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This study presents a novel asymmetrically coupled cavity (ACC) semiconductor laser structure designed to achieve stable single-mode operation in wider ridge waveguides, enhancing output power. The proposed structure con...

This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

This study develops a first-order quasi-static framework for climbing initiation in passive handcarts and proposes two passive modules to relax the resulting geometric constraints. Unlike motorized platforms that apply t...

Time series analysis is essential for finance, transportation, energy, healthcare, and climate research. While time-frequency domain representation underpins effective time series modeling, its holistic utilization and i...

The Zulfikar sword is a highly standardized sacred weapon symbol in Shia visual culture, forming a stable iconographic lineage across the Middle East and the Irano-Ottoman world. However, it is notably absent from Chines...

Radiography or X-ray imaging is a diagnostic imaging used in medicine to produce images of inner anatomical structures such as bones, teeth, lungs, and chest organs. Impulse noise is one of the major factors that degrade...

The governance of online rumors during major emergencies is essential for maintaining social stability and ensuring a healthy cyberspace. This study develops a tripartite evolutionary game model involving local governmen...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistic...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

Electrochemical potential noise signals from LiFePO4 batteries often contain a slowly varying trend component that overlaps with and distorts the intrinsic low-frequency electrochemical noise. This component must therefo...

Efficient current control in boost converters is critical for electric vehicle (EV) battery charging applications, where dynamic operating conditions challenge conventional control strategies. This paper presents a novel...

Three-phase pulse width modulation (PWM) rectifiers are crucial in industrial, civil, and transportation applications. Due to the diversity of grid loads, the three-phase input voltage may be unbalanced, which consequent...

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework ...

Multimodal remote sensing image registration is a fundamental step for multisource data fusion and geospatial analysis. However, nonlinear radiometric, textural, and geometric discrepancies across modalities challenge in...

Integration of Photovoltaic (PV) generation into oil and gas power networks has transformed fault behaviour by creating highly complex sensitivity challenges for conventional Overcurrent Relay (OCR) coordination and trip...

This study compares seven quantum algorithms—Variational Quantum Eigensolver (VQE), Variational Quantum Deflation (VQD), Quantum Approximate Optimization Algorithm (QAOA), Quantum Amplitude Estimation (QAE), Quant...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

This paper presents an inductorless design methodology for compact single-pole double-throw (SPDT) switches in Sub-6 GHz applications. To achieve compactness and meet key performance metrics below 5.0 GHz, the methodolog...

Driven by satellite remote sensing observations, deep learning models provide a promising solution for the rapid estimation of subsurface thermohaline structures. By learning from large-scale paired surface–subsur...

Timely prediction of Intensive Care Unit (ICU) admission at hospital arrival is critical for clinical decision-making, resource allocation, and patient management, particularly during large-scale health crises such as th...

This study focuses on the explainability of AI operations for diagnosing degradations in cloud applications. Log data can provide essential contextual information on misbehaving applications in monitoring, evaluated agai...

Measurements from global navigation satellite system reflectometry (GNSS-R) have proven effective for applications in sea surface height (SSH). Deep learning-based methods for spaceborne GNSS-R SSH retrieval can effectiv...