“bandwidth”的搜索结果

Use when a task needs the judgment of an Electrical and Electronic Engineering Technologist/Technician — bench-testing a prototype board against a power or timing spec, isolating a resistive fault in a power path with node-to-node voltage-drop measurements, checking whether an oscilloscope's own bandwidth is limiting a rise-time measurement before trusting it, running a power-supply load-regulation sweep, or evaluating ESD-event provenance and IPC-A-610 acceptance on a returned unit.

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Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.

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Annotate speech/TTS datasets with per-clip quality metrics (MOS, SNR, STOI, pitch, bandwidth, speaking rate, WER/CER, gender/emotion), multi-ASR consensus transcription and speaker labeling using the audiogear pipeline; then filter clips by quality and build listenable HTML QA reports. Use when asked to compute audio dataset metrics, build extended_metadata.csv, transcribe unlabeled audio, select clean TTS training data, or QA a speech dataset.

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Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

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Use when working with Cloudflare Cdn — cloudflare CDN management including zone configuration, cache purging, page rules, firewall rules, SSL/TLS settings, and performance optimization. Covers cache analytics, bandwidth usage, threat detection, and edge certificate management. Use when managing Cloudflare CDN zones, analyzing cache performance, configuring page rules, or troubleshooting delivery issues.

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Use when working with Bunny Cdn — bunny.net CDN management covering pull zones, storage zones, edge rules, cache configuration, and bandwidth analytics. Use when managing Bunny CDN pull zones, analyzing traffic patterns, configuring edge rules, monitoring cache hit ratios, or managing Bunny storage for origin content.

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Use when working with Aws Transit Gateway — aWS Transit Gateway attachment analysis, route table management, peering configuration, and network topology review. Covers TGW inventory, attachment health, route propagation, VPN connection status, and bandwidth utilization.

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Tell the user (or an agent) exactly what machine they are on — chip, cores, RAM, NPU TOPS, memory bandwidth, security posture, DSH tier, and the right Ollama model to pull. Refreshes the canonical profile at agents/core/.mesh/machine.json on every call. Reads the result via agents.core.machine — zero re-probing in application code.

中文简介正在准备中。当前显示原文说明。

Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.

中文简介正在准备中。当前显示原文说明。

Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.

中文简介正在准备中。当前显示原文说明。

Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.

中文简介正在准备中。当前显示原文说明。