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Adaptive Incremental Provenance Analysis for Trustworthy Federated Learning
No full textAdaptive Incremental Provenance Analysis for Trustworthy Federated Learnin
USING neural networks and CEO remuneration to predict the debt-income ratio of New Zealand local councils
No full textUSING neural networks and CEO remuneration to predict the debt-income ratio of New Zealand local council
The parental self-efficacy to respond to school refusal scale: Development and validation
No full textThe parental self-efficacy to respond to school refusal scale: Development and validatio
Exploring the Sentencing Offenders with Mental Disorders, Developmental Disorders, or Neurological Impairments Guideline in England and Wales: A Case Study Analysis
No full textExploring the Sentencing Offenders with Mental Disorders, Developmental Disorders, or Neurological Impairments Guideline in England and Wales: A Case Study Analysi
TGSAM-2: Text-Guided Medical Image Segmentation Using Segment Anything Model 2
No full textTGSAM-2: Text-Guided Medical Image Segmentation Using Segment Anything Model 2</p
Achieving near-isotropic strength and ductility in laser additively manufactured zinc via columnar-to-equiaxed grain transition under thermoelectric magnetic effect
No full textAchieving near-isotropic strength and ductility in laser additively manufactured zinc via columnar-to-equiaxed grain transition under thermoelectric magnetic effect</p
INTERNET VULGARITIES IN CHINA Cultures, Governance and Politics
No full textThis book utilizes empirically rich case studies explore the nature, regulation and evolution of internet cultural products, vernacular internet cultures and subcultural online communities which have been deemed 'vulgar' by the Chinese ..
A Lightweight LSTM Model for Flight Trajectory Prediction in Autonomous UAVs
No full textAutonomous Unmanned Aerial Vehicles (UAVs) are widely used in smart agriculture, logistics, and warehouse management, where precise trajectory prediction is important for safety and efficiency. Traditional approaches require complex physical modeling including mass properties, moment of inertia measurements, and aerodynamic coefficient calculations, which creates significant barriers for custom-built UAVs. Existing trajectory prediction methods are primarily designed for motion forecasting from dense historical observations, which are unsuitable for scenarios lacking historical data (e.g., takeoff phases) or requiring trajectory generation from sparse waypoint specifications (4–6 constraint points). This distinction necessitates architectural designs optimized for spatial interpolation rather than temporal extrapolation. To address these limitations, we present a segmented LSTM framework for complete autonomous flight trajectory prediction. Given target waypoints, our architecture decomposes flight operations, predicts different maneuver types, and outputs the complete trajectory, demonstrating new possibilities for mission-level trajectory planning in autonomous UAV systems. The system consists of a global duration predictor (0.124 MB) and five segment-specific trajectory generators (∼1.17 MB each), with a total size of 5.98 MB and can be deployed in various edge devices. Validated on real Crazyflie 2.1 data, our framework demonstrates high accuracy and provides reliable arrival time predictions, with an Average Displacement Error ranging from 0.0252 m to 0.1136 m. This data-driven approach avoids complex parameter configuration requirements, supports lightweight deployment in edge computing environments, and provides an effective solution for multi-UAV coordination and mission planning applications
EdgeDup: Popularity-aware Communication-efficient Decentralized Edge Data Deduplication
No full textEdgeDup: Popularity-aware Communication-efficient Decentralized Edge Data Deduplicatio
The Psychology of Eyewitness Identification: Exploring the Relationship Between Traditional and Alternative Approaches to Recognition
No full textThe Psychology of Eyewitness Identification: Exploring the Relationship Between Traditional and Alternative Approaches to Recognitio