Remote direct memory access (RDMA)-based distributed memory systems improve cluster-wide memory utilization by allowing for memory-constrained nodes to access unused memory on remote nodes. However, most existing systems adopt a memory-constrained-no...
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We investigated the effect of memory load on attentional control using the Reading Span Test (RST), a task that requires working memory capacity. Previous studies have shown that a shortage of working memory resources leads to a deficit of inhibition...
As digital data have increased exponentially due to an increasing number of information channels that create and distribute the data, distributed in-memory systems were introduced to process big data in real-time. However, when the load is concentrat...
Background: Target enhancement and non-target suppression are two critical mechanisms underlying representational prioritization in visual working memory (VWM). However, it remains unclear how VWM load modulates these prioritization mechanisms. Metho...
Educational video podcasts are increasingly used in higher education, yet the cognitive mechanisms underlying their effectiveness remain underexplored. This experimental study examined how working memory capacity and additive contextual features infl...
Electricity load forecasting is an important task for enhancing energy efficiency and operation reliability of the power system. Forecasting the hourly electricity load of the next day assists in optimizing the resources and minimizing the energy was...
Background/Objectives: A central question in cognitive neuroscience is how information is transferred from working memory to long-term memory, and what factors influence this process. This study aimed to explore the role of cognitive load in the cons...
As an important condition for fatigue analysis and life prediction, load spectrum is widely used in various engineering fields. The extrapolation of load samples is an important step in compiling load spectrum. It is of great significance to select a...
Short-term load forecasting (STLF) plays an important role in facilitating efficient and reliable operations of power systems and optimizing energy planning in the electricity market. To improve the accuracy of power load prediction, an adaptive clus...
In this paper, a fast-transient-response NMOS low-dropout regulator (LDO) with a wide load-capacitance range was presented to provide a V/2 read bias for cross-point memory. To utilize the large dropout voltage in the V/2 bias scheme, a fast loop con...
Non-intrusive load monitoring (NILM) is an important research direction and development goal on the distribution side of smart grid, which can significantly improve the timeliness of demand side response and users’ awareness of load. Due to rap...
Load forecasting for Integrated Energy Systems (IESs) is critical to enabling multi-energy coordinated optimization and low-carbon scheduling. Facing multi-load types and multi-site high-dimensional heterogeneous data, there remains a global learning...
Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) are frequently associated with working memory (WM) dysfunction, which is also observed in various neural psychiatric disorders, including depression, schizophrenia, and ADHD. Early de...
Visual working memory (VWM) enables people to temporarily store important information for use in subsequent tasks. Previous studies have indicated that a negative emotional state can influence the processing of VWM; however, the direction of this inf...
In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and re...
Short-term load forecasting is a key capability for smart-grid operation, but real smart-meter streams are affected by missing values, communication noise, and non-stationary consumption patterns. This paper studies forecasting using raw smart-meter...
Short-term load forecasting (STLF) plays an important role in the economic dispatch of power systems. Obtaining accurate short-term load can greatly improve the safety and economy of a power grid operation. In recent years, a large number of short-te...
The present study aimed to examine the effects of chronological age and cardiorespiratory fitness (CRF) on cognitive performance and prefrontal cortex activity, and to test the compensation-related utilization of neural circuits hypothesis (CRUNCH)....
Background/Objectives: Working memory (WM) performance relies on the coordination of updating and inhibition functions within the central executive system. However, their interaction under varying cognitive loads, particularly across sensory modaliti...
Purpose: The function of working memory (WM) is impaired by total sleep deprivation (TSD) and cognitive load. However, it is unclear whether the load modulates the effect of TSD on WM. We conducted a pilot study to investigate the effects of 36 h of...
High heat load on diesel engines is a main cause of ship failure, which can lead to ship downtime and pose a risk to personal safety and the environment. As such, predictive detection and maintenance measures are highly important. During the operatio...
The large-scale rapid deployment of renewable generation and energy storage is transforming traditional power system dynamics through intermittency, reduced inertia, and pronounced long-range temporal dependence. Existing power system modeling framew...
Forecasting domestic and foreign power demand is crucial for planning the operation and expansion of facilities. Power demand patterns are very complex owing to energy market deregulation. Therefore, developing an appropriate power forecasting model...
Short-term electrical load forecasting is of great significance to the safe operation, efficient management, and reasonable scheduling of the power grid. However, the electrical load can be affected by different kinds of external disturbances, thus,...
Load disaggregation for the identification of specific load types in the total demands (e.g., demand-manageable loads, such as heating or cooling loads) is becoming increasingly important for the operation of existing and future power supply systems....
In order to balance power supply and demand, which is crucial for the safe and effective functioning of power systems, short-term power load forecasting is a crucial component of power system planning and operation. This paper aims to address the iss...
Load forecasting (LF) is essential in enabling modern power systems’ safety and economical transportation and energy management systems. The dynamic balance between power generation and load in the optimization of power systems is receiving inc...
Load decomposition technology is an important aspect of power intelligence. At present, there are mainly machine learning methods based on artificial features and deep learning methods for load decomposition. The method based on artificial features h...
Short-Term Load Forecasting (STLF) is the most appropriate type of forecasting for both electricity consumers and generators. In this paper, STLF in a Microgrid (MG) is performed via the hybrid applications of machine learning. The proposed model is...
Load forecasting is an essential task in the operation management of a power system. Electric power companies utilize short-term load forecasting (STLF) technology to make reasonable power generation plans. A forecasting model with low prediction err...
This paper focuses on analytics of an extremely large dataset of smart grid electricity price and load, which is difficult to process with conventional computational models. These data are known as energy big data. The analysis of big data divulges t...
To accommodate the rapid development of the distribution network of China, it is essential to research load forecasting methods with higher accuracy and stronger generalization capabilities in order to optimize distribution system control strategies,...
With the rapid global proliferation of electric vehicles (EVs), their integration as a significant load component within power systems increasingly influences the stable operation and planning of electrical grids. However, the high uncertainty and ra...
Accurate electrical load forecasting is of great significance to help power companies in better scheduling and efficient management. Since high levels of uncertainties exist in the load time series, it is a challenging task to make accurate short-ter...
The long short-term memory (LSTM) model has been widely used for a broad range of applications entailing the estimation of variables in different fields to improve water quality management in rivers. The main objectives of this study are (1) to devel...
Accurate short-term forecasting of power load is essential for the reliable operation of the comprehensive energy systems of ports and for effectively reducing energy consumption. Owing to the complexity of port systems, traditional load forecasting...
No study has been reported to use machine learning methods to predict the full-range test curves of circular CFST columns. In this paper, the long short-term memory (LSTM) network was introduced to calculate the axially compressive load–strain...
Accurate load forecasting is of vital importance for improving the energy utilization efficiency and economic profitability of intelligent buildings. However, load forecasting is restricted in the popularization and application of conventional load f...
The driving scenario and information load jointly influence the cognitive efficiency of augmented reality head-up display (AR-HUD) interfaces. However, the moderating role of drivers’ working memory capacity (WMC) remains unclear. To investigate this...
Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a predictio...
NiTi shape memory alloy (SMA) tube was coupled with mild steel cylinder in order to investigate deformation mechanisms of NiTi SMA tubes undergoing radial loading. NiTi SMA tubes of interest deal with two kinds of nominal compositions; namely, Ni-50...
Prospective memory (PM) refers to the ability to remember to perform a planned event or activity at a specific time or situation in the future. Implementation intentions can promote a connection between PM cues and intended actions, thus improving an...
Numerosity can be represented in symbolic formats and non-symbolic dot arrays. How numerosity load unfolds across WM encoding/maintenance and test-stage comparison within a single paradigm remains unclear, especially within the tested 4–6 range...
The conventional address map often incurs traffic congestion in on-chip memory components and degrades memory utilization when the access pattern of an application is not matched with the address map. To reduce traffic congestion and improve the memo...
Before COVID-19, universities in the Philippines sparingly used online learning instructional methods. Online learning is now widely known, and universities are increasingly keen to adopt it as a mainstream instructional method. Accounting is a popul...
Many of rural Alaskan communities operate their own, stand-alone electrical microgrids as there is no state-wide power distribution network. Although the fossil fuel-based power generators are the primary energy source in these isolated communities,...
Recent evidence shows that physiological cues, such as pupil dilation (PD), heart rate (HR), skin conductivity (SC), and electroencephalography (EEG), can indicate cognitive load (CL) in users while performing tasks. This paper aims to investigate ph...
Background: The role of cognitive load theory (CLT) in understanding effective pedagogy has received increased attention in the fields of education and psychology in recent years. A considerable amount of literature has been published on the CLT cons...
Accurate power load forecasting is crucial for maintaining the equilibrium between power supply and demand and for safeguarding the stability of power systems. Through a comprehensive optimization of both the parameters and structure of the tradition...
To ensure the constant availability of electrical energy, power companies must consistently maintain a balance between supply and demand. However, electrical load is influenced by a variety of factors, necessitating the development of robust forecast...
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