'tip' 검색 결과

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert multiplayer for desync, rollback, dedicated --headless servers, interest culling, and bandwidth spikes: ENet/WebRTC choice, authority, secure RPCs, client prediction/reconcile, and adaptive sync. Trigger on rubber-banding, cheat-able clients, peer floods, late join, or profiler Network spikes — not only greenfield online games. Keywords: multiplayer, RPC, ENetMultiplayerPeer, MultiplayerSynchronizer, authority, client prediction, rollback, interest management, headless, desync.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert multiplayer for desync, rollback, dedicated --headless servers, interest culling, and bandwidth spikes: ENet/WebRTC choice, authority, secure RPCs, client prediction/reconcile, and adaptive sync. Trigger on rubber-banding, cheat-able clients, peer floods, late join, or profiler Network spikes — not only greenfield online games. Keywords: multiplayer, RPC, ENetMultiplayerPeer, MultiplayerSynchronizer, authority, client prediction, rollback, interest management, headless, desync.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Load this skill whenever the project contains tooltip components, hover- triggered informational popups, title attribute tooltips, or any content revealed on hover or focus. Under no circumstances create tooltips that are only triggered by hover without keyboard equivalent access. Absolutely always ensure tooltips are dismissible, persistent enough to read, and not the sole source of essential information.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent fallback for C_MultiplayRules_vtable (auto-generated, category: func). Locate C_MultiplayRules_vtable in the CS2 client module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: C_MultiplayRules_vtable, C_MultiplayRules_vtable

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Android와 KMP 프로젝트의 모듈 구조와 의존 관계를 정리합니다. 업무 로직·화면·데이터 접근을 분리해 설계하고 구현 예시로 각 계층의 역할을 설명합니다.

• Android와 KMP 프로젝트 구조 설계
• 화면 코드에서 업무 로직 분리
• 기기와 서버의 데이터 접근 설계

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing risky permissions identified in BloodHound
• Validating account takeover without resetting a password
• Generating directory change records during security exercises

Adapt machine learning training to run across multiple GPUs or machines with Ray Train. Covers changes to existing code, comparing training settings with Ray Tune, and saving checkpoints so training can resume after failures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adapting existing PyTorch code for multiple GPUs
• Training HuggingFace models across multiple machines
• Comparing learning rates and batch sizes with Ray Tune

Helps adapt machine learning training to multiple GPUs and machines with Ray Train. Covers resource allocation, recovery from saved training states, and Ray Tune searches that compare settings such as learning rate and batch size.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adapt existing PyTorch training to multiple GPUs
• Run HuggingFace training across multiple machines
• Compare learning rates and batch sizes with Ray Tune

Build game systems in Unity or Unreal Engine, including physics, AI, and multiplayer networking. The skill guides architecture, implementation, profiling, and testing to work toward frame rate targets and reduce memory use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing game mechanics in Unity or Unreal Engine
• Reducing frame drops and memory use
• Building multiplayer networking with lag compensation

Coordinate multiple AI agents by assigning tasks, tracking dependencies, exchanging messages, and monitoring progress. Separate Git working directories help organize parallel changes, while context checks and snapshots support handoffs and recovery.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Split feature development and testing between agents
• Track task dependencies and team progress
• Check overlapping changes before a handoff

Add multiple blockchain wallets or exchange accounts to TRES Finance. Import wallet details from CSV, Excel, or plain text, check addresses and duplicates, review the proposed entries, and confirm before submitting them together.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Import wallet addresses from CSV or Excel
• Register multiple wallets from plain text
• Check wallet addresses and duplicates before upload

Supports pathology image analysis in Python, from loading whole-slide images to normalizing stain colors, identifying cell nuclei, mapping spatial relationships, and training machine learning models. It also covers multiplex imaging and marker measurements.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preprocessing stained tissue images
• Detecting and segmenting cell nuclei
• Analyzing spatial relationships between cells

Create and customize MATLAB charts and plots. Plot types (line, scatter, bar, histogram, heatmap, surface), axes configuration, annotations, data tips, interactive plots, animation, multiple axes with tiledlayout, colororder, and performance optimization. Works for standalone figures, Live Scripts, and uifigure apps. Use when plotting data, customizing axes, adding annotations or interactivity, animating charts, or arranging multiple axes. Triggers: plot, chart, graph, axes, uiaxes, annotation, data tips, animation, tiledlayout, colororder, heatmap, scatter, figure, visualization, export.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate TipKit infrastructure with inline/popover tips, rules, display frequency, and testing utilities. Use when adding contextual tips or feature discovery to an iOS/macOS app.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Helps coding agents integrate and work with the Tiptap rich text editor. Use when building or modifying a rich text editor with Tiptap, installing Tiptap extensions, or implementing features like collaboration, comments, AI, or document conversion.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expertise in real-time multiplayer networking, lag compensation, and authoritative server architectureUse when "multiplayer game, netcode, client-server game, P2P networking, lag compensation, rollback networking, game server, matchmaking, lobby system, player synchronization, state replication, dedicated server, authoritative server, tick rate, network prediction, interpolation, extrapolation, GGPO, lockstep, real-time multiplayer, networking, multiplayer, gamedev, realtime, client-server, p2p, netcode, synchronization, lag-compensation, matchmaking" mentioned.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create or edit Czech club-member tips in src/jg/coop/data/tips for Discord synchronization. Use for tip content, filenames, headings, emoji identity, symbolic Discord references, voice, or parser compatibility.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

"Apply case study research design (Yin) to investigate how and why questions within real-life contexts using single or multiple case designs and triangulation. Use this skill when the user needs to choose between single and multiple case designs, apply holistic versus embedded units of analysis, triangulate evidence from multiple sources, or when they ask 'how should I structure a case study', 'single or multiple cases', or 'how do I ensure validity in case research'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Unity 6 multiplayer and networking guide. Use when building multiplayer games, working with Netcode for GameObjects, NetworkManager, NetworkObject, NetworkBehaviour, RPCs (ServerRpc, ClientRpc), NetworkVariables, or Unity multiplayer services (Relay, Lobby). Covers client-server architecture, state synchronization, and scene management. Based on Unity 6.3 LTS documentation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.