#復古硬體
Live, measured metrics for the hashtag #復古硬體 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #復古硬體
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-24 07:17 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-24 07:17 UTCNo related tags with measured usage found for #復古硬體.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-24 07:17 UTCEverything below is measured over the latest 17 public posts (spanning ~6571 hours).
Posting hours (UTC) — busiest: 05:00
Languages: Chinese (Taiwan) (17)
Avg boosts / post: 0
Top of the latest posts
🌘 世嘉 CD 遊戲《Silpheed》的藝術與工程技術 ➤ 極致的硬體壓榨:揭祕經典太空射擊遊戲的幕後工程學 ✤ https://fabiensanglard.net/silpheed/index.html 在 90 年代中期 CD-ROM 技術崛起的背景下,世嘉 Mega-CD 平臺因過度依賴全動態影像(FMV)而評價兩極。然而,《Silpheed》卻憑藉卓越的藝術感與高度工程化的優化手段,成為該平臺的技術標竿。作者透過對該遊戲 FMV 格式的逆向工程,揭示了開發商 G
🌘 GitHub - w84death/floppinux:一張軟碟片上的嵌入式 Linux ➤ 極限技術挑戰:如何將現代 Linux 核心塞進 1.44MB 的空間裡 ✤ https://github.com/w84death/floppinux FLOPPINUX 是一個極致精簡的 Linux 發行版,僅需一張 1.44MB 的 3.5 吋軟碟片即可運作。該專案旨在打造一個能在極低硬體需求下(如 Intel 486DX 處理器、20MB RAM)啟動並提供基礎終端環境的
🌗 為 Behringer DDX3216 數位混音機從零開發 x86 BIOS 並運行 DOS ➤ 硬體極客的浪漫:在混音機上運行 DOS ✤ https://chrisdevblog.com/2026/06/08/running-dos-on-behringers-ddx3216-using-a-diy-x86-bios/ 這篇文章記錄了作者挑戰在 Behringer DDX3216 數位混音機上運行 DOS 作業系統的過程。該設備核心搭載了 AMD Elan SC30
#復古硬體 across platforms
every network with a public tag surfaceFollow #復古硬體 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/復古硬體