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Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract Efficiently and accurately extracting key information from videos has become a core challenge in the current computer vision. Traditional methods rely on manual features and shallow models, making it difficult t...

Abstract The integration of large-scale distributed power sources complicates grid topology and intensifies spatiotemporal coupling in power data. This complicates the analysis of intrinsic correlations and makes predict...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

Efficient and highly accurate road crack detection algorithms are particularly important in road inspection systems. However, some of their limitations have gradually come to the fore as the target detection aspect has b...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

Abstract The increasing number of Internet of Things (IoT) devices demands a rigid and adaptive routing methodologies to ensure the reliable communication especially for the low-power and lossy networks. The Routing Prot...

With the rapid advancement of online education, students’ sentiment feedback serves as a pivotal factor in enhancing course quality and refining pedagogical strategies. However, conventional sentiment analysis approach...

Abstract Matching college students with appropriate innovative training projects is a challenging task that often relies on static assignment techniques, which overlook individual interests, skills, and learning styles. ...

Abstract In response to the dual challenges of complex static obstacles and frequent dynamic disturbances in the construction site environment, this paper proposes a hybrid path planning strategy that integrates global s...

Timetable management is a controversial but core administrative activity at tertiary learning institutions, normally saturated with timetabling clashes, resource wastage, and communication breakdowns. This study describe...

The functioning of an industria l enterprise of discrete production is considered as a set of interconnected production аnd design processes and managing them. Computer modeling of processes is used to review options fo...

The rapid expansion of digital communication has made social media an integral part of daily life, yet it has simultaneously amplified the reach of harmful behaviors. Early detection of cyberbullying is recognized as a c...

Electric Discharge Machining (EDM) is a non-traditional machining process that utilizes electric sparks between an electrode and a workpiece submerged in a dielectric fluid to ablate a material. It is commonly used in di...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

Moving towards a sustainable future, optimising energy systems and resources involves increasingly sophisticated decision-making processes that require balancing technical efficiency with societal, economic and environme...

Abstract To solve the problem of poor effectiveness and efficiency in traditional urban and rural planning layout optimization methods, an innovative urban and rural planning layout optimization method combining ant colo...

Abstract We introduce quantum Kolmogorov-Arnold networks (QKAN), a quantum algorithmic framework inspired by the recently proposed Kolmogorov-Arnold Networks (KAN). QKAN inherits the compositional structure of KAN and is...

With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

This study explores how social media users resist dominant objectifying discourses about physical appearance and sexual attraction on Reddit. Drawing on objectification theory and Foucauldian perspectives on power and su...

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive model...

Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. Wh...