A static website of a mobile devices store

Development of applications using the React Native framework on mobile operating systems: user interface, microservices and database for automation, testing and debugging purposes.

This project explores user authentication on mobile devices through typing patterns, leveraging touch and motion data. Using machine learning models, particularly LSTM, the research demonstrates superior user classification accuracy compared to traditional RNN models, enhancing security against ATO attacks.

Efficient offline route navigation with multi-criteria objectives on mobile devices

Utility for fetching mobile device(s) name(s). It uses DeviceSpecifications and a Google Programmable Search Engine to fetch the information based on provided model code(s).

Detect device is iOS or Android. 检测是iOS设备还是安卓设备。

This standard outlines the security requirements required to protect your organisational data and financial assets

🏄 A Lightweight Web Browser-based Machine Learning Framework

Bespoke OTA service for Planet Computers Ltd, supported by cloud-native technology.

This learning path provides system administrators with a comprehensive method for studying the skills tested in the CompTIA A+ (220-1001 and 220-1002) exams. It includes in-depth courses teaching skills from each exam domain and provides insights into resources you can use to prepare for the exam.

TransferCL: an open framework for transfer learning on mobile device

A collection of awesome framework, libraries, learning tutorials, videos, webcasts, technical resources and cool stuff about iOS Security.

Collective Knowledge workflow for ARM's workload automation tool: an open framework for gathering and sharing knowledge about system design and optimization using real-world workloads.

Public scenarios to crowdsource experiments (such as DNN crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework across diverse mobile devices provided by volunteers. Results are continuously aggregated at the open repository of knowledge:

Android application to participate in experiment crowdsourcing (such as workload crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework and open repositories of knowledge:

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

An NPM package written in React used to preview mobile devices. Especially helpful when used in combination with a CMS like Sanity.

Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:

PeleeNet in PyTorch