112.443 hasil
Menampilkan 1–20 · 0,24 detik · RSS
IEEE Access
Scopus
ISSN 2169-3536 · IEEE · 112.443 artikel di indeks
-
Artikel Jurnal
BMT_EEG: A Novel EEG Dataset for Evaluating the Effects of New Protocols on Biometric Authentication Systems
Due to uniqueness, revocability, and resilience to theft, Electroencephalography (EEG) biometric solutions are becoming more popular for securing high stake systems. To propel research in EEG-based biometrics, we introduced a novel dataset: Biometric EEG Dataset (BMT_EEG), uniquely designed to…
-
Artikel Jurnal
Multi-Layer Knowledge Distillation With Custom Temperature Scaling for Deepfake Detection
The swift emergence of highly convincing deepfakes on social media and digital platforms has posed considerable difficulties to digital security, privacy, and public confidence, as these fabrications are increasingly used for financial deception and social manipulation. The enormous computational…
-
Artikel Jurnal
Design and Experimental Validation of Sensorless 4-Channel Bilateral Teleoperation for Low-Cost Manipulators
Teleoperation of low-cost manipulators is attracting increasing attention as a practical means of collecting demonstration data for imitation learning. However, most existing low-cost systems rely on unilateral position control without force feedback, while implementing force-feedback bilateral…
-
Artikel Jurnal
An Efficient Characteristic Mode Tracking Algorithm Based on Far-Field Correlation and Characteristic Angle Extrapolation
This paper presents a novel and efficient algorithm for tracking characteristic modes across a wide frequency range. Surface current-based tracking algorithms often fail at large frequency steps; therefore, a more physically stable far-field-based method is needed. The proposed method employees…
-
Artikel Jurnal
An Adaptive Multi-Scale Graph and Seasonal Decomposition LSTM Framework for Accurate Wastewater Effluent Forecasting
Predicting effluent indicators is crucial for enabling a wastewater treatment plant (WWTP) to actively adjust treatment processes. However, research on long-term sequence forecasting under sudden water-quality fluctuations remains scarce. In this study, we propose a novel framework called…
-
Artikel Jurnal
A New Thyristor-Based DC Circuit Breaker With an Auxiliary Forced Commutation Branch
The rapid growth of renewable energy harvesting and the integration of renewable energy systems into power systems have significantly increased electricity market attention towards utilizing Direct Current (DC) power systems. The protection of DC systems is still recognized as a challenge to their…
-
Artikel Jurnal
Integrating Machine Learning and Image-Based Damage Quantification to Predict Self-Healing Performance of Asphalt Mixtures
This study presents a machine-learning framework that predicts a fracture-based healing index of asphalt mixtures by explicitly incorporating image-quantified fracture-surface damage modes (adhesive, cohesive, aggregate). Damage types were quantified through digital image processing. Two datasets…
-
Artikel Jurnal
Machine Learning-Based Estimation of Photovoltaic Solar Power Generation Under Heatwave Events in the Context of Climate Change in Santo André, São Paulo, Brazil
Climate change is intensifying extreme temperature events, especially heatwaves, which affect both energy demand and the performance of photovoltaic systems in the metropolitan region of São Paulo, particularly in the municipality of Santo André. The central problem lies in the difficulty of…
-
Artikel Jurnal
SCMIT: Style-Consistent Multi-Domain Image-to-Image Translation
Multi-domain image-to-image translation has become increasingly prominent in computer vision, addressing the demand for versatile models that can transform images across various domains. However, current image-to-image translation methods are often limited to transforming images between specific…
-
Artikel Jurnal
SCF-Net: A Lightweight Multi-Granular Feature Fusion Network for IoT Anomaly Detection
With the exponential growth in Internet of Things (IoT) deployments, the attack surface for modern networks has dramatically increased, making it essential to have an effective, scalable and resource-efficient solution that is capable of detecting anomalies. On the other hand, deep learning-based…
-
Artikel Jurnal
Data-Driven Aggregation Model of Type-III Wind Farms for Power System Transient Characteristic Simulation
The transient characteristics of large-scale Type-III wind farms (WFs) exhibit high complexity and weak interpretability. To analyze their dynamic response behavior, this paper proposes a two-stage reduced-order modeling method that comprehensively incorporates factors, such as wind speed and…
-
Artikel Jurnal
Elastic Cloud Scaling for Small Models: Dynamic Resource Allocation as an Alternative to Training Large LLMs
Large language models (LLMs) have driven significant advances in natural language processing, but their static deployment for high-throughput inference often leads to high computational cost and latency. For moderate-complexity, high-volume workloads, smaller language models (SLMs) can provide…
-
Artikel Jurnal
Effective Encoder-Decoder Network for Multiple Multi-Scale Jagged Masks in Vehicle Damage Segmentation
The segmentation of damaged areas in vehicle images is essential for practical applications such as automated insurance processing, vehicle resale evaluation, and maintenance support. Damage patterns often appear in different forms and sizes, and exhibit irregular shapes, which makes consistent…
-
Artikel Jurnal
A New Touchscreen Cover for Braille-Based Data Entry on Mobile Devices
The emerging advances in mobile technology, along with the anticipated global increase in the blind and low-vision population, emphasize the importance of introducing this community to such technology as an effective and low-cost communication tool. Aiming to enable blind and deaf-blind individuals…
-
Artikel Jurnal
Impact of Integer Quantization on Polar-Coding Over 4096-QAM OFDM Systems
Polar codes are fundamental to the control channels of fifth-generation (5G) systems. Owing to their excellent block error rate (BLER) performance, polar coding is considered a strong candidate for sixth-generation (6G) networks. In scenarios where both computational complexity and ultra-high data…
-
Artikel Jurnal
RLQO: Reinforcement Learning-Based AQM for Fluctuating mmWave RAN Links in 5G-A/6G
The instability of millimeter wave links in 5G-Advanced and 6G networks creates rapid channel fluctuations that traditional Active Queue Management mechanisms struggle to manage, leading to degraded network performance. To address this, we propose the Reinforcement Learning Queuing Optimizer…
-
Artikel Jurnal
Designing an OCR-Based Medication Support System With Drug–Drug Interaction Alerts for Elderly
Medication adherence and safety remain major healthcare challenges for elderly populations, particularly within Arabic-speaking communities. Managing multiple prescriptions (polypharmacy) increases the risk of medication errors and adverse drug–drug interactions (DDIs), challenges that are further…
-
Artikel Jurnal
Multimodal Analysis for Depression Recognition Using Stacked Multilevel Deep Neural Networks
Depression is a severe mental disorder that is associated with a persistent state of sadness, anhedonia, and psychosocial dysfunction. In its most severe form, it may culminate in suicidal ideation and behavior. Early diagnosis is crucial to attenuate adverse clinical outcomes. In this regard…
-
Artikel Jurnal
Deep Learning for Bluetooth Low Energy Indoor Positioning: A Comparative Analysis of Fingerprinting Accuracy and Generalization to Unseen Locations
Indoor positioning remains an important challenge in ubiquitous computing, particularly when balancing cost, accuracy, and adaptability. This work evaluates deterministic, probabilistic, classification, and regression models for indoor localization using a low-cost Bluetooth Low Energy (BLE) mesh…
-
Artikel Jurnal
Standardized ML and XAI Workflow for Presence-Only Species Distribution Modeling: A Case Study in the Amazon
The convergence of Machine Learning (ML) and ecology has provided powerful tools for Species Distribution Modeling (SDM). However, the application of complex algorithms to presence-only data often lacks methodological standardization and interpretability. This study proposes a comprehensive and…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.