202 Results Found

Background: The “Guidelines for the Management of Specific Learning Disorders” provide clear diagnostic and evaluative guidance on Reading Comprehension Disorder (RCD), as suggested by the DSM-5. The present study investigated the relatio...

Writers with decoding and/or spelling difficulties often produce short, lower-quality texts and experience less fluent writing, frequently interrupted by long pauses at the word level. Research suggests that from adolescence onward, such writers beco...

Morphological processing is the use of morphological structure during word reading. This study investigated whether middle school students applied morphological structure automatically when reading words. In addition, this study asked whether student...

Current language models have achieved remarkable success in NLP tasks. Nonetheless, individual decoding methods face difficulties in realizing the immense potential of these models. The challenge is primarily due to the lack of a decoding framework t...

Zero-shot neural decoding aims to decode image categories, which were not previously trained, from functional magnetic resonance imaging (fMRI) activity evoked when a person views images. However, having insufficient training data due to the difficul...

Intent detection and slot filling tasks share common semantic features and are interdependent. The abundance of professional terminology in specific domains, which poses difficulties for entity recognition, subsequently impacts the performance of int...

Video compression is designed to provide good subjective image quality, even at a high-compression ratio. In addition, video quality metrics have been used to show the results can maintain a high Peak Signal-to-Noise Ratio (PSNR), even at high compre...

In a low-reading-achievement context, this study examines the applicability of the Simple View of Reading in the Dominican Republic, a Spanish-speaking country, assessing elementary students across the first seven years of formal schooling, and it in...

Cloud detection is an essential step in optical remote sensing data processing. With the development of deep learning technology, cloud detection methods have made remarkable progress. Among them, researchers have started to try to introduce Transfor...

To address existing issues in water extraction from SAR images based on deep learning, such as confusion between mountain shadows and water bodies and difficulty in extracting complex boundary details for continuous water bodies, the LGFUNet model is...

Children with Down syndrome are at risk of reading difficulties. Reading skills are crucial for social and academic development, and thus, understanding the nature of reading in this clinical group is important. This longitudinal study investigated t...

The main purpose of this research was to analyze the prevalence and diversity of reading comprehension difficulties in Spanish students of primary and secondary schools. We evaluated a large sample of students from the Canary Islands region that stre...

This paper presents PCB design solutions for implementing a radiative-field RF energy harvester with an ASK-PWM decoding communication scheme using available commercial components. The paper provides the design approach and tackles key challenges suc...

Silent speech decoding is a novel application of the Brain–Computer Interface (BCI) based on articulatory neuromuscular activities, reducing difficulties in data acquirement and processing. In this paper, spatial features and decoders that can...

In the last years, there has been a big effort to identify risk factors for reading difficulties and to develop new methodologies to help struggling readers. It has been shown that early intervention is more successful than late intervention, and tha...

Dyslexic adolescents demonstrate deficits in word decoding, recognition, and oculomotor coordination as compared to healthy controls. Our lab recently showed intrinsic deficits in large saccades and vergence movements with a Remobi device independent...

Introduction: Operative time is commonly used as a surrogate marker for operative difficulty in liver resection, but the contribution of other intraoperative factors is less understood. This study aimed to develop an objective, composite score to ass...

Children born preterm (<37 weeks’ gestation) show a specific vulnerability for socio-emotional difficulties, which may lead to an increased likelihood of developing behavioral and psychiatric problems in adolescence and adulthood. The accura...

In this paper, we construct a five dimensional continuous hyperchaotic system and propose an image encryption scheme based on the hyperchaotic system, which adopts DNA dynamic coding mechanism and classical scrambling diffusion encryption structure....

Electroencephalography-based motor imagery (EEG-MI) classification is a critical component of the brain-computer interface (BCI), which enables people with physical limitations to communicate with the outside world via assistive technology. Regrettab...

This study aimed to develop an intuitive gait-related motor imagery (MI)-based hybrid brain-computer interface (BCI) controller for a lower-limb exoskeleton and investigate the feasibility of the controller under a practical scenario including stand-...

This study assessed two components of face emotion processing: emotion recognition and sensitivity to intensity of emotion expressions and their relation in children age 4 to 12 (N = 216). Results indicated a slower development in the accurate decodi...

To address issues such as detection failure and the difficulty in locating gripping points caused by the stacked placement of irregular parts in the automated sheet metal production process, a highly robust method for the recognition and pose estimat...

Decoding motor imagery electroencephalography (MI-EEG) signals presents significant challenges due to the difficulty in capturing the complex functional connectivity between channels and the temporal dependencies of EEG signals across different perio...

Remote sensing image object detection presents significant challenges, due to the difficulty in accurately predicting the rotational angles of ground-oriented objects, coupled with issues such as the false and missed detection caused by insufficient...

Sonar is a valuable tool for ocean exploration since it can obtain a wealth of data. With the development of intelligent technology, deep learning has brought new vitality to underwater sonar image classification. However, due to the difficulty and h...

In object detection, Transformer-based models such as DETR have exhibited state-of-the-art performance, capitalizing on the attention mechanism to handle spatial relations and feature dependencies. One inherent challenge these models face is the inte...

Background/objectives: A child’s working memory needs to be efficient in order to perform well at school, because its manipulative function needs to work properly in order to compose and decompose words, a skill that is necessary for reading. T...

The detection of crack information is very important in mural conservation. In practice, the number of ancient murals is scarce, and the difficulty of collecting digital information about murals leads to minimal data being collected. Crack informatio...

A Brain–Computer Interface (BCI) is a medium for communication between the human brain and computers, which does not rely on other human neural tissues, but only decodes Electroencephalography (EEG) signals and converts them into commands to co...

Low-light image enhancement (LLIE) aims to improve the visual quality of images taken under complex low-light conditions. Recent works focus on carefully designing Retinex-based methods or end-to-end networks based on deep learning for LLIE. However,...

High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices’ applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), h...

Supervisory control and data acquisition (SCADA) systems are widely utilized in power equipment for condition monitoring. For the collected data, there generally exists a problem—missing data of different types and patterns. This leads to the p...

Alexithymia, a multifaceted personality construct, is known to be related to difficulties in the decoding of emotional facial expressions, especially in case of suboptimal stimuli. The present study investigated whether and which facets of alexithymi...

Specific Learning Disorder (SLD) is a multifactorial, neurodevelopmental disorder which may involve persistent difficulties in reading (dyslexia), written expression and/or mathematics. Dyslexia is characterized by difficulties with speed and accurac...

Deep learning plays a highly essential role in the domain of remote sensing change detection (CD) due to its high efficiency. From some existing methods, we can observe that the fusion of information at each scale is quite vital for the accuracy of t...

Remote sensing semantic segmentation encounters several challenges, including scale variation, the coexistence of class similarity and intra-class diversity, difficulties in modeling long-range dependencies, and shadow occlusions. Slender structures...

Although the policy-gradient methods for reinforcement learning have shown significant improvement in image captioning, how to achieve high performance during the reinforcement optimizing process is still not a simple task. There are at least two dif...

The segmentation of visible ship images is an important part of intelligent ship monitoring systems. However, this task is faced with many difficulties in practical applications, such as complex background environments, variations in illumination, an...

This study presents the development and validation of the Record of Decision-Making (RODM), a formative assessment designed to measure beginning readers’ use of phonic elements to decode unknown words while reading. Grounded in overlapping wave...

Pre-processing and post-processing are significant aspects of natural language processing (NLP) application software. Pre-processing in neural machine translation (NMT) includes subword tokenization to alleviate the problem of unknown words, parallel...

With the increasingly maturing technology of unmanned surface vehicles (USVs), their applications are becoming more and more widespread. In order to meet operational requirements in complex scenarios, the real-time interaction and linkage of a large...

Background: The rapid expansion of the brain–computer interface for patients with neurological deficits has garnered significant interest, and for patients, it provides an additional route where conventional rehabilitation has its limits. This...

In response to the shortcomings of current spatiotemporal prediction models, which frequently encounter difficulties in temporal feature extraction and the forecasting of medium to high echo intensity regions over extended sequences, this study prese...

Change detection (CD) is an important remote sensing (RS) data analysis technology. Existing remote sensing change detection (RS-CD) technologies cannot fully consider situations where pixels between bitemporal images do not correspond well on a one-...

Satellite communications face difficulties such as intensified environmental attenuation, dynamic time-varying links, and diverse business scenarios, which usually require channel coding schemes with high coding gain and high throughput. Low-density...

In this paper, a packet loss concealment (PLC) algorithm for CELP-type speech coders is proposed in order to improve the quality of decoded speech under burst packet loss conditions in a wireless sensor network. Conventional receiver-based PLC algori...

Background: Automated surgical navigation can be separated into three stages: (1) organ identification and localization, (2) identification of the organs requiring further surgery, and (3) automated planning of the operation path and steps. With its...

This paper describes an automatic drum transcription (ADT) method that directly estimates a tatum-level drum score from a music signal in contrast to most conventional ADT methods that estimate the frame-level onset probabilities of drums. To estimat...

Accurate glomerular segmentation in renal pathological images is a key challenge for chronic kidney disease diagnosis and assessment. Due to the high visual similarity between pathological glomeruli and surrounding tissues in color, texture, and morp...