Working memory and attention are interrelated constructs that are sometimes even considered indistinguishable. Since attention is not a uniform construct, it is possible that different types of attention affect working memory capacity differently. To...
Recent research has extensively investigated working memory (WM)-guided attention, which is the phenomenon of attention being directed towards information in the external environment that matches the content stored in WM. While prior studies have foc...
Although scientists know that information stored in working memory guides visual attention, how this is accomplished is still under debate. Specifically, there is a dispute between the Biased Competition Model and Visual Attention Theory. The current...
Visual question answering (VQA) is regarded as a multi-modal fine-grained feature fusion task, which requires the construction of multi-level and omnidirectional relations between nodes. One main solution is the composite attention model which is com...
The role of attention allocation in object-location memory has been widely studied through incidental and intentional encoding conditions. However, the relation between sustained attention and memory encoding processes has scarcely been studied. The...
Lighting plays a fundamental role in learning spaces as it influences students’ performance. Nowadays, new technologies and new teaching methods in higher education mean that very different visual tasks are performed in the classroom, so further rese...
There are many reading competence tests in Spanish on the market and available in institutions like libraries or universities; some are scientifically validated whereas others lack theoretical support. Among the users of the AECL (Asociación E...
There is a debate about whether working memory (WM) representations are individual features or bound objects. While spatial attention is reported to play a significant role in feature binding, little is known about the role of spatial attention in WM...
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-age children. Although it has been well documented that children with ADHD are associated with impairment of executive functions including working memor...
Spatiotemporal prediction is challenging due to extracting representations being inefficient and the lack of rich contextual dependences. A novel approach is proposed for spatiotemporal prediction using a dual memory LSTM with dual attention neural n...
Polyphonic sound event detection (SED) is the task of detecting the time stamps and the class of sound event that occurred during a recording. Real life sound events overlap in recordings, and their durations vary dramatically, making them even harde...
29 March 2021
Fibromyalgia syndrome (FMS) is a chronic, generalized and diffuse pain disorder accompanied by cognitive deficits such as forgetfulness, concentration difficulties, loss of vocabulary and mental slowness, among others. In recent years, FMS has been a...
Objective: Obesity represents a health risk and several studies have linked this clinical entity to cognitive deficits. Among the neuropsychological rehabilitation tools, Peak, a digital application, has shown positive results as a therapeutic method...
Objectives: The effects of brain tumors located in the supplementary motor area (SMA) have so far been described mainly in the context of motor and speech disorders. There are few studies that have considered other cognitive domains, so this study ai...
The study presented here introduces a new approach to the investigation of transsaccadic memory for objects in naturalistic scenes. Participants were tested with a whole-report task from which—based on the theory of visual attention (TVA)—processing...
In this paper, we propose a novel network, self-attention generative adversarial network with blur and memory (BaMSGAN), for generating anime faces with improved clarity and faster convergence while retaining the capacity for continuous learning. Tra...
Humans inherently perceive 3D scenes using prior knowledge and visual perception, but 3D reconstruction in computer graphics is challenging due to complex object geometries, noisy backgrounds, and occlusions, leading to high time and space complexity...
Memory resident malware, particularly fileless and heavily obfuscated types, continues to pose a major problem for endpoint defense tools, as these threats often slip past traditional signature-based detection techniques. Deep learning has shown prom...
Many training programs have been designed using modern software to restore the impaired cognitive functions in patients with acquired brain damage (ABD). The objective of this study was to evaluate the effectiveness of a computer-based training progr...
The effect of non-informational speech spectrum noise as a distractor on cognitive and listening comprehension ability was examined in fifty-three young, normal hearing adults. Time-controlled tasks were used to measure auditory working memory (WM) c...
Selecting a target based on a representation in visual working memory (VWM) affords biasing covert attention towards objects with memory-matching features. Recently, we showed that even task-irrelevant features of a VWM template bias attention. Speci...
In this paper, a novel hyperspectral denoising method is proposed, aiming at restoring clean images from images disturbed by complex noise. Previous denoising methods have mostly focused on exploring the spatial and spectral correlations of hyperspec...
The network traffic prediction (NTP) model can help operators predict, adjust, and control network usage more accurately. Meanwhile, it also reduces network congestion and improves the quality of the user service experience. However, the characterist...
While the increased availability of traffic data is allowing us to better understand urban mobility, research on data-driven and predictive modeling is also providing new methods for improving traffic management and reducing congestion. In this paper...
Background and Purpose: The proliferation of short-form video content on social media platforms has led to increased user engagement but also raised concerns about potential addictive behaviors and cognitive consequences, particularly among youth. Th...
One-shot person Re-identification, which owns one labeled sample among numerous unlabeled data for each identity, is proposed to tackle the problem of the shortage of labeled data. Considering the scenarios without sufficient labeled data, it is very...
Previous research consistently reported that subjects that were exclusively breastfed (eBF) vs. not-exclusively breastfed (neBF) during infancy (0–6 months) showed increased scores of general intelligence measures (e.g., the intelligence quotie...
Introduction: Asthma is a chronic respiratory disease affecting approximately 5 million children in the US, but little is known about whether asthma alters children’s attention and memory functions. Most studies on this topic focus on psychiatr...
Background: Psoriasis and atopic dermatitis are chronic skin diseases found all over the world that cause a lot of suffering to patients. Objectives: The aim of this study was to answer the following questions: whether people suffering from psoriasis...
Counting the number of trees and obtaining information on tree crowns have always played important roles in the efficient and high-precision monitoring of forest resources. However, determining how to obtain the above information at a low cost and wi...
Shear wave velocity (VS) is a vital prerequisite for rock geophysics. However, due to historical, cost, and technical reasons, the shear wave velocity of some wells is missing. To reduce the deviation of the description of underground oil and gas dis...
One of the important criteria used in judging the performance of a chatbot is the ability to provide meaningful and informative responses that correspond with the context of a user’s utterance. Nowadays, the number of enterprises adopting and r...
The installed capacity of photovoltaic power generation occupies an increasing proportion in the power system, and its stability is greatly affected by the fluctuation of solar radiation. Accurate prediction of solar radiation is an important prerequ...
Answer selection, as a crucial method for intelligent medical service robots, has become more and more important in natural language processing (NLP). However, there are still some critical issues in the answer selection model. On the one hand, the m...
High precision in forecasting travel demand for online car-hailing is crucial for traffic management to schedule vehicles, hence reducing energy consumption and achieving sustainable development. Netflix demand forecasting relies on the capture of sp...
Nowadays, video surveillance has become ubiquitous with the quick development of artificial intelligence. Multi-object detection (MOD) is a key step in video surveillance and has been widely studied for a long time. The majority of existing MOD algor...
As scalar neurons of traditional neural networks promote dimension reduction caused by pooling, it is a difficult task to extract the high-dimensional spatial features and long-term correlation of pure signals from the noisy vibration signal. To addr...
Accurately predicting proton flux in the space radiation environment is crucial for satellite in-orbit management and space science research. This paper proposes a proton flux prediction method based on a hybrid neural network. This method is a predi...
Monitoring cycle life can provide a prediction of the remaining battery life. To improve the prediction accuracy of lithium-ion battery capacity degradation, we propose a hybrid long short-term memory recurrent neural network model with an attention...
Cloud image prediction is a spatio-temporal sequence prediction task, similar to video prediction. Spatio-temporal sequence prediction involves learning from historical data and using the learned features to generate future images. In this process, t...
Travel time prediction is critical for advanced traveler information systems (ATISs), which provides valuable information for enhancing the efficiency and effectiveness of the urban transportation systems. However, in the area of bus trips, existing...
In remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image an...
Soil moisture is recognized as a crucial variable in land–atmosphere interactions. This study introduces the Convolutional Attention Encoder–Decoder Long Short-Term Memory (CAEDLSTM) model to address the uncertainties and limitations inhe...
Current evidence indicates that acute aerobic exercise might increase domain-specific cognitive performance. However, only a small number of studies deduced the impact on lower and higher cognitive functions systematically or analyzed dose–resp...
An accurate dam deformation prediction model is vital to a dam safety monitoring system, as it helps assess and manage dam risks. Most traditional dam deformation prediction algorithms ignore the interpretation and evaluation of variables and lack qu...
Face memory impairments are common but heterogeneous in autism spectrum disorder (ASD), which may be influenced by co-occurrence with attention-deficit/hyperactivity disorder (ADHD). Here, we aimed to investigate the phenotype change of face memory i...
In the context of the rapid evolution of financial markets, the precise prediction of stock prices has become increasingly complex and challenging, influenced by a myriad of factors including macroeconomic indicators, company financial conditions, an...
A battery management system (BMS) is an important link between on-board power battery and electric vehicles. The BMS is used to collect, process, and store important information during the operation of a battery pack in real time. Due to the wide app...
Background: Children are especially sensitive to a broad range of influences and show a remarkable capacity for learning. One prominent example is declarative memory, which may be influenced by a variety of factors and is impaired in attention defici...
The rapid advancement of industrial processes makes ensuring the stability of industrial equipment a critical factor in improving production efficiency and safeguarding operational safety. Fault warning systems, as a key technological means to enhanc...
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