The HTTP protocol has used rarely in the devices to cloud in the IoT industry. Professionals usually consider MQTT as the standard of messaging protocol used in the Internet of Things (IoT). Few articles have mentioned using HTTP for devices transmission protocols.
This article investigates AWS Rest API and conducts the study about the feasibility of the HTTP protocol used from devices to cloud.
This post just archive all the vehicle image from Grand theft Auto: Liberty City Stories
Continue reading(For latest progress please refer to the thread -> here)
MTASA PORT
This is a project that ports the LCS map into MTASA. I will try to make the map as much as close to the original LCS atmosphere by using the MTASA engine provided. Since the model was ported from a mod : Re: Liberty City Stories, therefore in here, I must give the credit to the original author Ryadica926 for a big appropriate of his hard work! (The original Mod: https://gtaforums.com/topic/887066-re-liberty-city-stories/)
Continue readingRecently I’m working on a fun project of MTASA trying to convert a whole GTA: LCS Map into MTA: SA. one interesting fundings is MTA-SA LUA is case sensitive in file interpretation in contrast to the SA-MP platform.
Continue reading看来下次不乱折腾系统了，还好数据都备份了 =w=
World
[email protected]:~# world
bash: world: not foundMan
bash-3.2$ nice man woman
No manual entry for womanmake
bash-3.2$ make love
make: *** No rule to make target `love'. Stop.
Well，我也不知道改叫他啥，反正这里应该会包含关于 UTS My timetable -w- 在开发过程中的各种经历吧，例如想法，吐槽，不满，卖萌~ 嘛，反正我也不清楚具体有啥hhh
作者不提供对使用任何深度定制安卓，（例如：花瓣，蓝绿大厂、等），以及使用各种异端屏幕（刘海屏，水底屏，全面屏）出现的任何UI布局BUG不提供技术支持！
本app是基于react-native开发，理论上，是支持Android & iOS 平台，但是由于Apple对开发者的不友善的态度（你要发布App就要交$149 Aud），暂时不考虑提供iOS平台配布
最近利用假期的时间，开发一个针对我学校用的timetable课程表的软件，因为我学校的timetable软件是在的太难用了，特别是手机的完全自适应就是有毒。所以我就突然脑子一热，想开发个针对Android & Ios 可用的timetable app，也为了方便后辈们的生活。
Note: I’m not the expert in the machine learning area, so this is not a serious tutorial for the machine learning techniques. If you want to learn more about it, I highly recommend you to view some other video on youtube or coursera. e.g., Andrew ng’s tutorial series or 3Blue1Brown’s video if you want to have an overview of this area, or coding train, if you want to have fun with it :p
links are provided below.
According to the tutorials that introduced by the coding train, this time I’m trying to make a simple machine learning recipe (or you can call it algorithms) trying to predict some value based on the given input (in this stage, it still cannot called “learning”, but it is kind of the sprout of machine learning).
The scenario is simple; we want to predict the output based on some random data sets ( this means there’s no strong relationship between those data).
e.g. an simple ice cream sold relationships vs tempeture
Note:このメモはただはアイデア記録のつもり。