Human Action Recognition is a challenging task used in many applications. It interacts with many aspects of Computer Vision, Machine Learning, Deep Learning and Image Processing in order to understand human behaviours as well as identify them. It mak...
Online prediction for ship motion with strong nonlinear characteristics under harsh sea states will significantly reduce the damage of large accidents. Therefore, an integrated ship motion online prediction model consisting of a data augmentation alg...
Ship-radiated noise (SRN) recognition is vital for underwater acoustics, with applications in both military and civilian fields. Traditional manual recognition by sonar operators is inefficient and error-prone, motivating the development of automated...
In response to the volatility of photovoltaic power generation, this paper proposes a short-term photovoltaic power generation prediction model (HWOA-MVMD-TPA-TCN) based on a Hybrid Whale Optimization Algorithm (HWOA), multivariate variational mode d...
The near-future parking space availability is informative for the formulation of parking-related policy in urban areas. Plenty of studies have contributed to the spatial–temporal prediction for parking occupancy by considering the adjacency bet...
This study aims to explore the effects of Shape and Decoration on user experience and visual attention in anthropomorphic robot design. Eighty undergraduate students were divided into four groups, each viewing one of four stimuli: (a) Non-hat and Non...
Attentional biases seem to play an important role in anorexia nervosa (AN). The objective of this study was to measure visual attention patterns toward female bodies in adolescents and adults with and without AN in order to explore developmental and...
By studying the classification of anomaly patterns in integrated energy systems, a deeper understanding of their operational status can be gained, leading to improved reliability and efficiency. This can ultimately result in reduced energy consumptio...
Background/Objectives: Normative perceptual segmentation facilitates event perception, comprehension, and memory. Given that native English listeners’ normative perceptual segmentation of English speech streams coexists with a highly selective...
Schizophrenia is characterized by widespread disruptions in neural connectivity and dynamic modulation. Traditional EEG analyses often rely on static or averaged measures, which may overlook the temporal evolution of neural complexity across cognitiv...
Seasonal–trend-decomposed transformer has empowered long-term time series forecasting via capturing global temporal dependencies (e.g., period-based dependencies) in disentangled temporal patterns. However, existing methods design various auto-...
Predicting residential energy consumption is tantamount to forecasting a multivariate time series. A specific window for several sensor signals can induce various features extracted to forecast the energy consumption by using a prediction model. Howe...
There is a strong relationship between sustainability and equality education, as it is emphasized in the United Nations’ Sustainable Development Goals (SDGs). To maintain learning effectiveness, learning attention is a valuable consideration. B...
This paper proposes a hierarchical CNN-sLSTM-Attention model for long-sequence time series forecasting. It enhances efficiency by replacing traditional LSTMs with a stable LSTM (sLSTM) variant, which incorporates exponential gating and memory mixing....
Multivariate time series forecasting has long been a research hotspot because of its wide range of application scenarios. However, the dynamics and multiple patterns of spatiotemporal dependencies make this problem challenging. Most existing methods...
Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) include excessive activity, difficulty sustaining attention, and inability to act in a reflective manner. Early diagnosis and treatment of ADHD is key but may be influenced by the observatio...
Accurate load forecasting for community-level heating, ventilation, and air conditioning (HVAC) plays an important role in determining an efficient strategy for demand response (DR) and the operation of the power grid. However, community-level HVAC i...
When ships sail on the sea, the changes of ship motion attitude presents the characteristics of nonlinearity and high randomness. Aiming at the problem of low accuracy of ship roll angle prediction by traditional prediction algorithms and single neur...
The worst performance rule (WPR) describes the phenomenon that individuals’ slowest responses in a task are often more predictive of their intelligence than their fastest or average responses. To explain this phenomenon, it was previously sugge...
The attentional processes are conceptualized as a system of anatomical brain areas involving three specialized networks of alerting, orienting and executive control, each of which has been proven to have a relation with specified time-frequency oscil...
Infants’ visual processing of emotion undergoes significant development across the first year of life, yet our knowledge regarding the mechanisms underlying these advances is limited. Additionally, infant emotion processing is commonly examined...
Anomaly detection aims to identify abnormal instances that significantly deviate from normal samples. With the natural connectivity between instances in the real world, graph neural networks have become increasingly important in solving anomaly detec...
Blue-Phase Liquid Crystals (BPLCs) are considered to be excellent 3D photonic crystals and have attracted a great deal of attention due to their great potential for advanced applications in a wide range of fields including self-assembling tunable pho...
Because most tasks on real-time systems are conducted periodically, its execution pattern is highly predictable. While such a property of real-time systems allows developing the strong schedulability analysis tools providing high analytical capabilit...
The attention mechanism in natural language processing and self-attention mechanism in vision transformers improved many deep learning models. An implementation of the self-attention mechanism with the previously developed ConvLSTM sequence-to-one mo...
Objective: The aim of this study was to investigate a possible relationship between the time to onset (TTO) of adverse events following immunization (AEFIs) and recall bias and to compare it between AEFIs of COVID-19 vaccines reported though the spon...
We analyze ESG-related news coverage to examine media attention patterns as a reflection of stakeholders’ perceived salience of ESG issues at both the industry and firm levels, offering insights into the evolving nature of ESG materiality. Usin...
This paper introduces an innovative method for enhancing time series data preprocessing by integrating a cycling layer into a self-attention mechanism. Traditional approaches often fail to capture the cyclical patterns inherent to time series data, w...
In safety-critical systems like nuclear power plants, the rapid and accurate perception of visual interface information is vital. This study investigates the relationship between visual attention dispersion measured via heatmap entropy (as a specific...
This study investigates the cognitive mechanisms underlying vigilance and pattern recognition using a novel adaptation of Mackworth’s Clock Test. We aimed to quantify the time it takes for temporal patterns detected unconsciously through implic...
(1) Background: There is evidence of an attention bias–anxiety relationship in children, but lack of appropriate methods has limited the number of studies with children younger than eight years old. This study used eye tracking as a measure of...
Illusory line motion (ILM) refers to the perception of motion in a line that is, in fact, presented in full at one time. One form of this illusion (flashILM) occurs when the line is presented between two objects following a brief luminance change in...
The concept of different publishing patterns during a day has been employed for many decades in the broadcasting industry. These patterns are close related with dayparts, which are defined as sequential time blocks on comparable days during which the...
This study examines how architectural expertise shapes visual perception, extending the “Seeing for Speaking” hypothesis into a non-linguistic domain. Specifically, it investigates whether architectural training influences unconscious visual processi...
Interacting with animals often provides numerous benefits for children with autism spectrum disorder (ASD). One potential explanation for this is that children with ASD exhibit particular visual attention to animals. This study aimed to characterize...
Theories of embodied cognition suggest that hand motions and cognition are closely interconnected. An emerging technique of tracking how participants move a computer mouse (i.e., the mouse-tracking technique) has shown advantages over the traditional...
Mining spatiotemporal mobility patterns is crucial for optimizing urban planning, enhancing transportation systems, and improving public safety by providing useful insights into human movement and behavior over space and time. As an unsupervised lear...
In the civil aviation industry, security risk management has shifted from post-accident investigations and analyses to pre-accident warnings in an attempt to reduce flight risks by identifying currently untracked flight events and their trends and ef...
The first clinical impression of emergency patients conveys a myriad of information that has been incompletely elucidated. In this prospective, observational study, the value of the first clinical impression, assessed by 18 observations, to predict t...
In recent years, there has been a growing interest in developing next point-of-interest (POI) recommendation systems in both industry and academia. However, current POI recommendation strategies suffer from the lack of sufficient mixing of details of...
Text-dependent speaker verification (TD-SV), which verifies speaker identity using predefined phrases, has gained attention as a reliable contactless biometric authentication method for smart devices, internet of things (IoT), and real-time applicati...
The problem of anomaly detection in time series has recently received much attention, but in most practical applications, labels for normal and anomalous data are not available. Furthermore, reasons for anomalous results must often be determined. In...
While a road pattern influences wayfinding and navigation, its influence on the gaze behaviours of navigating pedestrians is not well documented. In this study, we compared gaze behaviour differences between regular and irregular road patterns using...
2 April 2022
Noise annoyance is usually estimated based on time-averaged noise metrics. However, such metrics ignore other potentially important acoustic characteristics, in particular the macro-temporal pattern of sounds as constituted by quiet periods (noise br...
The Flynn effect (FE) is the well-documented generational increase of mean IQ scores over time, but a methodological issue that has not received much attention in the FE literature is the heterogeneity in change patterns across time. Growth mixture m...
The future emotion prediction of users on social media has been attracting increasing attention from academics. Previous studies on predicting future emotion have focused on the characteristics of individuals’ emotion changes; however, the role...
Great Grey Owl incubation patterns; knowledge of its breeding behaviour is limited. We used video recordings of a captive nesting female at the Poznań Zoological Garden to quantify incubation attentiveness (time on and off eggs) and other behavi...
Recognition systems based on palm veins are gaining increasing attention as they are highly distinctive and very hard to counterfeit. Most popular systems are based on infrared radiation; they have the merit to be contactless but can provide only 2D...
The intermittent nature of solar energy poses significant challenges to the integration of photovoltaic (PV) power generation into the electrical grid. Consequently, the precise forecasting of PV power output becomes essential for efficient real-time...
Due to the complexity of the oil and gas station system, the operational data, with various temporal dependencies and inter-metric dependencies, has the characteristics of diverse patterns, variable working conditions and imbalance, which brings grea...
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