'systems' 검색 결과

Knowledge base from the DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.

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Knowledge base from MIL-HDBK-516C (Airworthiness Certification Criteria). Use for DoD air-system airworthiness planning: tailoring a certification basis, systems engineering criteria, and domain clusters for structures, flight technology, propulsion/installation, avionics/electrical/E3/diagnostics, computer systems/software, and crew systems (including applicable UAS control-station elements). Qualitative guidance handbook — not raw contractual requirements. Does not replace service airworthiness authority policy, civil FAA certification rules as authorities, or detailed JSSG/MIL performance specs.

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Cognitive Systems Engineering design methodology for joint cognitive systems and human-centered automation

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머신러닝 모델의 운영 적용을 위해 데이터 규격, 재현 가능한 학습, 품질 평가, 배포, 모니터링과 롤백을 정리하고 구현 계획과 검토 항목을 만듭니다.

• 실험 코드를 학습 파이프라인으로 만듭니다
• 모델 공개 전 품질 기준을 정합니다
• 데이터 누출과 전처리 차이를 조사합니다

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Process satellite imagery and map data for geospatial research. Helps align coordinate systems and image grids, calculate vegetation and terrain measures, summarize data by area, and analyze road networks while preserving masks and source information.

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• Align coordinate systems and raster grids
• Calculate vegetation indices from satellite imagery
• Analyze slope and aspect from elevation data

Build AI applications that answer questions using retrieved documents. Covers vector databases, text embeddings that represent meaning as numbers, search strategies, and result reranking to connect language models with external knowledge.

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• Building Q&A systems for internal documents
• Adding domain knowledge to chatbots
• Implementing natural language document search

Plan GDPR data handling for systems processing EU personal data. Review consent, requests from people to access or delete their data, collection limits, retention, encryption, and access controls as part of system design and compliance reviews.

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• Designing systems that process EU personal data
• Reviewing consent forms and purpose-specific choices
• Organizing responses to data access and deletion requests

Combine vector search, which finds similar meanings, with keyword search for exact terms. Design retrieval for search engines and RAG systems that supply reference material to AI, using methods to merge and rerank results.

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• Improving retrieval for RAG systems
• Finding names and codes through exact matching
• Supporting searches with specialized vocabulary

Build or modify content management systems such as WordPress and Shopify. Locate the right theme, extension, editor, or content layer, then make changes that respect platform conventions, media handling, previews, and publishing behavior.

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• Changing CMS themes and templates
• Developing plugins, apps, or modules
• Improving editor forms and previews

Add controls to AI agents that use APIs, databases, and files. Use Python patterns for tool permissions, approval requirements, call limits, suspicious input checks, audit logs, and trust scores that guide delegation between agents.

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• Restrict which tools an agent can call
• Check suspicious inputs before execution
• Require human approval for sensitive operations

Investigate attackers moving between internal systems by correlating login records with network traffic. Supports detection rules, suspicious SMB and RDP activity analysis, and reports showing attack timelines, affected hosts, and monitoring gaps.

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• Investigating attacker movement across internal systems
• Creating rules for suspicious authentication patterns
• Tracing affected hosts after a PsExec alert

Build automated pipelines that collect threat indicators, such as malicious IP addresses and file hashes, from multiple feeds. Standardize formats, remove duplicates, assess confidence, and distribute indicators to security monitoring systems for matching and alerts.

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• Automating threat feed ingestion
• Standardizing and deduplicating threat indicators
• Distributing indicators to multiple monitoring systems

Build incident response dashboards that bring affected systems, containment progress, indicators of compromise, and response timelines into one view. Help security teams coordinate active incidents and prepare operational reports and executive briefings.

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• Coordinating an active security incident
• Tracking affected systems and containment
• Reviewing response timelines after an incident

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

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• Define the assessment scope for systems handling controlled information
• Calculate an SPRS score and prioritize unmet security requirements
• Prepare security plans, remediation milestones, and assessment evidence

Plan backend systems with clear module boundaries and dependency rules. This skill helps select architecture patterns, organize business logic, and outline migration steps for systems that are easier to maintain and test.

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• Designing a new backend system
• Restructuring a monolithic application
• Defining shared architecture standards

Build visual AI systems that detect objects or divide images into labeled regions. This skill guides dataset preparation, model selection, training, evaluation, inference optimization, and deployment using frameworks such as PyTorch and Ultralytics.

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• Build an object detection pipeline
• Clean images and convert annotation formats
• Optimize a trained model for deployment

Investigate recurring problems by mapping feedback loops, the cycles through which effects influence their causes. Identify underlying structures, match known patterns, and assess where changes could help and what unintended effects they might produce.

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• Investigating recurring incidents
• Understanding coordination problems as teams grow
• Assessing unintended effects before changing a policy

Plan and improve AI agent systems by managing the information models receive. This collection covers memory, agent coordination, tool design, context compression, evaluation, and the operating controls needed for reliable autonomous workflows.

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• Planning information management for a new AI agent
• Investigating failures in long agent conversations
• Designing agent memory and multi-agent coordination

Turn research code and experimental results into ML and AI paper drafts. Clarify the main contribution, connect claims to evidence, find and verify references, and prepare conference submissions using LaTeX templates and review checklists.

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• Drafting a paper from research code and results
• Revising the abstract and introduction around a clear contribution
• Finding related work and verifying references

Design controlled failure experiments for distributed systems to examine how services recover. Produce failure injection scripts, monitoring plans, rollback procedures, and exercise guides, then turn findings into documented improvements.

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• Planning controlled failure experiments
• Testing recovery after Kubernetes Pod failures
• Checking service behavior under network delays

Build MCP servers and clients that connect AI systems to external tools and data. The skill defines validated inputs, implements tool and resource handlers, configures communication methods, and checks protocol behavior with the MCP Inspector.

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• Expose external tools and data to AI systems through MCP
• Start an MCP project in TypeScript or Python
• Validate inputs and investigate protocol errors

Design and implement RAG systems, which retrieve documents to inform AI answers. Get document preparation strategies, vector database comparisons, combined keyword and meaning-based search, result reranking, and an evaluation plan for retrieval quality.

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• Design an AI application that answers using internal documents
• Compare vector databases and document splitting strategies
• Improve search through keyword matching and result reranking