abundance of similar background information can significantly impede the efficiency of camouflaged object det...
To meet the demand for the aerosol detection of single-angle and multi-band polarization instrument containing short-wave infrared bands, an inversion algorithm that makes full use of multi-band intensity and polarization information is proposed base...
Aero engines are complex coupled systems in which faults in one subsystem can propagate and affect the performance of others. Relying on single-source performance parameters is often insufficient for accurately assessing component degradation. Althou...
Although stochastic resonance (SR) has been widely used to enhance weak fault signatures in machinery and has obtained remarkable achievements in engineering application, the parameter optimization of the existing SR-based methods requires the quanti...
21 July 2022
To make possible the inclusion of children with autism spectrum disorder (ASD) in mainstream settings, parental knowledge and attitudes towards the disorder play a key role between the home and the school setting. However, prior literature has not ca...
In sensor-based human activity recognition, many methods based on convolutional neural networks (CNNs) have been proposed. In the typical CNN-based activity recognition model, each class is treated independently of others. However, actual activity cl...
A wireless communication intelligent anti-jamming decision algorithm based on Deep Reinforcement Learning (DRL) can gradually optimize communication anti-jamming strategies without prior knowledge by continuously interacting with the jamming environm...
The clustering analysis algorithm is used to reveal the internal relationships among the data without prior knowledge and to further gather some data with common attributes into a group. In order to solve the problem that the existing algorithms alwa...
This study focuses on addressing the tracking control problem for a coaxial unmanned aerial vehicle (UAV) without any prior knowledge of its dynamic model. To overcome the limitations of model-based control, a model-free approach based on terminal sl...
Conventional control of robotic manipulators requires prior knowledge of their kinematic structure. Model-learning controllers have the advantage of being able to control robots without requiring a complete kinematic model and work well in less struc...
Extraneous details in visual representations can prompt children to use well-rehearsed, yet inappropriate, strategies that can hinder mathematics learning. Prior domain knowledge can reduce the negative effects of extraneous details in instructional...
Psychophysical methods allow us to measure the relationship between stimuli and sensory perception. Of these, Detection Threshold (DT) allows us to know the minimum concentration to produce taste identification. Given this, we wonder whether, for exa...
16 July 2024
This study examines HIV/AIDS-associated knowledge and attitudes towards treating disadvantaged communities among predoctoral dental students in U.S. dental schools who have not yet commenced their Community-Based Dental Education (CBDE) training. It...
Image segmentation attempts to classify the pixels of a digital image into multiple groups to facilitate subsequent image processing. It is an essential problem in many research areas such as computer vision and image processing application. A large...
In optical sparse projection reconstruction, the reconstruction of the tested field often requires the utilization of a priori knowledge to compensate for the lack of information due to the sparse projection angle. For situations where the radiation...
Autonomous decision-making is a hallmark of intelligent mobile robots and an essential element of autonomous navigation. The challenge is to enable mobile robots to complete autonomous navigation tasks in environments with mapless or low-precision ma...
Massive machine-type communications (mMTC) in future 6G networks will involve a vast number of devices with sporadic traffic. Grant-free access has emerged as an effective strategy to reduce the access latency and processing overhead by allowing devi...
Multi-target imaging beyond the optical memory effect (OME) is fundamentally challenged by the incoherent superposition of speckles originating from different OME regions, which renders object separation highly ill-posed. To address this challenge, w...
Simultaneous Localization And Mapping (SLAM) usually assumes the robot starts without knowledge of the environment. While prior information, such as emergency maps or layout maps, is often available, integration is not trivial since such maps are oft...
Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to ob...
Knowledge tracing (KT), aiming to model learners’ mastery of a concept based on their historical learning records, has received extensive attention due to its great potential in realizing personalized learning in intelligent tutoring systems. H...
Youth Mental Health First Aid (YMHFA) is a widely adopted professional development tool that helps educators across the United States improve their mental health literacy. Data from a pretest/posttest evaluation of the YMHFA training delivered at fiv...
27 December 2022
Although oral health is considered a key indicator of overall health, dentistry is still neglected in medical education at the university level. Interprofessional education (IPE) is an important tool to promote collaboration among health care provide...
The challenge of combining two unbiased estimators is a common occurrence in applied statistics, with significant implications across diverse fields such as manufacturing quality control, medical research, and the social sciences. Despite the widespr...
Variational graph autoencoder, which can encode structural information and attribute information in the graph into low-dimensional representations, has become a powerful method for studying graph-structured data. However, most existing methods based...
Platform vibration introduces sinusoidal modulation in inverse synthetic aperture lidar (ISAL) imaging, which causes paired echoes in ISAL imaging. In this paper, a varying amplitude vibration phase suppression algorithm is proposed. Working without...
Accurate reconstruction of thin-walled marine structures, such as ship hull plates and stiffened panels, via the conventional inverse Finite Element Method (iFEM) is severely limited by strain data scarcity in real-world deployments. Existing augment...
This paper focuses on state estimation for nonlinear stochastic systems with multiple switching models, especially under challenging conditions where the model dynamics are unknown and the transition probability matrix is uniformly distributed. Gauss...
Sensor-based human activity recognition has been extensively studied. Systems learn from a set of training samples to classify actions into a pre-defined set of ground truth activities. However, human behaviours vary over time, and so a recognition s...
Nowadays, recommender systems are vital in lessening the information overload by filtering out unnecessary information, thus increasing comfort and quality of life. Matrix factorization (MF) is a well-known recommender system algorithm that offers go...
This study investigates an Adaptive Feedback System (AFS) that integrates deep learning (a recurrent neural network trained with historical student data) and GPT-4 to provide personalized feedback in a Digital Art course. In a quasi-experimental desi...
For general insurance pricing, aligning losses with accurate premiums is crucial for insurance companies’ competitiveness. Traditional actuarial models often face challenges like data heterogeneity and mismeasured covariates, leading to misspec...
The remote sensing imaging environment is complex, in which many factors cause image blur. Thus, without prior knowledge, the restoration model established to obtain clear images can only rely on the observed blurry images. We still build the prior w...
In this article, we introduce a new subgradient extra-gradient algorithm to find the common element of a set of fixed points of a Bregman relatively nonexpansive mapping and the solution set of an equilibrium problem involving a Pseudomonotone and Br...
This study examines the perception of insult-related vocabulary in Spanish among native speakers (L1) and Polish learners of Spanish as a foreign language (L2). Insults are analyzed as versatile speech acts fulfilling pragmatic functions such as impo...
Multi-purpose service robots must execute their tasks reliably in different situations, as well as learn from humans and explain their plans to them. We address these issues by introducing a knowledge representation scheme to facilitate skill general...
On the Moon, in the near infrared wavelength range, spectral diagnostic features such as the 1-
Recently, the unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) has become a highly sought-after topic for its wide applications in target recognition, detection, and tracking. However, SAR automatic target recognition (ATR) models based o...
The global availability of information makes its selection difficult, but at the same time it allows for the construction of teaching without the particular prior knowledge of students. However, it requires teachers to learn new abilities, such as de...
Convolutional neural networks (CNNs) are the gold standard in the machine learning (ML) community. As a result, most of the recent studies have relied on CNNs, which have achieved higher accuracies compared with traditional machine learning approache...
Background/Objectives: Migraine affects approximately 3–10% of school-aged children and up to 28% of adolescents, with prevalence increasing during adolescence. For pediatric specialty providers, increased awareness of this condition may influe...
An accurate and robust Automatic License Plate Recognition (ALPR) method proves surprising versatility in an Intelligent Transportation and Surveillance (ITS) system. However, most of the existing approaches often use prior knowledge or fixed pre-and...
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