Sliding window protocol
View article: Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits
Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits Open
This report presents a complete operational optimization of weak measurement for superconducting transmon qubits, with specific applicability to the Google Sycamore (2021) platform. The analysis identifies a robust sweet-spot window for re…
View article: Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits
Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits Open
This report presents a complete operational optimization of weak measurement for superconducting transmon qubits, with specific applicability to the Google Sycamore (2021) platform. The analysis identifies a robust sweet-spot window for re…
View article: An Adjustable Smart Ring to Monitor Pulse Rate and Peripheral Blood Oxygen Saturation
An Adjustable Smart Ring to Monitor Pulse Rate and Peripheral Blood Oxygen Saturation Open
Purpose Smart rings are emerging as a promising solution in the field of wearable devices, offering a compact and ergonomic solution for continuous physiological monitoring, yet one of their major limitations is that they are not adjustabl…
View article: Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits
Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits Open
This report presents a complete operational optimization of weak measurement for superconducting transmon qubits, with specific applicability to the Google Sycamore (2021) platform. The analysis identifies a robust sweet-spot window for re…
View article: Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits
Weak-Measurement Optimization for Google Sycamore (2021): Operational Sweet-Spot Window for Repetitive Readout in Driven Transmon Qubits Open
This report presents a complete operational optimization of weak measurement for superconducting transmon qubits, with specific applicability to the Google Sycamore (2021) platform. The analysis identifies a robust sweet-spot window for re…
View article: GatedFWA: Linear Flash Windowed Attention with Gated Associative Memory
GatedFWA: Linear Flash Windowed Attention with Gated Associative Memory Open
Modern autoregressive models rely on attention, yet the Softmax full attention in Transformers scales quadratically with sequence length. Sliding Window Attention (SWA) achieves linear-time encoding/decoding by constraining the attention p…
View article: GatedFWA: Linear Flash Windowed Attention with Gated Associative Memory
GatedFWA: Linear Flash Windowed Attention with Gated Associative Memory Open
Modern autoregressive models rely on attention, yet the Softmax full attention in Transformers scales quadratically with sequence length. Sliding Window Attention (SWA) achieves linear-time encoding/decoding by constraining the attention p…
View article: Research on deformation characteristics and mechanisms of an open pit coal mine landslide event in extremely cold region
Research on deformation characteristics and mechanisms of an open pit coal mine landslide event in extremely cold region Open
For the sake of heavy rainfall, a landslide occurred at the Baorixile open-pit coal mine, at 13:40 (Beijing time, UTC + 8) on April 30, 2020, in China. The landslide event was about 130 × 10 5 m 3 and produced considerable damage in additi…
View article: Enhancing Small Object Detection with YOLO: A Novel Framework for Improved Accuracy and Efficiency
Enhancing Small Object Detection with YOLO: A Novel Framework for Improved Accuracy and Efficiency Open
This paper investigates and develops methods for detecting small objects in large-scale aerial images. Current approaches for detecting small objects in aerial images often involve image cropping and modifications to detector network archi…
View article: Enhancing Small Object Detection with YOLO: A Novel Framework for Improved Accuracy and Efficiency
Enhancing Small Object Detection with YOLO: A Novel Framework for Improved Accuracy and Efficiency Open
This paper investigates and develops methods for detecting small objects in large-scale aerial images. Current approaches for detecting small objects in aerial images often involve image cropping and modifications to detector network archi…
View article: Tropical Cyclone Track Prediction in the TCWC Indonesia Monitoring Area Using Deep Recurrent Neural Networks
Tropical Cyclone Track Prediction in the TCWC Indonesia Monitoring Area Using Deep Recurrent Neural Networks Open
Tropical Cyclones (TCs) are rapidly rotating large-scale storm systems and rank as the second most destructive natural hazards after earthquakes. Disaster mitigation in TC-prone regions is critical, particularly in view of the two-fold inc…
View article: Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event Retrieval
Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event Retrieval Open
Multimedia information retrieval from videos remains a challenging problem. While recent systems have advanced multimodal search through semantic, object, and OCR queries - and can retrieve temporally consecutive scenes - they often rely o…
View article: Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event Retrieval
Enhanced Multimodal Video Retrieval System: Integrating Query Expansion and Cross-modal Temporal Event Retrieval Open
Multimedia information retrieval from videos remains a challenging problem. While recent systems have advanced multimodal search through semantic, object, and OCR queries - and can retrieve temporally consecutive scenes - they often rely o…
View article: Nucleotide diversity (Pi) analysis of chloroplast genomes in <i>Polygonatum</i> species with 600 bp sliding window length and 200 bp step size.
Nucleotide diversity (Pi) analysis of chloroplast genomes in <i>Polygonatum</i> species with 600 bp sliding window length and 200 bp step size. Open
Nucleotide diversity (Pi) analysis of chloroplast genomes in Polygonatum species with 600 bp sliding window length and 200 bp step size.
View article: Quantifying Memory Use in Reinforcement Learning with Temporal Range
Quantifying Memory Use in Reinforcement Learning with Temporal Range Open
How much does a trained RL policy actually use its past observations? We propose \emph{Temporal Range}, a model-agnostic metric that treats first-order sensitivities of multiple vector outputs across a temporal window to the input sequence…
View article: MakieOrg/Makie.jl: v0.24.8
MakieOrg/Makie.jl: v0.24.8 Open
Makie v0.24.8 Diff since v0.24.7 Merged pull requests: support RichText concatenation (#5221) (@aplavin) CairoMakie: make poly respect linecap, joinstyle and miter_limit (#5415) (@manuelbb-upb) Reexport GridLayoutBase.Protrusion, to be use…
View article: Quantifying Memory Use in Reinforcement Learning with Temporal Range
Quantifying Memory Use in Reinforcement Learning with Temporal Range Open
How much does a trained RL policy actually use its past observations? We propose \emph{Temporal Range}, a model-agnostic metric that treats first-order sensitivities of multiple vector outputs across a temporal window to the input sequence…
View article: Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation
Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation Open
Efficient streaming video generation is critical for simulating interactive and dynamic worlds. Existing methods distill few-step video diffusion models with sliding window attention, using initial frames as sink tokens to maintain attenti…
View article: Dynamic Semantic Chunking for Optimal Context Window Utilization in Large Language Models
Dynamic Semantic Chunking for Optimal Context Window Utilization in Large Language Models Open
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. However, their performance is often constrained by the fixed-size context window, which limits the amount of i…
View article: Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes
Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes Open
We study the structural changes in multivariate time-series by estimating and comparing stationary graphs for macroeconomic time series before and after an economic crisis such as the Great Recession. Building on a latent time series frame…
View article: Dynamic Semantic Chunking for Optimal Context Window Utilization in Large Language Models
Dynamic Semantic Chunking for Optimal Context Window Utilization in Large Language Models Open
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. However, their performance is often constrained by the fixed-size context window, which limits the amount of i…
View article: Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation
Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation Open
Efficient streaming video generation is critical for simulating interactive and dynamic worlds. Existing methods distill few-step video diffusion models with sliding window attention, using initial frames as sink tokens to maintain attenti…
View article: Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes
Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes Open
We study the structural changes in multivariate time-series by estimating and comparing stationary graphs for macroeconomic time series before and after an economic crisis such as the Great Recession. Building on a latent time series frame…
View article: Accompanying data for "A Multilevel statistical process control chart framework for personalized patient monitoring: A simulation study using patients historical data"
Accompanying data for "A Multilevel statistical process control chart framework for personalized patient monitoring: A simulation study using patients historical data" Open
Statistical Process Control (SPC) charts offer a potentially effective means of continuously monitoring patient time-series data to enable the early detection ofclinical abnormalities. A significant challenge in implementing SPC methods, s…
View article: Lightweight Attention-Augmented YOLOv5s for Accurate and Real-Time Fall Detection in Elderly Care Environments
Lightweight Attention-Augmented YOLOv5s for Accurate and Real-Time Fall Detection in Elderly Care Environments Open
Falls among the elderly represent a leading cause of injury and mortality worldwide, necessitating reliable and real-time monitoring solutions. This study aims to develop a lightweight, accurate, and efficient fall detection framework base…
View article: Accompanying data for "A Multilevel statistical process control chart framework for personalized patient monitoring: A simulation study using patients historical data"
Accompanying data for "A Multilevel statistical process control chart framework for personalized patient monitoring: A simulation study using patients historical data" Open
Statistical Process Control (SPC) charts offer a potentially effective means of continuously monitoring patient time-series data to enable the early detection ofclinical abnormalities. A significant challenge in implementing SPC methods, s…
View article: Dissonance-Weighted Eviction: A Hybrid LRU Protocol for Long-Horizon Agent Memory
Dissonance-Weighted Eviction: A Hybrid LRU Protocol for Long-Horizon Agent Memory Open
System: LID-LIFT Orchestrator v1.4Series: Part 3 of the LID-LIFT Technical SuiteAbstract:Long-horizon autonomous agents suffer from 'context drift'—the accumulation of contradictory or obsolete information within the sliding context window…
View article: Dissonance-Weighted Eviction: A Hybrid LRU Protocol for Long-Horizon Agent Memory
Dissonance-Weighted Eviction: A Hybrid LRU Protocol for Long-Horizon Agent Memory Open
System: LID-LIFT Orchestrator v1.4Series: Part 3 of the LID-LIFT Technical SuiteAbstract:Long-horizon autonomous agents suffer from 'context drift'—the accumulation of contradictory or obsolete information within the sliding context window…
View article: CNT Hazard Probe v1: Synthetic Accelerator Hazard Memory
CNT Hazard Probe v1: Synthetic Accelerator Hazard Memory Open
This record releases CNT Hazard Probe v1, a reusable hazard–memory analysis pipeline applied here to a synthetic accelerator-like system with beam-dump–style events. It is part of the ongoing development of Cognitive Nexus Theory (CNT), wh…
View article: CNT Hazard Probe v1: Synthetic Accelerator Hazard Memory
CNT Hazard Probe v1: Synthetic Accelerator Hazard Memory Open
This record releases CNT Hazard Probe v1, a reusable hazard–memory analysis pipeline applied here to a synthetic accelerator-like system with beam-dump–style events. It is part of the ongoing development of Cognitive Nexus Theory (CNT), wh…