「hsi」の検索結果

Knowledge base from NASA Human Systems Integration (HSI) Practitioner's Guide (NASA/SP-2015-3709). Use for HSI process implementation, lifecycle phase activities, function allocation, ConOps development, HSI Plan writing, HSI metrics (MOE/MOP/TPM/KPP), HITL testing strategy, HSI team organisation, scaling/tailoring for program size, and V&V planning. Does not cover the specific human engineering design standards (NASA-STD-3001 content) or detailed HFE methods beyond what the guide itself provides.

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Set up the Graphsignal Profiler for inference workloads — vLLM, SGLang, PyTorch, and dstack services. Use when the user wants GPU profiling, tracing, or monitoring for inference, asks about `graphsignal-run` or `graphsignal.watch()`, or asks about CUPTI / Prometheus / OTLP setup.

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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.

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用于将图像像素在RGB、HSV或HSI颜色空间中进行三维散点图可视化。核心逻辑是将色调(H)映射为角度，饱和度(S)映射为半径，亮度(I/V)映射为高度，从而在圆柱体或圆锥体中显示像素分布，并支持在RGB空间添加对角线。

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用于将图像像素在RGB、HSV或HSI颜色空间中进行三维散点图可视化。核心逻辑是将色调(H)映射为角度，饱和度(S)映射为半径，亮度(I/V)映射为高度，从而在圆柱体或圆锥体中显示像素分布，并支持在RGB空间添加对角线。

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Acts as a director and previs supervisor for film, video, and AI filmmaking. Turns scripts, prose, briefs, or existing image and video assets into production deliverables — subtext breakdown, beat sheet, director's book, blocking and staging, shot list with coverage, keyframe and storyboard prompts, image-to-video motion prompts, sound and dialogue plans, edit timelines, continuity bibles, and QC repair notes. Carries genre playbooks, a controlled prompt lexicon, a coded failure-diagnosis manual, and capability-first adapters for current video and image models. Optionally applies one named director's style lens — Spielberg, Hitchcock, Kubrick, Kurosawa, Scorsese, Fellini, Bergman, Tarkovsky, Wong Kar-wai, Nolan, Villeneuve, Fincher, Refn, Bi Gan, Zhang Yimou, Hou Hsiao-hsien, Park Chan-wook, Malick, Michael Mann, Coen Brothers. Use for shot planning, blocking, staging, camera movement, visual continuity, storyboard and keyframe design, prompt repair, "in the style of X" direction, and any AI video workflow.

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HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data generation.

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HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data generation.

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HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data generation.

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Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, batch processing, or scheduled tasks. Always consult this skill when the user asks to create, build, or design an n8n workflow, automate a process, or connect services — even if they don't explicitly mention 'patterns'. Covers webhook, API, database, AI, batch processing, and scheduled automation architectures. Also use when optimizing a slow workflow or speeding up large-item-count processing (node count, batchSize, all-items vs per-item).

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Create a dark container-led technical design system with fuchsia-purple accents, layered rounded shells, crisp frame lines, and playful futuristic focal objects.

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Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, batch processing, or scheduled tasks. Always consult this skill when the user asks to create, build, or design an n8n workflow, automate a process, or connect services — even if they don't explicitly mention 'patterns'. Covers webhook, API, database, AI, batch processing, and scheduled automation architectures. Also use when optimizing a slow workflow or speeding up large-item-count processing (node count, batchSize, all-items vs per-item).

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Implement or review a single-index Algolia search contract with filters, facets, pagination, and highlighting. Use when building product or content search against the JavaScript v5 client. Trigger with "Algolia search workflow", "add facets", or "searchSingleIndex".

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Use this skill to run multiple Simulink simulations in parallel with parsim, batchsim, and DesignStudy. TRIGGER when: user asks for parameter sweep, sweeping/varying parameters across simulations, Monte Carlo study, batch simulation, running multiple simulations, parallel simulations, large-scale multiple simulations, any task involving repeated simulations with different parameter values, user mentions having an existing script/function for parameter sweeps, or user wants to migrate from parfor/set_param/for-loop patterns to recommended workflows.

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Render Obsidian-style weighted graph views from book JSON, keyword indexes, TOCs, card data, or node-link data. Use when the user asks for Obsidian graph view, graph view png, weighted graph, keyword graph, directory-keyword graph, spherical graph visualization, or high-weight nodes centered with clear Chinese labels.

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Convert Chinese or mixed-language text, iMandalArt cards, Obsidian 九宮, 表格, Mandala notes, or eight-domain outlines into a Markdown 3x3 nine-grid table with an ◎ center, then copy, save, append, or hand it to apps that render Markdown tables such as Obsidian and AIDA. Use when the user asks for Markdown 九宮格, Obsidian 九宮, Markdown table 九宮, 曼陀羅表格, nine-grid clipboard, AIDA table output, or conversion between Markdown 九宮, iMandalArt, and 81-grid workflows.

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Extract exactly 8 context-sensitive keywords from Chinese, English, or mixed text and turn them into a distributed weighted Graph View with no center goal node. Use when Codex needs keyword extraction, blacklist filtering, co-occurrence edges, node definitions/notes, weighted graph JSON, or an online Graph View tool for text analysis.

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Create narrow iMessage/PTT Border-Light HyperCard style nine-grid cards in Chinese or mixed Chinese-English. Use when the user says "iMessage 九宮 HyperCard", "iMessage 九宮", "做成 iMessage 九宮", "用 iMessage 九宮 HyperCard 整理", asks for a phone-readable short card with Context below, or wants Mandala/九宮/HyperCard content formatted for blue-bubble/iMessage sharing with long links, paths, and rules moved out of the card.

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Create iMandalArt 2.2 pure-text 3x3 Mandala index cards with a five-character center axis, eight orthogonal surrounding angles labeled Ⓐ-Ⓗ, compact title cells such as Ⓐ健康復節, hard-line CJK layout, optional の字型 ordering, and 井字號 compass ordering. Use when the user asks for iMandalArt, iMandalart, I MandalArt, の字型, ◊字型, 井字號, 中國城市方位, 64＋8＋1, 手機方形曼陀羅, 正方形九宮索引卡, 五字定格, ◎中心, Ⓐ-Ⓗ 九宮卡, TheBrain/Cerebro preview-safe hard-line cards, or a square 3x3 card that is not a Markdown table, visible-border PE2 card, or 81-cell Mandala.

Convert FIRE analysis cards, Chinese knowledge notes, or project-note JSON into validated EPUB books with directory cards, chapter cards, keyword index cards, backlinks, and GitHub-shareable ebook assets. Use when Codex needs to teach or automate the path from `fire-analysis-card` outputs to `project-note-json-to-epub` style EPUB files, including sample JSON manuscripts and attached `.epub` deliverables.

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Analyze Chinese notes, articles, manuscripts, and digital card-box material with FIRE 2.0: Full-D numbering, Index keyword webs, Route thinking paths, and Evolution over time. Use when Codex needs to prepare material for semantic search, turn temporary notes into permanent or project notes, build table-of-contents/index/search structures, create compact Chinese FIRE cards, or maintain this skill's original discussion thread provenance.

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Convert structured project-note JSON manuscripts into validated EPUB and optional Kindle-clickable PDF files. Use when the user asks to turn project notes, book-system JSON, FIRE-indexed notes, Luhmann/Zettelkasten numbered chunks, table-of-contents cards, index cards, cross-linked project notes, or manuscript JSON into an EPUB/PDF with chapter directories, keyword index cards, weighted links, bidirectional backlinks, versioned filenames, chapter-splitting plans, and full link testing.

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Use BIRD Book Deconstructor 2.2 to apply the formal BIRD 2.1 Knowledge Address protocol to complex manuscript text and TheBrain Thoughts. Use when splitting books into chapter/section/item knowledge nodes, assigning Book Address, structured Knowledge Index (Weight, Type, Keyword, Alias), Routes, verified Deep Links, and Semantic Roles; producing BIRD Excel workbooks, TheBrain scaffolds, Roam JSON, monochrome printable double nine-grid cards, or a routed handoff from iMandalArt to A4 eight-page booklets; or auditing and migrating existing BIRD/TheBrain indexes.

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Write spoken daily planning notes into an Obsidian Mandala Grid day-plan Markdown file. Use when the user says 今日的日計畫, 今日的日計劃, 日計畫, 日計劃, 青蛙, frog, 🐸, 九宮, 曼陀羅, Mandala Grid, 時段, time block, 日記, or asks to place spoken tasks/events/reflections into today's Obsidian daily plan sections.

日本語の概要は準備中です。原文の説明を表示しています。