'linear' 검색 결과

Write an evidence-based status update from Linear data - summarize what shipped, what is in progress, what is blocked or stale for a project, cycle, or a person's issues, and optionally post it as a Linear project status update after the user approves the text. Use for "status for project X", "weekly update", "what moved this cycle".

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Linear: manage issues, projects, teams via GraphQL + curl.

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RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

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Solve partial differential equations — finite differences, spectral methods, and physics-informed neural networks (PINNs via DeepXDE). Supports 1D/2D/3D, steady/transient, linear/nonlinear PDEs with Dirichlet, Neumann, and periodic boundary conditions.

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Analyze nonlinear dynamical systems — phase portraits, fixed points, stability analysis, bifurcation diagrams, Poincare sections, Lyapunov exponents, and chaos detection. Use for any autonomous or non-autonomous ODE system where qualitative behavior matters.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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Manage Linear issues, projects, and teams via the GraphQL API. Create, update, search, and organize issues. Uses API key auth (no OAuth needed). All operations via curl — no dependencies.

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Mirror issues and status across issue trackers with stable external-ID mapping to avoid duplicates. Load when syncing GitHub and Linear issues, mirroring ticket status, or keeping two trackers in sync. Also triggers on "issue sync", "sync issues", "mirror issues to", "keep Linear and GitHub in sync", or bidirectional issue tracker updates. Requires API access on both sides — stops if credentials missing.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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When the user wants to cut 1D materials optimally, minimize waste in linear cutting, or solve one-dimensional cutting stock problems. Also use when the user mentions "1D cutting," "linear cutting optimization," "rod cutting," "pipe cutting," "beam cutting," "trim loss," "cutting stock problem," "pattern generation," or "column generation for cutting." For 2D problems, see 2d-cutting-stock. For general trim loss, see trim-loss-minimization.

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Query and manage Linear issues, projects, and team workflows.

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Create HTML slide decks for humanities lectures and research presentations, organizing sources, arguments, and evidence. A coordinated navy and warm-yellow template gives the slides a calm, scholarly appearance.

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• Preparing slides for a humanities lecture
• Presenting research in a graduate seminar
• Turning a research synthesis into a scholarly deck

Analyze application and system performance to find bottlenecks, the points that slow processing. Use resource usage and performance data to plan improvements to resource allocation, load balancing, caching, and algorithms, then compare results after changes.

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• Investigating slow application processing
• Reviewing CPU and memory allocation
• Improving workload distribution across nodes

Analyze networks of people, web pages, or systems using PageRank, a method that scores importance from connections. Identify influential nodes and communities, generate personalized recommendations, and examine communication bottlenecks to guide network improvements.

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• Finding influential users and communities on social networks
• Analyzing links and page importance on a website
• Generating recommendations based on user preferences

Design and implement ways for multiple agents or distributed computers to agree on decisions. Covers weighted voting, task allocation, coordination, and protocols that handle faulty or malicious participants, with tools for mathematical analysis.

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• Design agreement protocols for multiple agents
• Build voting systems with weighted influence
• Review protocols for faulty or malicious nodes

Turn complex goals into actionable plans by mapping dependencies, prioritizing tasks, and allocating time, budget, and people. Supports coordination across multiple agents and revises plans when progress or constraints change.

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• Planning a feature launch under a deadline
• Allocating people and budget across competing goals
• Revising plans when requirements change

Reduce data with many features into fewer dimensions using UMAP. Create 2D or 3D views, prepare inputs for clustering, compare parameter settings, and project new samples while checking whether the results remain stable and meaningful.

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• Visualizing data with many features in 2D or 3D
• Preparing reduced features for HDBSCAN clustering
• Guiding dimensionality reduction with partial labels

Use SymPy to simplify expressions, solve equations, and calculate derivatives, integrals, and matrices with exact symbolic results. Specify assumptions, verify solutions, and turn mathematical expressions into numerical functions, source code, or LaTeX output.

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• Solving equations and checking their solutions
• Calculating symbolic derivatives, integrals, and limits
• Finding matrix eigenvalues with exact arithmetic

Plan and document studies that assess whether an analytical procedure suits its intended use. Select the governing framework, evaluate calibration, accuracy, precision, and detection limits, and compare methods using acceptance criteria defined before data collection.

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• Planning analytical validation studies and acceptance criteria
• Evaluating calibration, accuracy, and precision
• Estimating and confirming detection and quantitation limits

Design and build an OpenMAIC lesson series using a spiral curriculum: core ideas return with deeper explanations, new representations, and unfamiliar applications. It maps conceptual growth across lessons and checks that revisits add understanding.

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• Designing a Bruner-style spiral curriculum
• Moving from concrete examples to general models across lessons
• Revisiting concepts through unfamiliar applications and counterexamples

Calculate how to divide serving memory between recurrent state and KV cache, two memory pools used by hybrid models. Use startup logs and workload settings to recommend a ratio, estimate concurrency, and identify the limiting pool.

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• Choosing a memory ratio for a hybrid model
• Investigating limits on concurrent requests
• Recalculating memory allocation for context length

Analyze scheduled token releases, their recipients, and trading volume to estimate potential selling pressure. Review project treasury holdings, operating runway, and token supply growth to assess funding sustainability and the effect of dilution on staking yields.

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• Reviewing token releases scheduled for the next 90 days
• Estimating selling pressure relative to trading volume
• Assessing treasury diversification and funding runway

Model trading costs and execution assumptions in backtests, including slippage, the gap between expected and simulated fill prices. Compare price impact, fees, execution delays, and order splitting to assess how assumptions affect strategy results.

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• Compare backtests under different slippage assumptions
• Estimate how trading costs reduce annual returns
• Explore VWAP and TWAP order splitting

Develop an eight-part article series examining one company's competitive strengths, earnings, assets, management, and valuation. Review figures, sources, accounting definitions, and claims across the series to prepare consistent articles for public publication.

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• Planning an eight-part company analysis series
• Checking figures and definitions across articles
• Revising unsupported claims before publication