ipsn-experiments
De la autor
Use when designing or auditing IPSN-lineage evaluations, covering real testbeds and deployments, ground-truth instrumentation, energy/latency/footprint measurement on real hardware, on-device/TinyML profiling, estimation-theoretic baselines and bounds, and matching evidence to the shape of each sensing claim across the IP and SPOTS tracks.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-experiments -a claude-code
Se instalează în .claude/skills/ipsn-experiments/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 88
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- nsdi-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an NSDI submission — choosing traces, testbeds, and deployment evidence, sizing scale and failure-injection experiments, picking baselines that fight back, and reporting tail behavior so networked-systems reviewers can see where the design wins, loses, and breaks.DevOps★ 1.3K
- ipsn-submissionbrycewang-stanford/Awesome-Journal-SkillsUse when auditing an IPSN-lineage submission for HotCRP readiness, covering the IP-vs-SPOTS track choice, the ACM Primary Article Template and ≤12-page inclusive budget, the double-blind sweep for hardware/deployment papers, dataset/artifact links, and desk-reject triage — routed to the current successor (SenSys) call because IPSN no longer runs standalone.DevOps★ 1.3K
- socc-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing ACM SoCC evaluations, covering real or realistic deployments over simulation, production or representative workloads and traces, tail-latency and cost as first-class metrics, fair tuned baselines, scale and multi-tenancy behavior, reproducible measurement pipelines, and matching evidence to the shape of each cloud claim.DevOps★ 1.3K
- ndss-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing between testbed, emulation, and live experiments and meeting NDSS's deployment-realism evidence bar.DevOps★ 1.3K
- sosp-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a SOSP paper — mapping every claim to an experiment, choosing baselines a systems PC will accept as fair, mixing microbenchmarks with end-to-end and failure runs, reporting tails and overheads honestly, and isolating the mechanism the design credits.Design★ 1.3K
- cikm-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the empirical program of a CIKM paper — matching evidence to the claim's lanes across retrieval, mining, and knowledge-management evaluation cultures, choosing datasets and baselines that survive a blended panel, isolating the boundary mechanism, and meeting applied-track deployment-evidence bars.DevOps★ 1.3K
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