Online learning has become increasingly prevalent in real-world applications, where data streams often comprise heterogeneous feature types—both nominal and numerical—and labels may not arrive synchronously with features. However, most ex...
In this paper, we apply a Markov decision process to find the optimal asynchronous dynamic policy of an energy-efficient data center with two server groups. Servers in Group 1 always work, while servers in Group 2 may either work or sleep, and a fast...
Mobile group consumption refers to consumption by a group of people, such as a couple, a family, colleagues and friends, based on mobile communications. It differs from consumption only involving individuals, because of the complex relations among gr...
In view of the problems of data pollution, incomplete feature extraction, and poor multi-network parameter sharing and transmission under the federated learning framework of deep learning, this article proposes an improved asynchronous federated lear...
In an asynchronous data stream, the data items may be out of order with respect to their original timestamps. This paper studies the space complexity required by a data structure to maintain such a data stream so that it can approximate the set of fr...
In underwater acoustic modem design, pure asynchrony can contribute to improved wake-up coordination, thus avoiding energy-inefficient synchronization mechanisms. Nodes are designed with a pre-receptor and an acoustically adapted Radio Frequency Iden...
This paper presents a recent self-sampled-data control algorithm applied to nonlinear systems with actuator failures. Our approach uses the linear model of a given nonlinear system, and based on a granted actuator fault observer method, an asynchrono...
Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing....
The difficulty of adding external excitation and the asynchronous data collection from the industrial robot operation limited the online parameter identification of industrial robots. In this regard, this study proposes an identification method that...
With the continuous improvement of the performance of artificial intelligence and neural networks, a new type of computing architecture-edge computing, came into being. However, when the scale of hybrid intelligent edge systems expands, there are red...
With the advancement of the large language model (LLM), the demand for data labeling services has increased dramatically. Big models are inseparable from high-quality, specialized scene data, from training to deploying application iterations to landi...
Plant species classification in semi-arid mining areas is of great significance in assessing the environmental impacts and ecological restoration effects of coal mining. However, in semi-arid mining areas characterized by mixed arbor–shrub&ndas...
Building energy consumption data are widely used in various data research and analysis, and data quality is crucial for the accuracy of analysis results. Most existing data quality research focuses on the numerical accuracy of data, while little atte...
Addition is the key operation in digital systems, and floating-point adder (FPA) is frequently used for real number addition because floating-point representation provides a large dynamic range. Most of the existing FPA designs are synchronous and th...
Event cameras, as bio-inspired visual sensors, offer significant advantages in their high dynamic range and high temporal resolution for visual tasks. These capabilities enable efficient and reliable motion estimation even in the most complex scenes....
We review recent articles that focus on the main issues identified in high-frequency financial data analysis. The issues to be addressed include nonstationarity, low signal-to-noise ratios, asynchronous data, imbalanced data, and intraday seasonality...
The acquisition, processing, and monitoring of biomechanical variables in dynamic environments require sensor network architectures capable of handling high concurrency and large data volumes. This study aims to develop, validate, and deploy a robust...
The large-scale integration of stochastic renewable energy sources necessitates enhanced dynamic balancing capabilities in power systems, positioning hydropower as a critical balancing asset. Conventional excitation systems utilizing hot-standby dual...
Teachers’ professional learning often includes online components. This study examined how a case of 37 teachers utilized a specific online asynchronous professional learning platform designed to support teachers’ growth in learning to tea...
In this paper, we present a novel framework for enriching time series data in smart cities by supplementing it with information from external sources via semantic data enrichment. Our methodology effectively merges multiple data sources into a unifor...
This study presents a cost-effective IoT-based Supervisory Control and Data Acquisition system for the real-time monitoring and control of photovoltaic systems in a rural Pakistani community. The system utilizes the Blynk platform with Arduino Nano,...
This work presents the design and simulation of a time-interleaved successive approximation register (SAR) analog-to-digital converter (ADC) implemented in GlobalFoundries’ 22 nm Fully Depleted Silicon-on-Insulator (FD-SOI) CMOS process. Motiva...
The nature of contemporary spatial data infrastructures lies in the provision of geospatial information in an on-demand fashion. Although recent applications identified the need to react to real-time information in a time-critical way, research effor...
Interdisciplinary collaboration and communication are two essential aspects of Building Information Modeling (BIM) [...]
This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. Leveraging data from Moodle, a widely used learning management system (LMS), we analyzed 450...
Multi-radar systems can significantly improve tracking robustness and accuracy, but practical deployments are challenged by asynchronous sensing timestamps across distributed platforms and by limited communication bandwidth. This paper proposes a com...
The phenomenon of the COVID-19 pandemic requires prevention actions, such as social and physical distancing. In education, there is no choice but to adapt to online learning from traditional face-to-face learning. Online learning is divided into two...
Wearable medical devices, wireless sensor networks, and other energy-constrained sensing devices are often concerned with finding specific data within more-complex signals while maintaining low power consumption. Traditional analog-to-digital convert...
Successful track-to-track association (TTTA) in a multisensor and multitarget scenario is predicated on a reasonable likelihood function to evaluate the similarity of asynchronous mono tracks. To deal with the lack of synchronous data and prior knowl...
A network-on-chip (NoC) offers high performance, flexibility and scalability in communication infrastructure within multi-core platforms. However, NoCs contribute significantly to the overall system’s power consumption. The double-layer energy effici...
Due to the COVID-19 pandemic, schools and universities across the world have had to switch to online learning, which is offered either synchronously or asynchronously. This study examined the role of self-regulation on students’ performance in each o...
In this paper, a model-free adaptive direct torque control (MFADTC) method for the speed regulation of asynchronous motors is proposed to solve the problems of modeling difficulties and poor anti-disturbance ability of the asynchronous motor. The des...
Federated learning (FL), as a privacy-preserving distributed machine learning paradigm, demonstrates unique advantages in addressing data silo problems. However, the prevalent statistical heterogeneity (data distribution disparities) and system heter...
This paper presents a new, efficient asynchronous early output majority voter that can be used to effectively realize an asynchronous triple modular redundancy (TMR) implementation. For the input-output mode asynchronous realization, the dual-rail co...
This article introduces a novel asynchronous full adder that operates in an input–output mode (IOM), displaying both monotonicity and an early output characteristic. In a monotonic asynchronous circuit, the intermediate and primary outputs exhi...
The rapid development of artificial intelligence (AI) and 5G paradigm brings infinite possibilities for data annotation for new applications in the industrial Internet of Things (IIoT). However, the problem of data annotation consistency under distri...
In the era of cloud computing, the reliability and efficiency of distributed systems, particularly in cloud-based databases and applications, are important. State Machine Replication (SMR), underpinning these distributed architectures, commonly utili...
The recent unprecedented success of deep learning (DL) in various fields is underlied by its use of large-scale data and models. Training a large-scale deep neural network (DNN) model with large-scale data, however, is time-consuming. To speed up the...
Coordinated cyber attacks tamper with measurement data to disrupt the situational awareness of active distribution systems. Various sensors report measurements asynchronously at different rates, which introduces challenges during state estimation. In...
Although possessing flexibility and accessibility, asynchronous online courses suffer from high attrition and cause unsatisfactory learning performance, leading to a pressing need to understand factors influencing learners’ continuance of learn...
Asynchronous loads (AL), because of their low negative-sequence resistance, produce the effect of reduced unbalance at their connection points. Therefore, proper modeling of unbalanced load flows in power supply systems requires properly accounting f...
Industrial process monitoring is a critical application of multivariate time-series (MTS) anomaly detection, especially crucial for safety-critical systems such as nuclear power plants (NPPs). However, some current data-driven process monitoring appr...
To address the challenges of short dwell time near top dead center (TDC) and uneven heat release, this paper presents a comprehensive analysis of the effects of different ignition schemes on combustion characteristics, flame formation and development...
A 400-level undergraduate oral presentation and discussion course in Systems Neuroscience was delivered asynchronously online during the COVID-19 pandemic. Enrolled students banked their narrated oral presentations in video format online then engaged...
For a small satellite, the processor onboard the attitude determination and control system (ADCS) is required to monitor, communicate, and control all the sensors and actuators. In addition, the processor is required to consistently communicate with...
Real-time kinematic (RTK) positioning is a satellite navigation technique that is widely used to enhance the precision of position data obtained from global navigation satellite systems (GNSS). This technique can reduce or eliminate significant corre...
This paper discusses asynchronous distributed inference in object tracking. Unlike many studies, which assume that the delay in communication between partial estimators and the central station is negligible, our study focuses on the problem of asynch...
Three-phase asynchronous motors have a wide range of applications in the machinery industry and fault diagnosis aids in the healthy operation of a motor. In order to improve the accuracy and generalization of fault diagnosis in three-phase asynchrono...
With the hierarchical evolution of distribution network control architectures, distributed state estimation has become a focal point of research. To address communication delays arising from inter-level data exchanges, this paper proposes a multi-lev...
This article presents the results of the analysis of experimental data that were obtained during industrial tests of an adjustable asynchronous traction electric drive of a shuttle car for the mining industry. During these tests, by changing the para...
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