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Source channel @pushgoodcloud · Post #607 · 11月30日

#Lantau#大屿山 之前购买过的,可以联系 @ljfxz 退款,直接发机场邮箱给他 剩余价值退款按照( 剩余时长*时长单价)+(剩余流量*流量单价)的形式退款 流量单价=套餐价格*0.8/套餐流量总数 时长单价=套餐价格*0.2/套餐时长总数 例如轻量套餐价格为9元,流量为80G,时长为30天。那天数单价为(0.2*9)/30,流量单价为(0.8*9)/80。 此时轻量用户还剩10天,流量还有70G,那退款为10*[(0.2*9)/30] + 70*[(0.8*9)/80] 注* 充了流量的钱也可退

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搜索 #geolocation

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Libreware

@libreware · Post #1512 · 2025/09/28 11:58

Chasing Your Tail (CYT) https://github.com/ArgeliusLabs/Chasing-Your-Tail-NG A comprehensive #WiFi probe request analyzer that monitors and tracks wireless devices by analyzing their probe requests. The system integrates with #Kismet for packet capture and WiGLE API for #SSID#geolocation analysis, featuring advanced #surveillance#detection capabilities. Features Real-time Wi-Fi monitoring with Kismet integration Advanced surveillance detection with persistence scoring Automatic GPS integration - extracts coordinates from Bluetooth GPS via Kismet GPS correlation and location clustering (100m threshold) Spectacular KML visualization for Google Earth with professional styling and interactive content Multi-format reporting - Markdown, HTML (with pandoc), and KML outputs Time-window tracking (5, 10, 15, 20 minute windows) WiGLE API integration for SSID geolocation Multi-location tracking algorithms for detecting following behavior Enhanced GUI interface with surveillance analysis button Organized file structure with dedicated output directories Comprehensive logging and analysis tools Requirements Python 3.6+ Kismet wireless packet capture Wi-Fi adapter supporting monitor mode Linux-based system WiGLE API key (optional)

djangoproject

@djangoproject · Post #241 · 2017/01/25 13:30

http://www.aparat.com/v/4yGhH #Geolocation apps with #Django. Latitude, longitude, altitude, and even #iBeacons can be leveraged to enable geo-targeted experiences. But how do we build and optimize the server-side components to handle these requirements? Using a combination of libraries and techniques, we will illustrate these concepts. In this discussion everything from #map clustering and caching, to distance calculations and polygonal layering will be demonstrated using Django, #GeoDjango, #Redis, and #PostGIS as our tool belt.